Using Multi-layer Perceptron and Convolutional Neural Networks for Satellite image classification - 2023
Antonio Fonseca
Packages to be installed:
conda install -c conda-forge umap-learn
pip install phate
conda install -c conda-forge imageio
pip install wandb
[ ]:
import numpy as np
import codecs
import copy
import json
import scipy.io
from scipy.spatial.distance import cdist, pdist, squareform
from scipy.linalg import eigh
import matplotlib.pyplot as plt
from sklearn.cluster import KMeans
import random
from sklearn import manifold
import os
# import phate
# import umap
import pandas as pd
# import scprep
from torch.nn import functional as F
import pandas as pd
from sklearn.metrics import r2_score
from sklearn.preprocessing import MinMaxScaler
# import seaborn as sns
import torch
from torch.utils.data import Dataset, DataLoader
from torch.utils.data.sampler import SubsetRandomSampler,RandomSampler
from torchvision import datasets, transforms
from torch.nn.functional import softmax
from torch import optim, nn
import torchvision
import torchvision.transforms as transforms
import torchvision.datasets as datasets
import time
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
print(device)
/gpfs/gibbs/project/dijk/ahf38/conda_envs/geo_comp2/lib/python3.8/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html
from .autonotebook import tqdm as notebook_tqdm
/gpfs/gibbs/project/dijk/ahf38/conda_envs/geo_comp2/lib/python3.8/site-packages/torchvision/io/image.py:13: UserWarning: Failed to load image Python extension: /gpfs/gibbs/project/dijk/ahf38/conda_envs/geo_comp2/lib/python3.8/site-packages/torchvision/image.so: undefined symbol: _ZN5torch3jit17parseSchemaOrNameERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEE
warn(f"Failed to load image Python extension: {e}")
cuda
Now that we have an autoencoder working on MNIST, let’s use this model to visualize some geodata. For the next section we will use the SAT-6 (https://csc.lsu.edu/~saikat/deepsat/)
SAT-6 consists of a total of 405,000 image patches each of size 28x28 and covering 6 landcover classes - barren land, trees, grassland, roads, buildings and water bodies. 324,000 images (comprising of four-fifths of the total dataset) were chosen as the training dataset and 81,000 (one fifths) were chosen as the testing dataset. Similar to SAT-4, the training and test sets were selected from disjoint NAIP tiles. Once generated, the images in the dataset were randomized in the same way as that for SAT-4. The specifications for the various landcover classes of SAT-4 and SAT-6 were adopted from those used in the National Land Cover Data (NLCD) algorithm.
The datasets are encoded as MATLAB .mat files that can be read using the standard load command in MATLAB. Each sample image is 28x28 pixels and consists of 4 bands - red, green, blue and near infrared. The training and test labels are 1x4 and 1x6 vectors for SAT-4 and SAT-6 respectively having a single 1 indexing a particular class from 0 through 4 or 6 and 0 values at all other indices.
The MAT file for the SAT-6 dataset contains the following variables:
train_x 28x28x4x324000 uint8 (containing 324000 training samples of 28x28 images each with 4 channels)
train_y 324000x6 uint8 (containing 6x1 vectors having labels for the 324000 training samples)
test_x 28x28x4x81000 uint8 (containing 81000 test samples of 28x28 images each with 4 channels)
test_y 81000x6 uint8 (containing 6x1 vectors having labels for the 81000 test samples)
Labels: - Building = 0 - Barren_land = 1 - Tree=2 - Grassland=3 - Road = 4 - Water = 5
[ ]:
import numpy as np
import scipy.io
import matplotlib.pyplot as plt
import torch
from torch import optim, nn
import wandb
import datetime
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
print(device)
cuda
[ ]:
# Using the satelite images dataset
###############################################################################
#load the data
data = scipy.io.loadmat("./SAT-4_and_SAT-6_datasets/sat-6-full.mat")
train_images = data['train_x']
train_labels = data['train_y']
test_images = data['test_x']
test_labels = data['test_y']
[ ]:
[ ]:
####################################################################
#Checkout the data
print('Training data shape : ', train_images.shape, train_labels.shape)
print('Testing data shape : ', test_images.shape, test_labels.shape)
Training data shape : (28, 28, 4, 324000) (6, 324000)
Testing data shape : (28, 28, 4, 81000) (6, 81000)
[ ]:
#Change the dimension to fit into the model
x_train = train_images.transpose(3,0,1,2)
t_train = train_labels.transpose()
# x_test = test_images.transpose(3,0,1,2)
# t_test = test_labels.transpose()
print('Training data shape : ', x_train.shape, t_train.shape)
# print('Testing data shape : ', x_test.shape, t_test.shape)
Training data shape : (324000, 28, 28, 4) (324000, 6)
[ ]:
#Check what is in each channel
fig,ax = plt.subplots(4,4, figsize=(10,10))
ax = ax.ravel()
list_idx = np.linspace(0,100,num=16,dtype=np.int64)
for count, idx in enumerate(list_idx):
# print(idx)
print('count, t_train[count,:]: {}, {}'.format(count, t_train[count,:]))
# print(x_train[idx,:,:,0:3])
ax[count].imshow(x_train[count,:,:,0:3])
ax[count].set_title(str(np.argmax(t_train[count,:])))
count, t_train[count,:]: 0, [0 0 1 0 0 0]
count, t_train[count,:]: 1, [0 1 0 0 0 0]
count, t_train[count,:]: 2, [0 0 0 0 0 1]
count, t_train[count,:]: 3, [0 0 0 0 0 1]
count, t_train[count,:]: 4, [0 0 0 0 0 1]
count, t_train[count,:]: 5, [1 0 0 0 0 0]
count, t_train[count,:]: 6, [1 0 0 0 0 0]
count, t_train[count,:]: 7, [0 0 0 0 0 1]
count, t_train[count,:]: 8, [0 1 0 0 0 0]
count, t_train[count,:]: 9, [0 0 1 0 0 0]
count, t_train[count,:]: 10, [0 0 0 0 0 1]
count, t_train[count,:]: 11, [0 1 0 0 0 0]
count, t_train[count,:]: 12, [0 1 0 0 0 0]
count, t_train[count,:]: 13, [0 0 0 0 1 0]
count, t_train[count,:]: 14, [0 0 0 0 0 1]
count, t_train[count,:]: 15, [0 0 1 0 0 0]

[ ]:
# split in training and testing
from torch.utils.data import Dataset, DataLoader
from torch.utils.data.sampler import SubsetRandomSampler
import torchvision.transforms as transforms
from scipy.ndimage import zoom
class MyDataset(Dataset):
def __init__(self, data, target):
print('data.dtype: {}'.format(data.dtype))
print('target.dtype: {}'.format(target.dtype))
self.data = torch.from_numpy(data).float()
self.target = torch.from_numpy(target).float()
def __getitem__(self, index):
x = self.data[index]
y = self.target[index]
return x, y
def __len__(self):
return len(self.data)
print('x_train.shape: {}'.format(x_train.shape))
n_samples = 50000
dataset = MyDataset(x_train[:n_samples,:,:,:], np.argmax(t_train[:n_samples],axis=1))
del x_train, t_train
dataset_size = len(dataset)
print('dataset_size: {}'.format(dataset_size))
test_split=0.2
batch_size=1024
# -- split dataset
indices = list(range(dataset_size))
split = int(np.floor(test_split*dataset_size))
print('split: {}'.format(split))
# np.random.shuffle(indices) # Randomizing the indices is not a good idea if you want to model the sequence
train_indices, val_indices = indices[split:], indices[:split]
# -- create dataloaders
# #Original
train_sampler = SubsetRandomSampler(train_indices)
valid_sampler = SubsetRandomSampler(val_indices)
dataloaders = {
'train': torch.utils.data.DataLoader(dataset, batch_size=batch_size, sampler=train_sampler),
'test': torch.utils.data.DataLoader(dataset, batch_size=batch_size, sampler=valid_sampler),
'all': torch.utils.data.DataLoader(dataset, batch_size=5000, shuffle=False),
}
x_train.shape: (324000, 28, 28, 4)
data.dtype: uint8
target.dtype: int64
dataset_size: 50000
split: 10000
[ ]:
class FFnet(nn.Module):
'''
Linear activation in the middle (instead of an activation function)
'''
def __init__(self):
super(FFnet, self).__init__()
self.enc_lin1 = nn.Linear(3136, 1000) # 28 x 28 x 4
self.enc_lin2 = nn.Linear(1000, 500)
self.enc_lin3 = nn.Linear(500, 250)
self.enc_lin4 = nn.Linear(250, 6)
self.relu = nn.ReLU()
self.tanh = nn.Tanh()
def encode(self, x):
x = self.enc_lin1(x)
x = self.relu(x)
x = self.enc_lin2(x)
x = self.relu(x)
x = self.enc_lin3(x)
x = self.relu(x)
output = self.enc_lin4(x)
return output
def forward(self, x):
z = self.encode(x)
return z
[ ]:
[ ]:
## Second routine for training and evaluation (using the )
# Training and Evaluation routines
import time
def train(model,loss_fn, optimizer, train_loader, test_loader, num_epochs=None, verbose=False):
"""
This is a standard training loop, which leaves some parts to be filled in.
INPUT:
:param model: an untrained pytorch model
:param loss_fn: e.g. Cross Entropy loss or Mean Squared Error.
:param optimizer: the model optimizer, initialized with a learning rate.
:param training_set: The training data, in a dataloader for easy iteration.
:param test_loader: The testing data, in a dataloader for easy iteration.
"""
print('optimizer: {}'.format(optimizer))
if num_epochs is None:
num_epochs = 100
print('n. of epochs: {}'.format(num_epochs))
for epoch in range(num_epochs+1):
start = time.time()
# loop through each data point in the training set
for data, targets in train_loader:
# run the model on the data
model_input = data.view(data.size(0),-1).to(device)# TODO: Turn the 28 by 28 image tensors into a 784 dimensional tensor.
if verbose: print('model_input.shape: {}'.format(model_input.shape))
# Clear gradients w.r.t. parameters
optimizer.zero_grad()
out = model(model_input) # The second output is the latent representation
if verbose:
print('targets.shape: {}'.format(targets.shape))
print('targets: {}'.format(targets))
print('out.shape: {}'.format(out.shape))
print('out: {}'.format(out))
# Calculate the loss
targets = targets.type(torch.LongTensor).to(device) # add an extra dimension to keep CrossEntropy happy.
if verbose: print('targets.shape: {}'.format(targets.shape))
loss = loss_fn(out,targets)
if verbose: print('loss: {}'.format(loss))
# Find the gradients of our loss via backpropogation
loss.backward()
# Adjust accordingly with the optimizer
optimizer.step()
# Give status reports every 100 epochs
loss_train, acc_train = evaluate(model,train_loader,verbose)
loss_test, acc_test = evaluate(model,test_loader,verbose)
if epoch % 10==0:
print(f" EPOCH {epoch}. Progress: {epoch/num_epochs*100}%. ")
print(" Train loss: {:.4f}. Train Acc: {:.4f}, Test loss: {:.4f}. Test Acc: {:.4f}. Time/epoch: {:.4f}".format(loss_train, acc_train, loss_test, acc_test, (time.time() - start))) #TODO: implement the evaluate function to provide performance statistics during training.
wandb.log({
"Loss/train": loss_train,
"Loss/val": loss_test,
"Accuracy/train": acc_train,
"Accuracy/val": acc_test,
"epoch": epoch
}, step=epoch)
def evaluate(model, evaluation_set, verbose=False):
"""
Evaluates the given model on the given dataset.
Returns the percentage of correct classifications out of total classifications.
"""
with torch.no_grad(): # this disables backpropogation, which makes the model run much more quickly.
correct = 0
total = 0
loss_all=0
for data, targets in evaluation_set:
targets= targets.to(device)
# run the model on the data
model_input = data.view(data.size(0),-1).to(device)# TODO: Turn the 28 by 28 image tensors into a 784 dimensional tensor.
if verbose:
print('model_input.shape: {}'.format(model_input.shape))
print('targets.shape: {}'.format(targets.shape))
out = model(model_input)
targets = targets.type(torch.LongTensor).to(device)
loss = loss_fn(out,targets)
if verbose: print('out[:5]: {}'.format(out[:5]))
loss_all+=loss.item()
# the class with the highest energy is what we choose as prediction
_, predicted = torch.max(out.data, 1)
total += targets.size(0)
correct += (predicted == targets).sum().item()
acc = 100 * correct / total
loss = loss_all/total
return loss, acc
[ ]:
lr_range = [0.01,0.005,0.001, 0.0001]
for lr in lr_range:
if 'model' in globals():
print('Deleting previous model')
del model, loss_fn, optimizer
model = FFnet().to(device)
DATETIME = datetime.datetime.now().strftime('%Y-%m-%d-%H_%M_%S')
wandb.init(project="GeoComp_Matera2023", entity="ahof1704", name="CNN_sat_FFnet_{}".format(DATETIME))
wandb.watch(model, log="all", log_freq=1)
optimizer = torch.optim.Adam(model.parameters(), lr = lr)
loss_fn = nn.CrossEntropyLoss().to(device)
train(model,loss_fn, optimizer, dataloaders['train'], dataloaders['test'],verbose=False)
Deleting previous model
Run history:
Accuracy/train | ▄▆▆▇▇████▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▄▆▆▇▇████▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | █▂▂▂▁▁▁▁▁▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ |
Loss/val | █▂▂▁▁▁▁▁▁▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.00154 |
Loss/val | 0.00153 |
epoch | 58 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_141005-tk5smslm/logs
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_141211-bdbijsdw
optimizer: Adam (
Parameter Group 0
amsgrad: False
betas: (0.9, 0.999)
capturable: False
eps: 1e-08
foreach: None
lr: 0.01
maximize: False
weight_decay: 0
)
n. of epochs: 100
EPOCH 0. Progress: 0.0%.
Train loss: 0.0008. Train Acc: 66.3475, Test loss: 0.0008. Test Acc: 66.8600. Time/epoch: 4.3759
EPOCH 10. Progress: 10.0%.
Train loss: 0.0004. Train Acc: 81.9250, Test loss: 0.0004. Test Acc: 81.8900. Time/epoch: 3.9911
EPOCH 20. Progress: 20.0%.
Train loss: 0.0002. Train Acc: 89.1425, Test loss: 0.0003. Test Acc: 88.6500. Time/epoch: 3.9714
EPOCH 30. Progress: 30.0%.
Train loss: 0.0002. Train Acc: 93.1425, Test loss: 0.0002. Test Acc: 92.5700. Time/epoch: 3.7580
EPOCH 40. Progress: 40.0%.
Train loss: 0.0015. Train Acc: 36.8250, Test loss: 0.0015. Test Acc: 37.5400. Time/epoch: 3.8162
EPOCH 50. Progress: 50.0%.
Train loss: 0.0015. Train Acc: 36.8250, Test loss: 0.0015. Test Acc: 37.5400. Time/epoch: 3.9956
EPOCH 60. Progress: 60.0%.
Train loss: 0.0015. Train Acc: 36.8250, Test loss: 0.0015. Test Acc: 37.5400. Time/epoch: 3.7411
EPOCH 70. Progress: 70.0%.
Train loss: 0.0015. Train Acc: 36.8250, Test loss: 0.0015. Test Acc: 37.5400. Time/epoch: 4.1185
EPOCH 80. Progress: 80.0%.
Train loss: 0.0015. Train Acc: 36.8250, Test loss: 0.0015. Test Acc: 37.5400. Time/epoch: 3.8451
EPOCH 90. Progress: 90.0%.
Train loss: 0.0015. Train Acc: 36.8250, Test loss: 0.0015. Test Acc: 37.5400. Time/epoch: 4.0117
EPOCH 100. Progress: 100.0%.
Train loss: 0.0015. Train Acc: 36.8250, Test loss: 0.0015. Test Acc: 37.5400. Time/epoch: 3.9103
Deleting previous model
Run history:
Accuracy/train | ▅▇▇█▇▇▅████▇██▄▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▅▇▇█▇▇▅████▇██▄▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁█▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁█▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.00154 |
Loss/val | 0.00153 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_141211-bdbijsdw/logs
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_141901-0dxs47tg
optimizer: Adam (
Parameter Group 0
amsgrad: False
betas: (0.9, 0.999)
capturable: False
eps: 1e-08
foreach: None
lr: 0.005
maximize: False
weight_decay: 0
)
n. of epochs: 100
EPOCH 0. Progress: 0.0%.
Train loss: 0.0005. Train Acc: 75.6150, Test loss: 0.0005. Test Acc: 75.5200. Time/epoch: 4.0944
EPOCH 10. Progress: 10.0%.
Train loss: 0.0003. Train Acc: 84.7850, Test loss: 0.0003. Test Acc: 84.7500. Time/epoch: 3.9586
EPOCH 20. Progress: 20.0%.
Train loss: 0.0002. Train Acc: 92.3075, Test loss: 0.0002. Test Acc: 91.8300. Time/epoch: 3.8414
EPOCH 30. Progress: 30.0%.
Train loss: 0.0002. Train Acc: 93.0650, Test loss: 0.0002. Test Acc: 92.7300. Time/epoch: 4.0199
EPOCH 40. Progress: 40.0%.
Train loss: 0.0002. Train Acc: 89.9625, Test loss: 0.0002. Test Acc: 89.8600. Time/epoch: 4.3224
EPOCH 50. Progress: 50.0%.
Train loss: 0.0002. Train Acc: 90.8100, Test loss: 0.0002. Test Acc: 90.1700. Time/epoch: 4.3020
EPOCH 60. Progress: 60.0%.
Train loss: 0.0005. Train Acc: 77.6900, Test loss: 0.0005. Test Acc: 77.7400. Time/epoch: 3.9768
EPOCH 70. Progress: 70.0%.
Train loss: 0.0003. Train Acc: 87.5625, Test loss: 0.0003. Test Acc: 87.5900. Time/epoch: 3.8873
EPOCH 80. Progress: 80.0%.
Train loss: 0.0003. Train Acc: 87.9400, Test loss: 0.0003. Test Acc: 87.7400. Time/epoch: 4.0226
EPOCH 90. Progress: 90.0%.
Train loss: 0.0002. Train Acc: 93.2150, Test loss: 0.0002. Test Acc: 92.6300. Time/epoch: 4.4531
EPOCH 100. Progress: 100.0%.
Train loss: 0.0002. Train Acc: 92.7275, Test loss: 0.0002. Test Acc: 92.2400. Time/epoch: 3.9699
Deleting previous model
Run history:
Accuracy/train | ▁▁▄▇▄▇▇▅▇▇▇▇█▇▇▆▇███▇▃▄▂▆▆▅▆▇▅▇▇▆▇▇▇▇▇██ |
Accuracy/val | ▁▁▄▇▅▇▇▅▇▇▇▇█▇▇▆▇███▇▃▄▂▆▆▅▆▇▅▇▇▆▇▇▇▇▇▇▇ |
Loss/train | ▇█▄▂▄▂▂▄▂▂▂▂▁▂▃▃▂▁▁▁▁█▄▆▃▃▄▃▂▃▂▂▂▂▂▁▂▂▁▁ |
Loss/val | ▇█▄▂▄▂▂▄▂▂▂▂▁▂▃▃▂▁▁▁▁█▄▆▃▃▄▃▂▃▂▂▂▂▂▂▂▂▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 92.7275 |
Accuracy/val | 92.24 |
Loss/train | 0.00016 |
Loss/val | 0.00017 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_141901-0dxs47tg/logs
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_142559-stjo6gi9
optimizer: Adam (
Parameter Group 0
amsgrad: False
betas: (0.9, 0.999)
capturable: False
eps: 1e-08
foreach: None
lr: 0.001
maximize: False
weight_decay: 0
)
n. of epochs: 100
EPOCH 0. Progress: 0.0%.
Train loss: 0.0005. Train Acc: 78.5275, Test loss: 0.0005. Test Acc: 78.4300. Time/epoch: 4.0875
EPOCH 10. Progress: 10.0%.
Train loss: 0.0003. Train Acc: 88.7000, Test loss: 0.0003. Test Acc: 88.5600. Time/epoch: 3.8260
EPOCH 20. Progress: 20.0%.
Train loss: 0.0002. Train Acc: 92.8550, Test loss: 0.0002. Test Acc: 92.3100. Time/epoch: 3.9107
EPOCH 30. Progress: 30.0%.
Train loss: 0.0003. Train Acc: 85.9700, Test loss: 0.0003. Test Acc: 85.9500. Time/epoch: 3.7582
EPOCH 40. Progress: 40.0%.
Train loss: 0.0002. Train Acc: 92.8800, Test loss: 0.0002. Test Acc: 92.4900. Time/epoch: 3.9415
EPOCH 50. Progress: 50.0%.
Train loss: 0.0001. Train Acc: 94.0175, Test loss: 0.0002. Test Acc: 93.3500. Time/epoch: 3.8053
EPOCH 60. Progress: 60.0%.
Train loss: 0.0002. Train Acc: 92.9325, Test loss: 0.0002. Test Acc: 92.3500. Time/epoch: 4.0517
EPOCH 70. Progress: 70.0%.
Train loss: 0.0002. Train Acc: 92.4325, Test loss: 0.0002. Test Acc: 91.9600. Time/epoch: 4.0073
EPOCH 80. Progress: 80.0%.
Train loss: 0.0002. Train Acc: 92.7200, Test loss: 0.0002. Test Acc: 92.0100. Time/epoch: 3.7292
EPOCH 90. Progress: 90.0%.
Train loss: 0.0001. Train Acc: 96.1825, Test loss: 0.0001. Test Acc: 95.4600. Time/epoch: 4.0354
EPOCH 100. Progress: 100.0%.
Train loss: 0.0001. Train Acc: 93.8075, Test loss: 0.0002. Test Acc: 92.5900. Time/epoch: 4.2393
Deleting previous model
Run history:
Accuracy/train | ▁▁▁▁▅▃▇▇▇▇▆▇▄▆▇▆▇█▅▇▇▇▇▄▇▅▇▇▆▆▇▇▇▇▇▇▇██▇ |
Accuracy/val | ▁▂▂▂▅▃▇▇▇▇▆▇▄▆▇▆▇█▅▇▇█▇▄█▆▇▇▆▆▇▇▇▇▇▇███▇ |
Loss/train | ▇█▅█▄▅▃▃▂▃▂▂▄▃▂▃▂▁▃▂▂▂▂▄▁▃▂▂▃▃▂▂▁▂▁▂▁▁▁▂ |
Loss/val | ▇█▅█▄▅▃▂▂▂▂▂▄▂▂▂▂▁▃▁▂▂▂▄▁▃▂▂▃▃▂▂▁▂▁▂▁▁▁▂ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 93.8075 |
Accuracy/val | 92.59 |
Loss/train | 0.00015 |
Loss/val | 0.00018 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_142559-stjo6gi9/logs
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_143250-rhx17fj2
optimizer: Adam (
Parameter Group 0
amsgrad: False
betas: (0.9, 0.999)
capturable: False
eps: 1e-08
foreach: None
lr: 0.0001
maximize: False
weight_decay: 0
)
n. of epochs: 100
EPOCH 0. Progress: 0.0%.
Train loss: 0.0004. Train Acc: 81.5800, Test loss: 0.0004. Test Acc: 81.4000. Time/epoch: 4.6343
EPOCH 10. Progress: 10.0%.
Train loss: 0.0002. Train Acc: 91.4275, Test loss: 0.0002. Test Acc: 91.2600. Time/epoch: 3.9659
EPOCH 20. Progress: 20.0%.
Train loss: 0.0003. Train Acc: 86.6925, Test loss: 0.0003. Test Acc: 86.5700. Time/epoch: 4.0900
EPOCH 30. Progress: 30.0%.
Train loss: 0.0002. Train Acc: 93.3275, Test loss: 0.0002. Test Acc: 93.0000. Time/epoch: 3.7836
EPOCH 40. Progress: 40.0%.
Train loss: 0.0003. Train Acc: 86.7875, Test loss: 0.0003. Test Acc: 86.6300. Time/epoch: 3.9666
EPOCH 50. Progress: 50.0%.
Train loss: 0.0003. Train Acc: 86.1525, Test loss: 0.0003. Test Acc: 86.0300. Time/epoch: 4.4136
EPOCH 60. Progress: 60.0%.
Train loss: 0.0003. Train Acc: 89.4050, Test loss: 0.0003. Test Acc: 88.9200. Time/epoch: 4.2230
EPOCH 70. Progress: 70.0%.
Train loss: 0.0001. Train Acc: 95.5700, Test loss: 0.0001. Test Acc: 94.6200. Time/epoch: 4.1061
EPOCH 80. Progress: 80.0%.
Train loss: 0.0001. Train Acc: 96.5025, Test loss: 0.0001. Test Acc: 95.6900. Time/epoch: 4.3656
EPOCH 90. Progress: 90.0%.
Train loss: 0.0002. Train Acc: 92.6275, Test loss: 0.0002. Test Acc: 91.9200. Time/epoch: 4.0278
EPOCH 100. Progress: 100.0%.
Train loss: 0.0001. Train Acc: 97.1175, Test loss: 0.0001. Test Acc: 96.3000. Time/epoch: 3.7401
Using CNNs for a image dataset
[ ]:
class CNNet(nn.Module):
def __init__(self):
super().__init__()
self.conv1 = nn.Conv2d(4, 6, 5)
self.pool = nn.MaxPool2d(2, 2)
self.conv2 = nn.Conv2d(6, 16, 5)
self.fc1 = nn.Linear(16 * 4 * 4, 120)
self.fc2 = nn.Linear(120, 84)
self.fc3 = nn.Linear(84, 6)
def forward(self, x):
x = self.pool(F.relu(self.conv1(x)))
x = self.pool(F.relu(self.conv2(x)))
x = torch.flatten(x, 1) # flatten all dimensions except batch
x = F.relu(self.fc1(x))
x = F.relu(self.fc2(x))
x = self.fc3(x)
return x
model = CNNet()
[ ]:
# Training and Evaluation routines
import time
def train(model,loss_fn, optimizer, train_loader, test_loader, num_epochs=None, verbose=False):
"""
This is a standard training loop, which leaves some parts to be filled in.
INPUT:
:param model: an untrained pytorch model
:param loss_fn: e.g. Cross Entropy loss of Mean Squared Error.
:param optimizer: the model optimizer, initialized with a learning rate.
:param training_set: The training data, in a dataloader for easy iteration.
:param test_loader: The testing data, in a dataloader for easy iteration.
"""
print('optimizer: {}'.format(optimizer))
if num_epochs is None:
num_epochs = 100
print('n. of epochs: {}'.format(num_epochs))
for epoch in range(num_epochs+1):
start = time.time()
# loop through each data point in the training set
for data, targets in train_loader:
# run the model on the data
model_input = data.permute(0, 3, 2, 1).to(device)
if verbose: print('model_input.shape: {}'.format(model_input.shape))
# Clear gradients w.r.t. parameters
optimizer.zero_grad()
out = model(model_input) # The second output is the latent representation
if verbose:
print('targets.shape: {}'.format(targets.shape))
print('targets: {}'.format(targets))
print('out.shape: {}'.format(out.shape))
print('out: {}'.format(out))
# Calculate the loss
targets = targets.type(torch.LongTensor).to(device) # add an extra dimension to keep CrossEntropy happy.
if verbose: print('targets.shape: {}'.format(targets.shape))
loss = loss_fn(out,targets)
if verbose: print('loss: {}'.format(loss))
# Find the gradients of our loss via backpropogation
loss.backward()
# Adjust accordingly with the optimizer
optimizer.step()
# Give status reports every 100 epochs
if epoch % 10==0:
print(f" EPOCH {epoch}. Progress: {epoch/num_epochs*100}%. ")
loss_train, acc_train = evaluate(model,train_loader,verbose)
loss_test, acc_test = evaluate(model,test_loader,verbose)
print(" Train loss: {:.4f}. Train Acc: {:.4f}, Test loss: {:.4f}. Test Acc: {:.4f}. Time/epoch: {:.4f}".format(loss_train, acc_train, loss_test, acc_test, (time.time() - start))) #TODO: implement the evaluate function to provide performance statistics during training.
def evaluate(model, evaluation_set, verbose=False):
"""
Evaluates the given model on the given dataset.
Returns the percentage of correct classifications out of total classifications.
"""
with torch.no_grad(): # this disables backpropogation, which makes the model run much more quickly.
correct = 0
total = 0
loss_all=0
for data, targets in evaluation_set:
# run the model on the data
model_input = data.permute(0, 3, 2, 1).to(device)
if verbose:
print('model_input.shape: {}'.format(model_input.shape))
print('targets.shape: {}'.format(targets.shape))
out = model(model_input)
targets = targets.type(torch.LongTensor)
loss = loss_fn(out,targets)
if verbose: print('out[:5]: {}'.format(out[:5]))
loss_all+=loss.item()
# the class with the highest energy is what we choose as prediction
_, predicted = torch.max(out.data, 1)
total += targets.size(0)
correct += (predicted == targets).sum().item()
acc = 100 * correct / total
loss = loss_all/total
return loss, acc
[ ]:
lr_range = [0.01,0.005,0.001]
for lr in lr_range:
if 'model' in globals():
print('Deleting previous model')
del model, loss_fn, optimizer
model = CNNet().to(device)
optimizer = torch.optim.Adam(model.parameters(), lr = lr)
loss_fn = nn.CrossEntropyLoss().to(device)
train(model,loss_fn, optimizer, dataloaders['train'], dataloaders['test'],verbose=False)
Deleting previous model
---------------------------------------------------------------------------
NameError Traceback (most recent call last)
Cell In[14], line 6
4 if 'model' in globals():
5 print('Deleting previous model')
----> 6 del model, loss_fn, optimizer
7 model = CNNet().to(device)
8 optimizer = torch.optim.Adam(model.parameters(), lr = lr)
NameError: name 'loss_fn' is not defined
Define Your Neural Network
Before we can run the sweep, let’s define a function that creates and trains our neural network.
In the function below, we define a simple CNN in Pytorch, and add the following lines of code to log models metrics, visualize performance and output and track our experiments easily:
wandb.init() – Initialize a new W&B run. Each run is single execution of the training script.
wandb.config – Save all your hyperparameters in a config object. This lets you use our app to sort and compare your runs by hyperparameter values.
callbacks=[WandbCallback()] – Fetch all layer dimensions, model parameters and log them automatically to your W&B dashboard.
wandb.log() – Logs custom objects – these can be images, videos, audio files, HTML, plots, point clouds etc. Here we use wandb.log to log images of Simpson characters overlaid with actual and predicted labels.
Sweeping with WandB
[ ]:
# Configure the sweep – specify the parameters to search through, the search strategy, the optimization metric et all.
sweep_config = {
'method': 'random', #grid, random
'metric': {
'name': 'Accuracy/val',
'goal': 'maximize'
},
'parameters': {
'epochs': {
'values': [10, 20, 50]
},
'batch_size': {
'values': [32,64,128]
},
'weight_decay': {
'values': [0.0005, 0.005, 0.05]
},
'learning_rate': {
'values': [1e-2, 1e-3, 1e-4, 3e-4, 3e-5, 1e-5]
},
'optimizer': {
'values': ['adam', 'sgd', 'rmsprop']
}
}
}
[ ]:
# Initialize a new sweep
# Arguments:
# – sweep_config: the sweep config dictionary defined above
# – entity: Set the username for the sweep
# – project: Set the project name for the sweep
sweep_id = wandb.sweep(sweep_config, entity="ahof1704", project="CNN_Sat_sweep")
Create sweep with ID: 4bmop0um
Sweep URL: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
[ ]:
class CNNet(nn.Module):
def __init__(self):
super().__init__()
self.conv1 = nn.Conv2d(4, 6, 5)
self.pool = nn.MaxPool2d(2, 2)
self.conv2 = nn.Conv2d(6, 16, 5)
self.fc1 = nn.Linear(16 * 4 * 4, 120)
self.fc2 = nn.Linear(120, 84)
self.fc3 = nn.Linear(84, 6)
def forward(self, x):
x = self.pool(F.relu(self.conv1(x)))
x = self.pool(F.relu(self.conv2(x)))
x = torch.flatten(x, 1) # flatten all dimensions except batch
x = F.relu(self.fc1(x))
x = F.relu(self.fc2(x))
x = self.fc3(x)
return x
model = CNNet()
[ ]:
# Training and Evaluation routines for Sweeping
import time
loss_fn = nn.CrossEntropyLoss().to(device)
def train(config=None):
"""
This is a standard training loop, which leaves some parts to be filled in.
INPUT:
:param model: an untrained pytorch model
:param loss_fn: e.g. Cross Entropy loss of Mean Squared Error.
:param optimizer: the model optimizer, initialized with a learning rate.
:param training_set: The training data, in a dataloader for easy iteration.
:param test_loader: The testing data, in a dataloader for easy iteration.
"""
with wandb.init(config=config):
verbose=False
model = CNNet().to(device)
model.train()
# Config is a variable that holds and saves hyperparameters and inputs
config = wandb.config
print('optimizer: {}'.format(config.optimizer))
# Define the optimizer
if config.optimizer=='sgd':
optimizer = torch.optim.SGD(model.parameters(), lr=config.learning_rate, weight_decay=config.weight_decay, momentum=0.9, nesterov=True)
elif config.optimizer=='rmsprop':
optimizer = torch.optim.RMSprop(model.parameters(), lr=config.learning_rate, weight_decay=config.weight_decay)
elif config.optimizer=='adam':
optimizer = torch.optim.Adam(model.parameters(), lr=config.learning_rate, betas=(0.9, 0.999))
# -- create dataloaders
train_sampler = SubsetRandomSampler(train_indices)
valid_sampler = SubsetRandomSampler(val_indices)
dataloaders = {
'train': torch.utils.data.DataLoader(dataset, batch_size=config.batch_size, sampler=train_sampler),
'test': torch.utils.data.DataLoader(dataset, batch_size=config.batch_size, sampler=valid_sampler),
'all': torch.utils.data.DataLoader(dataset, batch_size=5000, shuffle=False),
}
train_loader = dataloaders['train']
test_loader = dataloaders['test']
for epoch in range(config.epochs+1):
start = time.time()
# loop through each data point in the training set
for data, targets in train_loader:
# run the model on the data
model_input = data.permute(0, 3, 2, 1).to(device)
if verbose: print('model_input.shape: {}'.format(model_input.shape))
# Clear gradients w.r.t. parameters
optimizer.zero_grad()
out = model(model_input) # The second output is the latent representation
if verbose:
print('targets.shape: {}'.format(targets.shape))
print('targets: {}'.format(targets))
print('out.shape: {}'.format(out.shape))
print('out: {}'.format(out))
# Calculate the loss
targets = targets.type(torch.LongTensor).to(device) # add an extra dimension to keep CrossEntropy happy.
if verbose: print('targets.shape: {}'.format(targets.shape))
loss = loss_fn(out,targets)
if verbose: print('loss: {}'.format(loss))
# Find the gradients of our loss via backpropogation
loss.backward()
# Adjust accordingly with the optimizer
optimizer.step()
loss_train, acc_train = evaluate(model,train_loader,verbose)
loss_test, acc_test = evaluate(model,test_loader,verbose)
# Give status reports every 100 epochs
if epoch % 10==0:
print(f" EPOCH {epoch}. Progress: {epoch/config.epochs*100}%. ")
print(" Train loss: {:.4f}. Train Acc: {:.4f}, Test loss: {:.4f}. Test Acc: {:.4f}. Time/epoch: {:.4f}".format(loss_train, acc_train, loss_test, acc_test, (time.time() - start))) #TODO: implement the evaluate function to provide performance statistics during training.
wandb.log({
"Loss/train": loss_train,
"Loss/val": loss_test,
"Accuracy/train": acc_train,
"Accuracy/val": acc_test,
"epoch": epoch
}, step=epoch)
def evaluate(model, evaluation_set, verbose=False):
"""
Evaluates the given model on the given dataset.
Returns the percentage of correct classifications out of total classifications.
"""
model.eval()
with torch.no_grad(): # this disables backpropogation, which makes the model run much more quickly.
correct = 0
total = 0
loss_all=0
for data, targets in evaluation_set:
# run the model on the data
model_input = data.permute(0, 3, 2, 1).to(device)
if verbose:
print('model_input.shape: {}'.format(model_input.shape))
print('targets.shape: {}'.format(targets.shape))
out = model(model_input)
targets = targets.type(torch.LongTensor).to(device)
loss = loss_fn(out,targets)
if verbose: print('out[:5]: {}'.format(out[:5]))
loss_all+=loss.item()
# the class with the highest energy is what we choose as prediction
_, predicted = torch.max(out.data, 1)
total += targets.size(0)
correct += (predicted == targets).sum().item()
acc = 100 * correct / total
loss = loss_all/total
return loss, acc
[ ]:
wandb.agent(sweep_id, train)
wandb: Agent Starting Run: zzam8458 with config:
wandb: batch_size: 64
wandb: epochs: 10
wandb: learning_rate: 1e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230517_235613-zzam8458
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0088. Train Acc: 83.1675, Test loss: 0.0088. Test Acc: 83.3300. Time/epoch: 3.3380
EPOCH 10. Progress: 100.0%.
Train loss: 0.0028. Train Acc: 92.3525, Test loss: 0.0029. Test Acc: 92.4100. Time/epoch: 3.2960
Run history:
Accuracy/train | ▁▅▅▆▆▇▇▇▇██ |
Accuracy/val | ▁▄▅▆▆▇▇▇███ |
Loss/train | █▃▂▂▂▂▁▁▁▁▁ |
Loss/val | █▃▂▂▂▂▁▁▁▁▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 92.3525 |
Accuracy/val | 92.41 |
Loss/train | 0.00284 |
Loss/val | 0.00293 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230517_235613-zzam8458/logs
wandb: Agent Starting Run: oft3pjvq with config:
wandb: batch_size: 32
wandb: epochs: 50
wandb: learning_rate: 0.001
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230517_235703-oft3pjvq
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0099. Train Acc: 87.1850, Test loss: 0.0103. Test Acc: 86.9400. Time/epoch: 4.9065
EPOCH 10. Progress: 20.0%.
Train loss: 0.0049. Train Acc: 94.0975, Test loss: 0.0054. Test Acc: 93.6300. Time/epoch: 4.8879
EPOCH 20. Progress: 40.0%.
Train loss: 0.0035. Train Acc: 95.4450, Test loss: 0.0042. Test Acc: 94.4000. Time/epoch: 4.8633
EPOCH 30. Progress: 60.0%.
Train loss: 0.0038. Train Acc: 95.4750, Test loss: 0.0047. Test Acc: 94.5100. Time/epoch: 4.6823
EPOCH 40. Progress: 80.0%.
Train loss: 0.0052. Train Acc: 93.3300, Test loss: 0.0058. Test Acc: 92.8400. Time/epoch: 4.6711
EPOCH 50. Progress: 100.0%.
Train loss: 0.0033. Train Acc: 96.1875, Test loss: 0.0042. Test Acc: 95.2100. Time/epoch: 4.8509
Run history:
Accuracy/train | ▁▅▅▆▆▇▆▇▆▇▇▆▇▇▇▆▇▇▆█▇█▇▅▇▇▆█▇▆███▇██▇███ |
Accuracy/val | ▁▅▆▆▇▇▇▇▆█▇▇▇█▇▅▇▇▆█▇██▄▇█▆█▇▆█▇█▇██▇███ |
Loss/train | █▅▄▄▃▂▃▂▃▂▂▃▂▂▂▃▂▂▂▁▂▂▂▅▂▁▃▁▂▃▁▁▁▂▁▁▂▁▁▁ |
Loss/val | █▄▃▃▂▂▂▂▃▂▂▃▂▁▂▄▂▂▂▁▂▂▁▅▂▁▃▁▃▃▁▂▁▂▁▁▂▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 96.1875 |
Accuracy/val | 95.21 |
Loss/train | 0.00333 |
Loss/val | 0.00418 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230517_235703-oft3pjvq/logs
wandb: Agent Starting Run: 5l40buem with config:
wandb: batch_size: 32
wandb: epochs: 50
wandb: learning_rate: 3e-05
wandb: optimizer: sgd
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_000122-5l40buem
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0067. Train Acc: 91.3225, Test loss: 0.0069. Test Acc: 91.1800. Time/epoch: 4.6403
EPOCH 10. Progress: 20.0%.
Train loss: 0.0040. Train Acc: 94.8575, Test loss: 0.0042. Test Acc: 94.8800. Time/epoch: 4.6858
EPOCH 20. Progress: 40.0%.
Train loss: 0.0036. Train Acc: 95.1500, Test loss: 0.0038. Test Acc: 95.2500. Time/epoch: 4.6908
EPOCH 30. Progress: 60.0%.
Train loss: 0.0034. Train Acc: 95.7000, Test loss: 0.0035. Test Acc: 95.7100. Time/epoch: 4.5836
EPOCH 40. Progress: 80.0%.
Train loss: 0.0035. Train Acc: 95.5450, Test loss: 0.0036. Test Acc: 95.4700. Time/epoch: 4.5669
EPOCH 50. Progress: 100.0%.
Train loss: 0.0033. Train Acc: 95.9025, Test loss: 0.0035. Test Acc: 95.9200. Time/epoch: 4.6939
Run history:
Accuracy/train | ▁▂▅▅▄▇▆▇▆▆▆▇▇▆█▄▇▇▇▇█▇██████▇▇█▇▇█▇▇████ |
Accuracy/val | ▁▃▅▅▅▇▆▇▆▇▆▇▇▆█▅▇▇▇▆▇▇▇█████▇▇█▇▇█▇█████ |
Loss/train | █▆▄▄▅▃▃▃▂▂▃▂▂▃▂▄▂▂▂▂▂▂▂▁▁▁▁▁▁▂▁▁▂▁▁▁▁▁▁▁ |
Loss/val | █▆▄▄▅▃▃▃▃▂▂▂▂▃▂▄▂▂▂▂▂▂▂▁▁▁▁▁▁▂▁▁▂▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 95.9025 |
Accuracy/val | 95.92 |
Loss/train | 0.00333 |
Loss/val | 0.00346 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_000122-5l40buem/logs
wandb: Agent Starting Run: ycw8i34p with config:
wandb: batch_size: 32
wandb: epochs: 10
wandb: learning_rate: 0.01
wandb: optimizer: sgd
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_000536-ycw8i34p
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0481. Train Acc: 36.8250, Test loss: 0.0480. Test Acc: 37.5400. Time/epoch: 4.6145
EPOCH 10. Progress: 100.0%.
Train loss: 0.0480. Train Acc: 36.8250, Test loss: 0.0479. Test Acc: 37.5400. Time/epoch: 4.7618
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | ▆▄▃█▆▂▂▂▂▃▁ |
Loss/val | ▆▅▃█▃▃▁▂▂▃▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.04804 |
Loss/val | 0.04794 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_000536-ycw8i34p/logs
wandb: Agent Starting Run: jc5xf3r3 with config:
wandb: batch_size: 32
wandb: epochs: 10
wandb: learning_rate: 0.01
wandb: optimizer: sgd
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_000642-jc5xf3r3
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0481. Train Acc: 36.8250, Test loss: 0.0480. Test Acc: 37.5400. Time/epoch: 4.5855
EPOCH 10. Progress: 100.0%.
Train loss: 0.0481. Train Acc: 36.8250, Test loss: 0.0480. Test Acc: 37.5400. Time/epoch: 4.7293
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | ▄█▁▃▄▁▂▆█▂▃ |
Loss/val | ▃█▁▃▃▂▄▆█▁▂ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.0481 |
Loss/val | 0.04798 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_000642-jc5xf3r3/logs
wandb: Agent Starting Run: i7nmk94y with config:
wandb: batch_size: 128
wandb: epochs: 10
wandb: learning_rate: 1e-05
wandb: optimizer: sgd
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_000748-i7nmk94y
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0065. Train Acc: 73.8450, Test loss: 0.0065. Test Acc: 73.8100. Time/epoch: 2.1962
EPOCH 10. Progress: 100.0%.
Train loss: 0.0019. Train Acc: 90.5125, Test loss: 0.0020. Test Acc: 90.4400. Time/epoch: 2.3259
Run history:
Accuracy/train | ▁▄▅▆▆▇▇▇███ |
Accuracy/val | ▁▄▅▆▆▇▇▇███ |
Loss/train | █▅▃▃▂▂▂▁▁▁▁ |
Loss/val | █▅▃▃▂▂▂▁▁▁▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 90.5125 |
Accuracy/val | 90.44 |
Loss/train | 0.00192 |
Loss/val | 0.00196 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_000748-i7nmk94y/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: 8e2wk0j2 with config:
wandb: batch_size: 64
wandb: epochs: 20
wandb: learning_rate: 1e-05
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_000835-8e2wk0j2
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0068. Train Acc: 85.0775, Test loss: 0.0068. Test Acc: 85.7200. Time/epoch: 3.0562
EPOCH 10. Progress: 50.0%.
Train loss: 0.0025. Train Acc: 93.6550, Test loss: 0.0027. Test Acc: 93.5200. Time/epoch: 3.1775
EPOCH 20. Progress: 100.0%.
Train loss: 0.0022. Train Acc: 94.7350, Test loss: 0.0023. Test Acc: 94.4900. Time/epoch: 3.1338
Run history:
Accuracy/train | ▁▄▅▆▆▇▇▇▇▇▇▇█████████ |
Accuracy/val | ▁▄▅▆▆▇▇▇▇▇▇██████████ |
Loss/train | █▄▃▃▂▂▂▂▂▁▂▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▄▃▃▂▂▂▂▂▁▂▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 94.735 |
Accuracy/val | 94.49 |
Loss/train | 0.00217 |
Loss/val | 0.0023 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_000835-8e2wk0j2/logs
wandb: Agent Starting Run: 9olidkws with config:
wandb: batch_size: 32
wandb: epochs: 50
wandb: learning_rate: 3e-05
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_000955-9olidkws
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0068. Train Acc: 91.0925, Test loss: 0.0069. Test Acc: 90.8100. Time/epoch: 4.7435
EPOCH 10. Progress: 20.0%.
Train loss: 0.0047. Train Acc: 93.6450, Test loss: 0.0048. Test Acc: 93.8200. Time/epoch: 4.8731
EPOCH 20. Progress: 40.0%.
Train loss: 0.0039. Train Acc: 94.9900, Test loss: 0.0040. Test Acc: 95.1200. Time/epoch: 4.8602
EPOCH 30. Progress: 60.0%.
Train loss: 0.0052. Train Acc: 92.5125, Test loss: 0.0053. Test Acc: 92.6600. Time/epoch: 4.6839
EPOCH 40. Progress: 80.0%.
Train loss: 0.0036. Train Acc: 95.6250, Test loss: 0.0037. Test Acc: 95.6400. Time/epoch: 4.8334
EPOCH 50. Progress: 100.0%.
Train loss: 0.0036. Train Acc: 95.3300, Test loss: 0.0037. Test Acc: 95.5700. Time/epoch: 4.8268
Run history:
Accuracy/train | ▁▃▃▅▄▄▆▅▅▆▅▆▇▇▆▇▆▇▇▇▆▆▇█▃▇▇▇▇▆█▇█▆████▇▇ |
Accuracy/val | ▁▃▄▅▅▅▆▅▅▆▄▇▇▇▆▇▇▇▇▇▆▆▇█▃▇▇▇▇▆█▇█▇████▇▇ |
Loss/train | █▆▅▄▄▄▃▄▄▃▄▃▂▂▃▂▂▂▂▂▃▂▁▁▅▂▂▂▂▃▁▂▁▃▁▁▁▁▂▂ |
Loss/val | █▆▅▄▄▄▃▄▄▃▄▂▂▂▃▂▂▂▂▂▃▂▁▁▅▂▂▂▂▃▁▂▁▂▁▁▁▁▂▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 95.33 |
Accuracy/val | 95.57 |
Loss/train | 0.00357 |
Loss/val | 0.00366 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_000955-9olidkws/logs
wandb: Agent Starting Run: xwgaxq12 with config:
wandb: batch_size: 128
wandb: epochs: 50
wandb: learning_rate: 0.0003
wandb: optimizer: sgd
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_001419-xwgaxq12
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0018. Train Acc: 90.3100, Test loss: 0.0019. Test Acc: 90.2400. Time/epoch: 2.3505
EPOCH 10. Progress: 20.0%.
Train loss: 0.0012. Train Acc: 93.2350, Test loss: 0.0013. Test Acc: 93.2100. Time/epoch: 2.3292
EPOCH 20. Progress: 40.0%.
Train loss: 0.0009. Train Acc: 95.3875, Test loss: 0.0011. Test Acc: 94.9800. Time/epoch: 2.1884
EPOCH 30. Progress: 60.0%.
Train loss: 0.0006. Train Acc: 96.9850, Test loss: 0.0007. Test Acc: 96.5600. Time/epoch: 2.3183
EPOCH 40. Progress: 80.0%.
Train loss: 0.0006. Train Acc: 97.2925, Test loss: 0.0007. Test Acc: 96.8100. Time/epoch: 2.3052
EPOCH 50. Progress: 100.0%.
Train loss: 0.0005. Train Acc: 97.6450, Test loss: 0.0006. Test Acc: 97.1600. Time/epoch: 2.1686
Run history:
Accuracy/train | ▁▃▄▅▅▆▆▆▄▆▆▇▅▆▆▇▆▇▇▇▅▇▆▇▇▇▇▇███▇███▇▇███ |
Accuracy/val | ▁▃▄▅▅▆▆▆▄▆▆▇▅▆▆▇▆▇▇▇▅▇▆▇▇▇▇▇▇██▇█▇█▇▇█▇█ |
Loss/train | █▆▅▄▄▃▃▃▅▃▃▂▄▃▃▂▃▂▂▂▃▂▃▂▂▂▂▂▁▁▁▂▁▁▁▁▂▁▁▁ |
Loss/val | █▆▅▄▄▃▃▃▅▃▃▂▄▃▃▂▃▂▂▂▃▂▂▂▁▂▂▂▁▁▁▂▁▁▁▂▃▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 97.645 |
Accuracy/val | 97.16 |
Loss/train | 0.00049 |
Loss/val | 0.00063 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_001419-xwgaxq12/logs
wandb: Agent Starting Run: 3qr8irec with config:
wandb: batch_size: 32
wandb: epochs: 50
wandb: learning_rate: 1e-05
wandb: optimizer: sgd
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_001627-3qr8irec
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0119. Train Acc: 88.0000, Test loss: 0.0122. Test Acc: 87.8200. Time/epoch: 4.7784
EPOCH 10. Progress: 20.0%.
Train loss: 0.0055. Train Acc: 92.7175, Test loss: 0.0056. Test Acc: 92.7200. Time/epoch: 4.6236
EPOCH 20. Progress: 40.0%.
Train loss: 0.0050. Train Acc: 93.7725, Test loss: 0.0052. Test Acc: 93.5600. Time/epoch: 4.5725
EPOCH 30. Progress: 60.0%.
Train loss: 0.0047. Train Acc: 93.7725, Test loss: 0.0049. Test Acc: 93.9700. Time/epoch: 4.7329
EPOCH 40. Progress: 80.0%.
Train loss: 0.0040. Train Acc: 95.1700, Test loss: 0.0042. Test Acc: 95.1100. Time/epoch: 4.7364
EPOCH 50. Progress: 100.0%.
Train loss: 0.0041. Train Acc: 95.0375, Test loss: 0.0043. Test Acc: 94.8900. Time/epoch: 4.7085
Run history:
Accuracy/train | ▁▄▄▅▅▆▆▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇██▇████▇█▇█▇████▆█ |
Accuracy/val | ▁▄▄▅▅▆▆▆▆▇▆▇▇▇▇▇▆▇▇▇▇▇█▇▇████▇█▇█▇████▆█ |
Loss/train | █▄▄▃▃▂▂▂▂▂▂▂▂▂▂▁▂▂▂▂▁▂▁▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▂▁ |
Loss/val | █▄▄▃▃▃▂▂▂▂▂▂▂▂▂▁▂▂▂▂▁▂▁▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▂▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 95.0375 |
Accuracy/val | 94.89 |
Loss/train | 0.0041 |
Loss/val | 0.00427 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_001627-3qr8irec/logs
wandb: Agent Starting Run: t4osxxhb with config:
wandb: batch_size: 128
wandb: epochs: 20
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_002039-t4osxxhb
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0016. Train Acc: 91.7150, Test loss: 0.0016. Test Acc: 91.6600. Time/epoch: 2.3046
EPOCH 10. Progress: 50.0%.
Train loss: 0.0007. Train Acc: 96.3875, Test loss: 0.0008. Test Acc: 95.9900. Time/epoch: 2.4241
EPOCH 20. Progress: 100.0%.
Train loss: 0.0004. Train Acc: 97.8550, Test loss: 0.0006. Test Acc: 97.0100. Time/epoch: 2.4088
Run history:
Accuracy/train | ▁▃▄▅▅▆▆▆▇▆▆▆▇▆▇▇███▇█ |
Accuracy/val | ▁▄▄▆▅▇▆▇▇▇▇▆▇▆█▇███▇█ |
Loss/train | █▅▅▄▄▃▃▃▂▃▃▃▂▃▂▂▁▁▁▂▁ |
Loss/val | █▅▄▃▃▂▃▂▂▂▂▃▁▃▁▂▁▁▁▃▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 97.855 |
Accuracy/val | 97.01 |
Loss/train | 0.00044 |
Loss/val | 0.00063 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_002039-t4osxxhb/logs
wandb: Agent Starting Run: 3d41qa4k with config:
wandb: batch_size: 32
wandb: epochs: 20
wandb: learning_rate: 0.01
wandb: optimizer: adam
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_002141-3d41qa4k
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0481. Train Acc: 36.8250, Test loss: 0.0480. Test Acc: 37.5400. Time/epoch: 5.1893
EPOCH 10. Progress: 50.0%.
Train loss: 0.0480. Train Acc: 36.8250, Test loss: 0.0480. Test Acc: 37.5400. Time/epoch: 5.1383
EPOCH 20. Progress: 100.0%.
Train loss: 0.0480. Train Acc: 36.8250, Test loss: 0.0479. Test Acc: 37.5400. Time/epoch: 5.1727
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | ▆▅▄▄▄▆▅▅▂▆▂▂▁▇▄█▅▄▅▇▂ |
Loss/val | ▅█▂▁▃▇▆▇▄▆▅▅▂█▅▆▅▆▅▄▂ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.04805 |
Loss/val | 0.04793 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_002141-3d41qa4k/logs
wandb: Agent Starting Run: xvc9j71t with config:
wandb: batch_size: 32
wandb: epochs: 20
wandb: learning_rate: 0.0001
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_002342-xvc9j71t
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0060. Train Acc: 91.9650, Test loss: 0.0062. Test Acc: 91.7200. Time/epoch: 4.8781
EPOCH 10. Progress: 50.0%.
Train loss: 0.0121. Train Acc: 84.9550, Test loss: 0.0121. Test Acc: 85.3500. Time/epoch: 4.8153
EPOCH 20. Progress: 100.0%.
Train loss: 0.0035. Train Acc: 95.7625, Test loss: 0.0036. Test Acc: 95.7500. Time/epoch: 4.8847
Run history:
Accuracy/train | ▆▆▆▆▇▇▇▇▇█▁▇███▇█▇███ |
Accuracy/val | ▅▅▆▆▇▇▇▇▇█▁▇▇████▇███ |
Loss/train | ▃▃▂▂▂▂▂▁▂▂█▂▁▁▁▁▁▂▁▁▁ |
Loss/val | ▃▃▂▂▂▂▂▁▂▂█▂▁▁▁▁▁▂▁▁▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 95.7625 |
Accuracy/val | 95.75 |
Loss/train | 0.00353 |
Loss/val | 0.0036 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_002342-xvc9j71t/logs
wandb: Agent Starting Run: w3ttjtb4 with config:
wandb: batch_size: 128
wandb: epochs: 50
wandb: learning_rate: 0.0001
wandb: optimizer: sgd
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_002539-w3ttjtb4
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0018. Train Acc: 90.5200, Test loss: 0.0019. Test Acc: 90.5500. Time/epoch: 2.3806
EPOCH 10. Progress: 20.0%.
Train loss: 0.0010. Train Acc: 95.0050, Test loss: 0.0011. Test Acc: 94.8300. Time/epoch: 2.3062
EPOCH 20. Progress: 40.0%.
Train loss: 0.0009. Train Acc: 95.5125, Test loss: 0.0009. Test Acc: 95.4000. Time/epoch: 2.1862
EPOCH 30. Progress: 60.0%.
Train loss: 0.0008. Train Acc: 96.2875, Test loss: 0.0008. Test Acc: 96.1700. Time/epoch: 2.3307
EPOCH 40. Progress: 80.0%.
Train loss: 0.0009. Train Acc: 95.3725, Test loss: 0.0010. Test Acc: 95.1500. Time/epoch: 2.3377
EPOCH 50. Progress: 100.0%.
Train loss: 0.0009. Train Acc: 95.3175, Test loss: 0.0009. Test Acc: 95.4600. Time/epoch: 2.3253
Run history:
Accuracy/train | ▁▅▁▅▆▃▆▅▆▇▆▅▆▇▇▆▇▇▇▅▇▇█▇█▆▆▆▇█▇█▇█▇██▇▅▇ |
Accuracy/val | ▁▅▂▅▆▃▆▆▆▆▆▅▆▇▇▆▇▇▇▅▇▇█▇█▆▇▆▇███▇█▇██▇▅▇ |
Loss/train | █▅▇▄▃▅▃▄▃▂▃▄▃▂▂▂▂▂▂▃▂▂▁▂▁▃▂▃▂▁▁▁▂▁▂▁▁▂▃▂ |
Loss/val | █▅▇▄▃▅▃▃▃▃▂▄▃▂▂▂▂▂▂▃▂▂▁▂▁▃▂▃▁▁▁▁▂▁▂▁▁▂▃▂ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 95.3175 |
Accuracy/val | 95.46 |
Loss/train | 0.0009 |
Loss/val | 0.00093 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_002539-w3ttjtb4/logs
wandb: Agent Starting Run: 6kgluzmq with config:
wandb: batch_size: 32
wandb: epochs: 10
wandb: learning_rate: 0.0003
wandb: optimizer: sgd
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_002749-6kgluzmq
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0046. Train Acc: 93.9450, Test loss: 0.0048. Test Acc: 93.8200. Time/epoch: 4.6201
EPOCH 10. Progress: 100.0%.
Train loss: 0.0035. Train Acc: 95.2925, Test loss: 0.0039. Test Acc: 95.0600. Time/epoch: 4.7475
Run history:
Accuracy/train | ▄▁▄▆▇▄▇▇██▆ |
Accuracy/val | ▄▁▄▆▇▃▇▇██▆ |
Loss/train | ▅█▅▃▂▅▂▃▁▁▃ |
Loss/val | ▅█▆▃▂▅▂▃▁▁▃ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 95.2925 |
Accuracy/val | 95.06 |
Loss/train | 0.0035 |
Loss/val | 0.00385 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_002749-6kgluzmq/logs
wandb: Agent Starting Run: vn8tnx3k with config:
wandb: batch_size: 128
wandb: epochs: 10
wandb: learning_rate: 0.001
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_002855-vn8tnx3k
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0042. Train Acc: 76.6925, Test loss: 0.0043. Test Acc: 76.9400. Time/epoch: 2.2380
EPOCH 10. Progress: 100.0%.
Train loss: 0.0169. Train Acc: 58.1875, Test loss: 0.0170. Test Acc: 58.5100. Time/epoch: 2.3528
Run history:
Accuracy/train | ▆▇▇█▅▆██▅█▁ |
Accuracy/val | ▆▇██▅▆██▅█▁ |
Loss/train | ▂▂▁▂▂▂▁▁▂▁█ |
Loss/val | ▂▂▁▂▂▂▁▁▂▁█ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 58.1875 |
Accuracy/val | 58.51 |
Loss/train | 0.0169 |
Loss/val | 0.01697 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_002855-vn8tnx3k/logs
wandb: Agent Starting Run: 7m5xr9i9 with config:
wandb: batch_size: 64
wandb: epochs: 50
wandb: learning_rate: 0.01
wandb: optimizer: sgd
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_002936-7m5xr9i9
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0240. Test Acc: 37.5400. Time/epoch: 3.0138
EPOCH 10. Progress: 20.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 2.9350
EPOCH 20. Progress: 40.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 3.0977
EPOCH 30. Progress: 60.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0240. Test Acc: 37.5400. Time/epoch: 3.1260
EPOCH 40. Progress: 80.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0240. Test Acc: 37.5400. Time/epoch: 3.1197
EPOCH 50. Progress: 100.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0240. Test Acc: 37.5400. Time/epoch: 3.0731
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | ▃▂▂▁▅▂▁▃▅▁█▅▁▄▃▃▇▂▃▅▂▂▂▁▁▃▁▂▃▁▂▁▁▄▃▂▁▁▃▂ |
Loss/val | ▃▃▂▂▆▄▂▆▅▂█▅▂▅▄▄▄▂▃▅▅▆▃▄▂▆▁▃▃▄▃▂▄▄▂▃▃▄▃▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.02402 |
Loss/val | 0.02403 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_002936-7m5xr9i9/logs
wandb: Agent Starting Run: do2ct7u1 with config:
wandb: batch_size: 128
wandb: epochs: 50
wandb: learning_rate: 3e-05
wandb: optimizer: adam
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_003223-do2ct7u1
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0021. Train Acc: 90.2725, Test loss: 0.0022. Test Acc: 90.5000. Time/epoch: 2.4773
EPOCH 10. Progress: 20.0%.
Train loss: 0.0009. Train Acc: 95.6300, Test loss: 0.0009. Test Acc: 95.6800. Time/epoch: 2.4208
EPOCH 20. Progress: 40.0%.
Train loss: 0.0007. Train Acc: 96.4575, Test loss: 0.0008. Test Acc: 96.4900. Time/epoch: 2.4178
EPOCH 30. Progress: 60.0%.
Train loss: 0.0006. Train Acc: 96.9950, Test loss: 0.0007. Test Acc: 96.5600. Time/epoch: 2.2943
EPOCH 40. Progress: 80.0%.
Train loss: 0.0006. Train Acc: 97.2800, Test loss: 0.0006. Test Acc: 96.9200. Time/epoch: 2.4210
EPOCH 50. Progress: 100.0%.
Train loss: 0.0005. Train Acc: 97.6825, Test loss: 0.0006. Test Acc: 97.2500. Time/epoch: 2.4330
Run history:
Accuracy/train | ▁▃▄▄▅▅▅▆▆▆▆▆▇▇▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇█▇████████ |
Accuracy/val | ▁▃▄▄▅▅▅▆▆▆▆▇▇▇▆▇▇▇▇▇▇▆▇▇▇▇██▇▇██████████ |
Loss/train | █▅▅▄▄▃▃▃▃▃▃▂▂▂▃▂▂▂▂▂▂▃▂▂▁▂▁▁▂▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▅▅▄▄▃▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▁▂▁▁▂▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 97.6825 |
Accuracy/val | 97.25 |
Loss/train | 0.00051 |
Loss/val | 0.00062 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_003223-do2ct7u1/logs
wandb: Agent Starting Run: uchsrn45 with config:
wandb: batch_size: 64
wandb: epochs: 50
wandb: learning_rate: 0.01
wandb: optimizer: rmsprop
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_003440-uchsrn45
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0176. Train Acc: 55.3525, Test loss: 0.0178. Test Acc: 55.5500. Time/epoch: 3.2013
EPOCH 10. Progress: 20.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 3.1492
EPOCH 20. Progress: 40.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 3.1419
EPOCH 30. Progress: 60.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 3.0273
EPOCH 40. Progress: 80.0%.
Train loss: 0.0241. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 3.1642
EPOCH 50. Progress: 100.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 3.1493
Run history:
Accuracy/train | █▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | █▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | ▁███████████████████████████████████████ |
Loss/val | ▁███████████████████████████████████████ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.02405 |
Loss/val | 0.02409 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_003440-uchsrn45/logs
wandb: Agent Starting Run: oc0l1pdk with config:
wandb: batch_size: 128
wandb: epochs: 50
wandb: learning_rate: 0.0001
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_003732-oc0l1pdk
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0018. Train Acc: 88.6375, Test loss: 0.0018. Test Acc: 88.6900. Time/epoch: 2.2337
EPOCH 10. Progress: 20.0%.
Train loss: 0.0008. Train Acc: 96.1925, Test loss: 0.0008. Test Acc: 96.0400. Time/epoch: 2.3739
EPOCH 20. Progress: 40.0%.
Train loss: 0.0005. Train Acc: 97.7425, Test loss: 0.0006. Test Acc: 97.5600. Time/epoch: 2.3606
EPOCH 30. Progress: 60.0%.
Train loss: 0.0004. Train Acc: 98.0750, Test loss: 0.0006. Test Acc: 97.5400. Time/epoch: 2.3336
EPOCH 40. Progress: 80.0%.
Train loss: 0.0003. Train Acc: 98.4550, Test loss: 0.0005. Test Acc: 97.6800. Time/epoch: 2.2281
EPOCH 50. Progress: 100.0%.
Train loss: 0.0003. Train Acc: 98.6000, Test loss: 0.0006. Test Acc: 97.7000. Time/epoch: 2.3394
Run history:
Accuracy/train | ▁▂▂▅▆▆▆▆▆▆▇▆▅▆▆▇▇▇▇▇▇▇▅▇███▇█▇████████▇█ |
Accuracy/val | ▁▂▂▅▆▆▆▆▇▆▇▆▅▆▇▇███▇▇▇▅▇███▇█▇███▇▇███▇█ |
Loss/train | ███▅▄▄▃▃▃▃▃▄▄▃▃▂▂▂▂▂▂▂▅▂▂▁▁▂▂▂▁▁▁▁▁▁▁▁▂▁ |
Loss/val | ███▅▃▃▃▃▃▃▂▃▄▃▂▂▂▁▁▂▂▂▅▂▁▁▁▂▂▂▁▁▁▁▁▁▁▁▂▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.6 |
Accuracy/val | 97.7 |
Loss/train | 0.0003 |
Loss/val | 0.00055 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_003732-oc0l1pdk/logs
wandb: Agent Starting Run: xdwakrae with config:
wandb: batch_size: 64
wandb: epochs: 20
wandb: learning_rate: 0.001
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_003945-xdwakrae
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0104. Train Acc: 70.3125, Test loss: 0.0103. Test Acc: 70.9600. Time/epoch: 3.0324
EPOCH 10. Progress: 50.0%.
Train loss: 0.0019. Train Acc: 95.6000, Test loss: 0.0021. Test Acc: 95.4500. Time/epoch: 3.1860
EPOCH 20. Progress: 100.0%.
Train loss: 0.0016. Train Acc: 95.8350, Test loss: 0.0021. Test Acc: 95.1400. Time/epoch: 3.1535
Run history:
Accuracy/train | ▁▃▅▇▇▇▆▆▇██▇███████▇█ |
Accuracy/val | ▁▃▅▇▇▇▆▆▇██▇███████▇█ |
Loss/train | █▆▄▂▂▂█▃▂▂▁▂▁▁▁▁▁▁▁▂▁ |
Loss/val | ▇▅▄▂▂▂█▃▂▁▁▁▁▁▁▁▁▁▁▂▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 95.835 |
Accuracy/val | 95.14 |
Loss/train | 0.00164 |
Loss/val | 0.00205 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_003945-xdwakrae/logs
wandb: Agent Starting Run: cr02yzq9 with config:
wandb: batch_size: 32
wandb: epochs: 10
wandb: learning_rate: 0.0001
wandb: optimizer: adam
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_004106-cr02yzq9
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0045. Train Acc: 94.1700, Test loss: 0.0047. Test Acc: 94.2100. Time/epoch: 5.1689
EPOCH 10. Progress: 100.0%.
Train loss: 0.0025. Train Acc: 97.0225, Test loss: 0.0027. Test Acc: 96.5200. Time/epoch: 5.1706
Run history:
Accuracy/train | ▁▄▃▅▇▆▅▅▇▇█ |
Accuracy/val | ▁▄▃▅▇▇▅▅▇▇█ |
Loss/train | █▅▆▃▂▃▃▄▂▂▁ |
Loss/val | █▆▆▄▂▃▃▅▂▂▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 97.0225 |
Accuracy/val | 96.52 |
Loss/train | 0.00246 |
Loss/val | 0.00275 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_004106-cr02yzq9/logs
wandb: Agent Starting Run: cmkt7j2h with config:
wandb: batch_size: 64
wandb: epochs: 50
wandb: learning_rate: 0.0001
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_004217-cmkt7j2h
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0034. Train Acc: 90.8500, Test loss: 0.0035. Test Acc: 91.1100. Time/epoch: 3.2042
EPOCH 10. Progress: 20.0%.
Train loss: 0.0014. Train Acc: 96.5125, Test loss: 0.0016. Test Acc: 96.3200. Time/epoch: 3.1972
EPOCH 20. Progress: 40.0%.
Train loss: 0.0009. Train Acc: 97.7800, Test loss: 0.0011. Test Acc: 97.3000. Time/epoch: 3.1353
EPOCH 30. Progress: 60.0%.
Train loss: 0.0009. Train Acc: 97.5925, Test loss: 0.0012. Test Acc: 97.0900. Time/epoch: 3.0095
EPOCH 40. Progress: 80.0%.
Train loss: 0.0005. Train Acc: 98.8900, Test loss: 0.0009. Test Acc: 98.0400. Time/epoch: 2.9984
EPOCH 50. Progress: 100.0%.
Train loss: 0.0005. Train Acc: 98.8875, Test loss: 0.0010. Test Acc: 97.9200. Time/epoch: 3.1653
Run history:
Accuracy/train | ▁▃▄▄▅▄▃▅▆▆▆▆▆▆▇▄▇▇▇▇▇▇▇▇▇▇▆▇▇██▇████████ |
Accuracy/val | ▁▄▄▄▅▄▃▆▆▆▇▇▆▆▇▄▇▇▇▇▇▇██▇▇▆▇▆██▇█████▇▇█ |
Loss/train | █▆▅▅▄▅▆▄▃▃▃▃▃▄▂▅▂▂▂▂▂▂▂▂▂▂▃▂▂▁▁▂▁▁▁▁▁▁▁▁ |
Loss/val | █▅▅▅▄▄▆▃▃▃▂▂▃▃▂▅▂▂▂▂▂▂▁▁▂▂▃▂▂▁▁▂▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.8875 |
Accuracy/val | 97.92 |
Loss/train | 0.00047 |
Loss/val | 0.001 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_004217-cmkt7j2h/logs
wandb: Agent Starting Run: mq1zs0j2 with config:
wandb: batch_size: 128
wandb: epochs: 10
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_004510-mq1zs0j2
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0015. Train Acc: 91.7725, Test loss: 0.0015. Test Acc: 92.0400. Time/epoch: 2.2943
EPOCH 10. Progress: 100.0%.
Train loss: 0.0008. Train Acc: 96.0750, Test loss: 0.0009. Test Acc: 95.9700. Time/epoch: 2.3073
Run history:
Accuracy/train | ▃▁▅▄▆▆▇▆██▇ |
Accuracy/val | ▄▁▆▄▆▆▇▇██▇ |
Loss/train | ▆█▄▆▄▃▂▃▁▁▂ |
Loss/val | ▆█▃▆▄▃▂▃▁▁▂ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 96.075 |
Accuracy/val | 95.97 |
Loss/train | 0.00077 |
Loss/val | 0.00085 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_004510-mq1zs0j2/logs
wandb: Agent Starting Run: t25nlhl0 with config:
wandb: batch_size: 128
wandb: epochs: 50
wandb: learning_rate: 0.0003
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_004550-t25nlhl0
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0017. Train Acc: 90.7050, Test loss: 0.0018. Test Acc: 90.5800. Time/epoch: 2.3931
EPOCH 10. Progress: 20.0%.
Train loss: 0.0029. Train Acc: 85.2775, Test loss: 0.0030. Test Acc: 85.6400. Time/epoch: 2.2056
EPOCH 20. Progress: 40.0%.
Train loss: 0.0011. Train Acc: 93.8225, Test loss: 0.0011. Test Acc: 94.1100. Time/epoch: 2.3408
EPOCH 30. Progress: 60.0%.
Train loss: 0.0015. Train Acc: 91.7100, Test loss: 0.0016. Test Acc: 91.5500. Time/epoch: 2.3471
EPOCH 40. Progress: 80.0%.
Train loss: 0.0010. Train Acc: 94.9125, Test loss: 0.0010. Test Acc: 95.0100. Time/epoch: 2.3499
EPOCH 50. Progress: 100.0%.
Train loss: 0.0011. Train Acc: 94.4100, Test loss: 0.0011. Test Acc: 94.7400. Time/epoch: 2.2061
Run history:
Accuracy/train | ▆▆▅▅▇▃▇▇▃█▅▇▅▆▆▁▇█▇▆▇█▅▆▆▆█▇█▇██████████ |
Accuracy/val | ▅▆▅▅▇▃▇▇▃█▅▇▅▆▆▁▇█▇▆▇█▅▆▆▆█▇█▇██████████ |
Loss/train | ▃▃▃▃▂▆▂▂▆▁▄▂▄▂▃█▁▁▂▂▂▁▃▃▃▂▁▂▁▂▁▁▁▁▁▁▁▁▁▁ |
Loss/val | ▃▃▃▃▃▆▂▂▆▁▄▂▄▃▃█▁▁▂▂▂▁▃▃▃▂▁▂▁▂▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 94.41 |
Accuracy/val | 94.74 |
Loss/train | 0.00108 |
Loss/val | 0.0011 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_004550-t25nlhl0/logs
wandb: Agent Starting Run: xiqj6i11 with config:
wandb: batch_size: 64
wandb: epochs: 10
wandb: learning_rate: 0.001
wandb: optimizer: sgd
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_004759-xiqj6i11
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0075. Train Acc: 77.7025, Test loss: 0.0074. Test Acc: 78.1000. Time/epoch: 3.1311
EPOCH 10. Progress: 100.0%.
Train loss: 0.0031. Train Acc: 92.9450, Test loss: 0.0034. Test Acc: 92.3900. Time/epoch: 3.0820
Run history:
Accuracy/train | ▁▃▄▅▅▅▄▇▆██ |
Accuracy/val | ▁▂▄▅▅▅▄▆▆██ |
Loss/train | █▅▅▆▄▄▄▃▄▂▁ |
Loss/val | █▅▅▆▄▄▄▃▄▂▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 92.945 |
Accuracy/val | 92.39 |
Loss/train | 0.00312 |
Loss/val | 0.00339 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_004759-xiqj6i11/logs
wandb: Agent Starting Run: famk9f31 with config:
wandb: batch_size: 32
wandb: epochs: 10
wandb: learning_rate: 0.0003
wandb: optimizer: rmsprop
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_004848-famk9f31
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0062. Train Acc: 90.5375, Test loss: 0.0063. Test Acc: 90.7300. Time/epoch: 4.9297
EPOCH 10. Progress: 100.0%.
Train loss: 0.0032. Train Acc: 96.3000, Test loss: 0.0034. Test Acc: 96.2200. Time/epoch: 4.8901
Run history:
Accuracy/train | ▃▂▁▇▆█▅██▇█ |
Accuracy/val | ▃▂▁▇▆█▅██▇█ |
Loss/train | ▆█▇▂▃▁▄▁▁▂▂ |
Loss/val | ▆█▇▂▃▁▄▁▁▂▂ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 96.3 |
Accuracy/val | 96.22 |
Loss/train | 0.0032 |
Loss/val | 0.00339 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_004848-famk9f31/logs
wandb: Agent Starting Run: ytk8g35l with config:
wandb: batch_size: 32
wandb: epochs: 10
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_004953-ytk8g35l
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0082. Train Acc: 89.1525, Test loss: 0.0083. Test Acc: 89.5100. Time/epoch: 5.2215
EPOCH 10. Progress: 100.0%.
Train loss: 0.0031. Train Acc: 96.1425, Test loss: 0.0042. Test Acc: 94.8700. Time/epoch: 5.1365
Run history:
Accuracy/train | ▁▃▆▅▆▅▇████ |
Accuracy/val | ▁▃▆▅▆▅▇█▇█▇ |
Loss/train | █▆▄▄▃▄▂▁▁▁▁ |
Loss/val | █▆▃▃▃▄▂▁▁▁▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 96.1425 |
Accuracy/val | 94.87 |
Loss/train | 0.00307 |
Loss/val | 0.00423 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_004953-ytk8g35l/logs
wandb: Agent Starting Run: aec4ug5t with config:
wandb: batch_size: 128
wandb: epochs: 20
wandb: learning_rate: 3e-05
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_005103-aec4ug5t
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0020. Train Acc: 90.2800, Test loss: 0.0020. Test Acc: 90.5100. Time/epoch: 2.3997
EPOCH 10. Progress: 50.0%.
Train loss: 0.0012. Train Acc: 94.1325, Test loss: 0.0012. Test Acc: 94.1300. Time/epoch: 2.3393
EPOCH 20. Progress: 100.0%.
Train loss: 0.0012. Train Acc: 94.0325, Test loss: 0.0012. Test Acc: 94.1000. Time/epoch: 2.3384
Run history:
Accuracy/train | ▁▂▃▁▆▆▇▆▆▆▆▇▇███▇▇▆█▆ |
Accuracy/val | ▁▂▃▁▆▆▇▆▆▇▆▇▇███▇▇▇█▆ |
Loss/train | █▆▅▇▃▂▂▃▃▂▃▂▂▂▁▁▂▂▂▁▂ |
Loss/val | █▆▅▇▃▂▂▃▃▂▃▂▂▂▁▁▂▂▂▁▂ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 94.0325 |
Accuracy/val | 94.1 |
Loss/train | 0.00116 |
Loss/val | 0.00121 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_005103-aec4ug5t/logs
wandb: Agent Starting Run: pjh7m7v6 with config:
wandb: batch_size: 64
wandb: epochs: 20
wandb: learning_rate: 3e-05
wandb: optimizer: adam
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_005204-pjh7m7v6
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0039. Train Acc: 89.7025, Test loss: 0.0041. Test Acc: 89.3400. Time/epoch: 3.3796
EPOCH 10. Progress: 50.0%.
Train loss: 0.0016. Train Acc: 96.1050, Test loss: 0.0018. Test Acc: 96.0800. Time/epoch: 3.3007
EPOCH 20. Progress: 100.0%.
Train loss: 0.0013. Train Acc: 96.8500, Test loss: 0.0015. Test Acc: 96.6600. Time/epoch: 3.3318
Run history:
Accuracy/train | ▁▃▄▆▆▆▇▇▇▇▇▇▇▇█▇▇▇▇▇█ |
Accuracy/val | ▁▄▄▆▆▆▇▇▇▇▇▇▇██▇▇▇▇██ |
Loss/train | █▅▅▃▃▃▃▂▂▂▂▂▂▂▂▃▂▂▂▂▁ |
Loss/val | █▅▄▃▃▃▂▂▂▂▂▂▂▂▁▂▂▂▂▂▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 96.85 |
Accuracy/val | 96.66 |
Loss/train | 0.00132 |
Loss/val | 0.00147 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_005204-pjh7m7v6/logs
wandb: Agent Starting Run: k19vq8g3 with config:
wandb: batch_size: 128
wandb: epochs: 50
wandb: learning_rate: 3e-05
wandb: optimizer: sgd
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_005326-k19vq8g3
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0031. Train Acc: 87.0525, Test loss: 0.0031. Test Acc: 86.9800. Time/epoch: 2.3651
EPOCH 10. Progress: 20.0%.
Train loss: 0.0012. Train Acc: 93.9275, Test loss: 0.0013. Test Acc: 94.1100. Time/epoch: 2.3194
EPOCH 20. Progress: 40.0%.
Train loss: 0.0011. Train Acc: 94.6950, Test loss: 0.0011. Test Acc: 94.6200. Time/epoch: 2.3236
EPOCH 30. Progress: 60.0%.
Train loss: 0.0011. Train Acc: 93.9350, Test loss: 0.0012. Test Acc: 94.1100. Time/epoch: 2.1896
EPOCH 40. Progress: 80.0%.
Train loss: 0.0009. Train Acc: 95.4750, Test loss: 0.0010. Test Acc: 95.4700. Time/epoch: 2.3240
EPOCH 50. Progress: 100.0%.
Train loss: 0.0009. Train Acc: 95.7675, Test loss: 0.0010. Test Acc: 95.7500. Time/epoch: 2.3105
Run history:
Accuracy/train | ▁▃▄▅▆▆▆▆▇▇▇▇▇▇▇▇▇▇▇███▇█▇███████████████ |
Accuracy/val | ▁▃▄▅▆▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇█▇███████████████ |
Loss/train | █▅▄▃▃▂▂▂▂▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▅▄▃▃▂▂▂▂▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 95.7675 |
Accuracy/val | 95.75 |
Loss/train | 0.00091 |
Loss/val | 0.00097 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_005326-k19vq8g3/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: 41ow5vvs with config:
wandb: batch_size: 128
wandb: epochs: 50
wandb: learning_rate: 0.001
wandb: optimizer: adam
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_005543-41ow5vvs
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0013. Train Acc: 92.6025, Test loss: 0.0014. Test Acc: 92.5400. Time/epoch: 2.4629
EPOCH 10. Progress: 20.0%.
Train loss: 0.0008. Train Acc: 96.0200, Test loss: 0.0010. Test Acc: 95.3400. Time/epoch: 2.4240
EPOCH 20. Progress: 40.0%.
Train loss: 0.0005. Train Acc: 97.5950, Test loss: 0.0009. Test Acc: 96.1700. Time/epoch: 2.3089
EPOCH 30. Progress: 60.0%.
Train loss: 0.0004. Train Acc: 97.9350, Test loss: 0.0010. Test Acc: 96.0000. Time/epoch: 2.2992
EPOCH 40. Progress: 80.0%.
Train loss: 0.0004. Train Acc: 98.0250, Test loss: 0.0011. Test Acc: 95.8700. Time/epoch: 2.4359
EPOCH 50. Progress: 100.0%.
Train loss: 0.0007. Train Acc: 96.9100, Test loss: 0.0016. Test Acc: 94.9100. Time/epoch: 2.4494
Run history:
Accuracy/train | ▁▃▂▃▄▅▆▄▅▆▆▆▆▃▆▆▇▆▅▇▇▇▇▇▇▇▇▇▆▇█▇▇██▆▇█▇▆ |
Accuracy/val | ▁▄▂▄▅▇▇▅▆▇▇█▇▃▇▇▇▆▅▇█▇▇▇▇▇▇█▆▇█▆▆██▅▇▇▆▅ |
Loss/train | █▇▇▇▆▄▄▅▄▃▃▃▃▆▃▃▂▃▄▂▂▂▂▂▂▂▂▂▄▂▁▃▂▁▁▄▂▁▂▄ |
Loss/val | ▆▄▅▄▄▂▁▃▂▁▁▁▁▅▁▂▁▃▄▂▂▂▂▂▂▃▄▂▅▄▂▅▅▄▃▆▄▅▆█ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 96.91 |
Accuracy/val | 94.91 |
Loss/train | 0.0007 |
Loss/val | 0.00165 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_005543-41ow5vvs/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: rma15prl with config:
wandb: batch_size: 128
wandb: epochs: 50
wandb: learning_rate: 0.0001
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_005805-rma15prl
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0021. Train Acc: 88.6875, Test loss: 0.0021. Test Acc: 88.5300. Time/epoch: 2.2395
EPOCH 10. Progress: 20.0%.
Train loss: 0.0010. Train Acc: 94.8100, Test loss: 0.0011. Test Acc: 94.8900. Time/epoch: 2.3652
EPOCH 20. Progress: 40.0%.
Train loss: 0.0006. Train Acc: 97.1975, Test loss: 0.0007. Test Acc: 96.8800. Time/epoch: 2.3607
EPOCH 30. Progress: 60.0%.
Train loss: 0.0005. Train Acc: 97.9025, Test loss: 0.0006. Test Acc: 97.4800. Time/epoch: 2.3467
EPOCH 40. Progress: 80.0%.
Train loss: 0.0004. Train Acc: 97.8625, Test loss: 0.0006. Test Acc: 97.2900. Time/epoch: 2.2306
EPOCH 50. Progress: 100.0%.
Train loss: 0.0015. Train Acc: 92.9100, Test loss: 0.0017. Test Acc: 92.7400. Time/epoch: 2.2342
Run history:
Accuracy/train | ▁▃▅▄▄▆▄▆▅▇▄▇▆▇▇▇▇▇▆▇▇▇█▇█▇▇█▇███▇▇██▆▇▇▄ |
Accuracy/val | ▁▃▅▄▅▇▄▆▆▇▄▇▆▇▇▇▇▇▆▇▇▇█▇█▇██▇▇██▇▇██▆▇▇▄ |
Loss/train | █▆▄▅▅▃▅▃▄▃▅▂▃▂▂▂▂▂▃▂▂▂▁▂▁▂▂▁▂▂▁▁▂▂▁▁▄▂▁▅ |
Loss/val | █▆▄▄▅▃▅▃▃▂▅▂▃▂▂▂▂▂▃▂▂▂▁▂▁▂▂▁▂▂▁▁▂▂▁▁▄▂▂▆ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 92.91 |
Accuracy/val | 92.74 |
Loss/train | 0.00147 |
Loss/val | 0.00167 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_005805-rma15prl/logs
wandb: Agent Starting Run: 9g0xstpx with config:
wandb: batch_size: 64
wandb: epochs: 50
wandb: learning_rate: 0.001
wandb: optimizer: adam
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_010017-9g0xstpx
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0024. Train Acc: 93.3225, Test loss: 0.0025. Test Acc: 93.3200. Time/epoch: 3.3641
EPOCH 10. Progress: 20.0%.
Train loss: 0.0016. Train Acc: 95.8700, Test loss: 0.0019. Test Acc: 95.5100. Time/epoch: 3.1685
EPOCH 20. Progress: 40.0%.
Train loss: 0.0013. Train Acc: 96.5725, Test loss: 0.0018. Test Acc: 96.1900. Time/epoch: 3.1581
EPOCH 30. Progress: 60.0%.
Train loss: 0.0014. Train Acc: 96.4300, Test loss: 0.0021. Test Acc: 95.7500. Time/epoch: 3.3234
EPOCH 40. Progress: 80.0%.
Train loss: 0.0011. Train Acc: 96.9625, Test loss: 0.0018. Test Acc: 96.0000. Time/epoch: 3.3414
EPOCH 50. Progress: 100.0%.
Train loss: 0.0009. Train Acc: 98.0200, Test loss: 0.0022. Test Acc: 96.9100. Time/epoch: 3.3105
Run history:
Accuracy/train | ▂▂▄▂▃▄▄▅▅▅▆▄▅▅▆▅▆▆▆▇▆▇▇▇▆▇█▇▇▇▇▇▇▁▇▅▆█▆█ |
Accuracy/val | ▃▃▅▃▄▄▅▅▆▆▆▅▅▅▆▆▇▇▇▇▆█▇▇▆▇██▇█▇▇▇▁█▆▆█▆█ |
Loss/train | ██▆█▇▆▆▅▄▅▄▆▅▄▄▅▃▃▃▂▃▂▃▂▃▂▁▂▂▂▂▂▂█▂▅▃▁▆▁ |
Loss/val | ▆▆▄▆▅▅▅▃▃▃▂▅▄▃▃▃▂▂▃▂▃▁▁▂▄▂▁▂▂▂▂▁▂█▂▅▅▂▇▅ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.02 |
Accuracy/val | 96.91 |
Loss/train | 0.00087 |
Loss/val | 0.00223 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_010017-9g0xstpx/logs
wandb: Agent Starting Run: hljjsi11 with config:
wandb: batch_size: 128
wandb: epochs: 50
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_010315-hljjsi11
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0017. Train Acc: 90.4575, Test loss: 0.0017. Test Acc: 90.5300. Time/epoch: 2.2875
EPOCH 10. Progress: 20.0%.
Train loss: 0.0008. Train Acc: 95.6600, Test loss: 0.0009. Test Acc: 95.4700. Time/epoch: 2.4250
EPOCH 20. Progress: 40.0%.
Train loss: 0.0006. Train Acc: 96.7150, Test loss: 0.0008. Test Acc: 95.9700. Time/epoch: 2.4188
EPOCH 30. Progress: 60.0%.
Train loss: 0.0003. Train Acc: 98.7750, Test loss: 0.0005. Test Acc: 97.8700. Time/epoch: 2.2719
EPOCH 40. Progress: 80.0%.
Train loss: 0.0003. Train Acc: 98.6125, Test loss: 0.0006. Test Acc: 97.6300. Time/epoch: 2.2986
EPOCH 50. Progress: 100.0%.
Train loss: 0.0002. Train Acc: 98.8025, Test loss: 0.0007. Test Acc: 97.2700. Time/epoch: 2.4233
Run history:
Accuracy/train | ▁▄▄▅▆▆▆▆▅▇▆▇▇▆▇▇▆▇▇▇▇█▇▇█▆▇█▇██▇█▇██▇███ |
Accuracy/val | ▁▄▅▅▆▆▇▇▆▇▇▇▇▆▇▇▆█▇▇▇█▇▇█▆▇█▇██▇█▇██▇▇█▇ |
Loss/train | █▆▅▅▄▄▃▃▄▂▃▂▂▃▃▃▃▂▂▂▂▂▂▂▁▃▂▁▂▁▁▂▁▂▁▁▂▁▁▁ |
Loss/val | █▅▄▄▃▃▂▂▃▂▂▁▁▂▂▂▂▁▁▂▂▁▂▃▁▄▁▁▂▁▁▂▁▂▁▁▂▂▁▂ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.8025 |
Accuracy/val | 97.27 |
Loss/train | 0.00024 |
Loss/val | 0.00066 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_010315-hljjsi11/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: nt3b11pr with config:
wandb: batch_size: 32
wandb: epochs: 10
wandb: learning_rate: 1e-05
wandb: optimizer: sgd
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_010539-nt3b11pr
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0111. Train Acc: 86.6875, Test loss: 0.0114. Test Acc: 86.5300. Time/epoch: 4.6194
EPOCH 10. Progress: 100.0%.
Train loss: 0.0052. Train Acc: 93.3725, Test loss: 0.0054. Test Acc: 93.3400. Time/epoch: 4.7821
Run history:
Accuracy/train | ▁▃▄▅▆▇▇▄▇▇█ |
Accuracy/val | ▁▃▄▅▆▇▇▄█▇█ |
Loss/train | █▅▄▃▂▂▂▄▁▂▁ |
Loss/val | █▅▄▃▂▂▂▄▁▂▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 93.3725 |
Accuracy/val | 93.34 |
Loss/train | 0.00515 |
Loss/val | 0.00545 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_010539-nt3b11pr/logs
wandb: Agent Starting Run: zvbsrho9 with config:
wandb: batch_size: 64
wandb: epochs: 10
wandb: learning_rate: 0.01
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_010644-zvbsrho9
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0242. Train Acc: 36.8250, Test loss: 0.0243. Test Acc: 37.5400. Time/epoch: 3.0688
EPOCH 10. Progress: 100.0%.
Train loss: 0.0244. Train Acc: 36.8250, Test loss: 0.0244. Test Acc: 37.5400. Time/epoch: 3.0125
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | ▂█▂▁▆▄▇▁▇▆▇ |
Loss/val | ▂█▂▁▅▄▇▁▆▆▇ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.02439 |
Loss/val | 0.02443 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_010644-zvbsrho9/logs
wandb: Agent Starting Run: js3qtjb0 with config:
wandb: batch_size: 64
wandb: epochs: 50
wandb: learning_rate: 0.0001
wandb: optimizer: sgd
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_010733-js3qtjb0
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0067. Train Acc: 85.3000, Test loss: 0.0068. Test Acc: 85.8900. Time/epoch: 2.9926
EPOCH 10. Progress: 20.0%.
Train loss: 0.0017. Train Acc: 95.5425, Test loss: 0.0018. Test Acc: 95.5200. Time/epoch: 2.9669
EPOCH 20. Progress: 40.0%.
Train loss: 0.0018. Train Acc: 95.4600, Test loss: 0.0020. Test Acc: 95.2000. Time/epoch: 3.1107
EPOCH 30. Progress: 60.0%.
Train loss: 0.0016. Train Acc: 96.0800, Test loss: 0.0017. Test Acc: 95.7800. Time/epoch: 3.0781
EPOCH 40. Progress: 80.0%.
Train loss: 0.0013. Train Acc: 96.7250, Test loss: 0.0015. Test Acc: 96.4200. Time/epoch: 3.1107
EPOCH 50. Progress: 100.0%.
Train loss: 0.0012. Train Acc: 97.1975, Test loss: 0.0014. Test Acc: 96.9500. Time/epoch: 3.0805
Run history:
Accuracy/train | ▁▅▅▅▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇█▇▇█▇██████████▇████ |
Accuracy/val | ▁▄▅▅▆▆▇▇▇▇▇▇▇▇▇▇▇█▇▇█▇▇█▇▇█████████▇████ |
Loss/train | █▄▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▁▁▂▁▂▁▁▂▁▁▁▁▁▁▁▁▁▁▂▁▁▁▁ |
Loss/val | █▄▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▁▁▂▁▁▁▁▂▁▁▁▁▁▁▁▁▁▁▂▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 97.1975 |
Accuracy/val | 96.95 |
Loss/train | 0.00116 |
Loss/val | 0.00137 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_010733-js3qtjb0/logs
wandb: Agent Starting Run: 2svh3oa2 with config:
wandb: batch_size: 32
wandb: epochs: 10
wandb: learning_rate: 0.0001
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_011021-2svh3oa2
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0060. Train Acc: 92.1275, Test loss: 0.0061. Test Acc: 91.9300. Time/epoch: 4.8761
EPOCH 10. Progress: 100.0%.
Train loss: 0.0027. Train Acc: 96.5675, Test loss: 0.0030. Test Acc: 96.0500. Time/epoch: 4.8464
Run history:
Accuracy/train | ▃▁▅▇▇█▇▇▇██ |
Accuracy/val | ▃▁▅▇▇█▇█▇█▇ |
Loss/train | ▇█▄▂▂▁▂▁▂▁▁ |
Loss/val | ▇█▄▂▂▁▂▁▂▁▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 96.5675 |
Accuracy/val | 96.05 |
Loss/train | 0.00269 |
Loss/val | 0.00296 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_011021-2svh3oa2/logs
wandb: Agent Starting Run: pcr7q62f with config:
wandb: batch_size: 64
wandb: epochs: 50
wandb: learning_rate: 0.0001
wandb: optimizer: rmsprop
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_011127-pcr7q62f
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0039. Train Acc: 88.8100, Test loss: 0.0039. Test Acc: 89.1000. Time/epoch: 3.0240
EPOCH 10. Progress: 20.0%.
Train loss: 0.0017. Train Acc: 95.9075, Test loss: 0.0018. Test Acc: 95.7000. Time/epoch: 3.1668
EPOCH 20. Progress: 40.0%.
Train loss: 0.0014. Train Acc: 96.3800, Test loss: 0.0016. Test Acc: 96.1700. Time/epoch: 3.0218
EPOCH 30. Progress: 60.0%.
Train loss: 0.0011. Train Acc: 97.4375, Test loss: 0.0013. Test Acc: 97.1200. Time/epoch: 2.9951
EPOCH 40. Progress: 80.0%.
Train loss: 0.0010. Train Acc: 97.6875, Test loss: 0.0012. Test Acc: 97.4000. Time/epoch: 3.1581
EPOCH 50. Progress: 100.0%.
Train loss: 0.0009. Train Acc: 97.8525, Test loss: 0.0011. Test Acc: 97.5400. Time/epoch: 3.1793
Run history:
Accuracy/train | ▁▄▅▅▂▅▆▆▆▆▆▇▆▇▇▇▇▇▇█▇▇█▆▇█▇▆█▇██████████ |
Accuracy/val | ▁▄▅▅▁▅▆▆▆▆▆▇▆▇▇▇▇▇▇█▇▇█▆███▆█▇██████████ |
Loss/train | █▅▄▄▇▄▄▃▃▃▃▂▃▂▂▂▂▂▂▁▂▂▁▃▂▁▂▃▁▃▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▅▄▄▇▄▄▃▃▃▃▂▃▂▂▂▂▂▂▁▂▂▁▃▂▁▁▃▁▂▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 97.8525 |
Accuracy/val | 97.54 |
Loss/train | 0.00087 |
Loss/val | 0.0011 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_011127-pcr7q62f/logs
wandb: Agent Starting Run: tq2yb5rq with config:
wandb: batch_size: 32
wandb: epochs: 10
wandb: learning_rate: 0.001
wandb: optimizer: sgd
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_011419-tq2yb5rq
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0269. Train Acc: 62.7025, Test loss: 0.0267. Test Acc: 63.3500. Time/epoch: 4.7851
EPOCH 10. Progress: 100.0%.
Train loss: 0.0141. Train Acc: 79.1350, Test loss: 0.0141. Test Acc: 79.7000. Time/epoch: 4.7103
Run history:
Accuracy/train | ▂▁▂▄▇█▇████ |
Accuracy/val | ▂▁▂▄▇█▇█▇██ |
Loss/train | ██▇▇▃▁▂▁▂▁▁ |
Loss/val | ██▇▇▃▁▂▁▂▁▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 79.135 |
Accuracy/val | 79.7 |
Loss/train | 0.01414 |
Loss/val | 0.01411 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_011419-tq2yb5rq/logs
wandb: Agent Starting Run: xm0g4eyc with config:
wandb: batch_size: 64
wandb: epochs: 20
wandb: learning_rate: 0.01
wandb: optimizer: sgd
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_011526-xm0g4eyc
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 3.0983
EPOCH 10. Progress: 50.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 3.1080
EPOCH 20. Progress: 100.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 2.9523
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | ▂▂▃▃▄▂▃▃▂█▇▇▂▂▁▁▃▅▃▁▃ |
Loss/val | ▅▇▃▄▅▅▃▅▅▇▅█▅▅▁▄▅▆▅▃█ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.02403 |
Loss/val | 0.02408 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_011526-xm0g4eyc/logs
wandb: Agent Starting Run: oibs8tj5 with config:
wandb: batch_size: 64
wandb: epochs: 50
wandb: learning_rate: 0.01
wandb: optimizer: sgd
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_011642-oibs8tj5
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0240. Test Acc: 37.5400. Time/epoch: 3.1351
EPOCH 10. Progress: 20.0%.
Train loss: 0.0241. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 3.1293
EPOCH 20. Progress: 40.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 2.9743
EPOCH 30. Progress: 60.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 2.9681
EPOCH 40. Progress: 80.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 3.0801
EPOCH 50. Progress: 100.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 3.1191
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁█▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁█▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | ██████████████████████████▁█████████████ |
Loss/val | ██████████████████████████▁█████████████ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.02402 |
Loss/val | 0.02406 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_011642-oibs8tj5/logs
wandb: Agent Starting Run: td3idvxx with config:
wandb: batch_size: 128
wandb: epochs: 20
wandb: learning_rate: 1e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_011929-td3idvxx
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0060. Train Acc: 80.2150, Test loss: 0.0060. Test Acc: 80.0600. Time/epoch: 2.3139
EPOCH 10. Progress: 50.0%.
Train loss: 0.0013. Train Acc: 93.2350, Test loss: 0.0014. Test Acc: 93.0400. Time/epoch: 2.4386
EPOCH 20. Progress: 100.0%.
Train loss: 0.0011. Train Acc: 93.9750, Test loss: 0.0012. Test Acc: 94.0900. Time/epoch: 2.4276
Run history:
Accuracy/train | ▁▅▆▆▇▇▇▇▇▇███████████ |
Accuracy/val | ▁▅▆▆▇▇▇▇▇█▇██████████ |
Loss/train | █▄▃▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▄▃▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 93.975 |
Accuracy/val | 94.09 |
Loss/train | 0.00114 |
Loss/val | 0.0012 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_011929-td3idvxx/logs
wandb: Agent Starting Run: cet2jps7 with config:
wandb: batch_size: 32
wandb: epochs: 50
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_012032-cet2jps7
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0066. Train Acc: 91.0700, Test loss: 0.0067. Test Acc: 91.1100. Time/epoch: 5.0446
EPOCH 10. Progress: 20.0%.
Train loss: 0.0029. Train Acc: 96.4875, Test loss: 0.0034. Test Acc: 96.0800. Time/epoch: 5.1598
EPOCH 20. Progress: 40.0%.
Train loss: 0.0022. Train Acc: 97.2775, Test loss: 0.0034. Test Acc: 96.4800. Time/epoch: 5.1723
EPOCH 30. Progress: 60.0%.
Train loss: 0.0009. Train Acc: 99.0950, Test loss: 0.0022. Test Acc: 97.9000. Time/epoch: 5.1286
EPOCH 40. Progress: 80.0%.
Train loss: 0.0011. Train Acc: 98.7550, Test loss: 0.0031. Test Acc: 97.5600. Time/epoch: 5.1539
EPOCH 50. Progress: 100.0%.
Train loss: 0.0007. Train Acc: 99.1825, Test loss: 0.0029. Test Acc: 97.8000. Time/epoch: 5.0007
Run history:
Accuracy/train | ▁▄▃▄▄▄▅▆▆▆▆▇▆▄▇▅▆▇▅▇▇▆▇▇█▇█▇▇▇█▇▇█▇▆▇███ |
Accuracy/val | ▁▄▄▄▅▄▆▇▆▆▇▇▇▄▇▅▆▇▅▇▇▆▇▇█▇█▇▇▇█▇▇█▇▆▇███ |
Loss/train | █▅▅▅▅▅▄▃▄▃▃▃▃▅▃▄▃▂▄▂▂▃▃▃▁▂▁▂▂▂▁▂▃▁▃▃▂▁▁▁ |
Loss/val | █▄▅▅▄▅▃▁▃▂▂▂▂▅▂▅▃▂▅▁▂▃▃▃▁▂▁▂▂▂▁▂▃▁▄▅▂▁▂▂ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 99.1825 |
Accuracy/val | 97.8 |
Loss/train | 0.00071 |
Loss/val | 0.00285 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_012032-cet2jps7/logs
wandb: Agent Starting Run: wgxc0r89 with config:
wandb: batch_size: 64
wandb: epochs: 50
wandb: learning_rate: 1e-05
wandb: optimizer: sgd
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_012506-wgxc0r89
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0057. Train Acc: 88.1100, Test loss: 0.0058. Test Acc: 87.8200. Time/epoch: 3.1096
EPOCH 10. Progress: 20.0%.
Train loss: 0.0025. Train Acc: 93.7300, Test loss: 0.0026. Test Acc: 93.8200. Time/epoch: 2.9596
EPOCH 20. Progress: 40.0%.
Train loss: 0.0022. Train Acc: 94.6750, Test loss: 0.0023. Test Acc: 94.5100. Time/epoch: 2.9497
EPOCH 30. Progress: 60.0%.
Train loss: 0.0020. Train Acc: 95.2350, Test loss: 0.0021. Test Acc: 95.1200. Time/epoch: 3.0862
EPOCH 40. Progress: 80.0%.
Train loss: 0.0019. Train Acc: 95.4075, Test loss: 0.0020. Test Acc: 95.2700. Time/epoch: 3.0906
EPOCH 50. Progress: 100.0%.
Train loss: 0.0018. Train Acc: 95.4550, Test loss: 0.0019. Test Acc: 95.4600. Time/epoch: 2.9645
Run history:
Accuracy/train | ▁▃▄▅▆▆▆▆▆▆▆▇▇▇▇▇▇▇▇▇▇▇████▇██████▇▇█████ |
Accuracy/val | ▁▃▄▅▆▆▆▆▆▆▆▇▇▇▇▇▇▇▇▇▇▇▇██▇▇██████▇▇█████ |
Loss/train | █▅▄▃▃▃▃▂▂▂▂▂▂▂▂▂▂▂▁▂▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▅▄▃▃▃▃▂▂▂▂▂▂▂▂▂▂▂▁▂▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 95.455 |
Accuracy/val | 95.46 |
Loss/train | 0.0018 |
Loss/val | 0.00191 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_012506-wgxc0r89/logs
wandb: Agent Starting Run: wpego9ua with config:
wandb: batch_size: 64
wandb: epochs: 10
wandb: learning_rate: 0.01
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_012754-wpego9ua
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0150. Train Acc: 58.0100, Test loss: 0.0149. Test Acc: 58.5900. Time/epoch: 3.1601
EPOCH 10. Progress: 100.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 3.0320
Run history:
Accuracy/train | █▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | █▁▁▁▁▁▁▁▁▁▁ |
Loss/train | ▁██████████ |
Loss/val | ▁██████████ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.02403 |
Loss/val | 0.02405 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_012754-wpego9ua/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: ntymp54i with config:
wandb: batch_size: 128
wandb: epochs: 50
wandb: learning_rate: 1e-05
wandb: optimizer: adam
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_012850-ntymp54i
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0062. Train Acc: 75.4750, Test loss: 0.0063. Test Acc: 75.7900. Time/epoch: 2.4605
EPOCH 10. Progress: 20.0%.
Train loss: 0.0018. Train Acc: 89.3325, Test loss: 0.0019. Test Acc: 89.1500. Time/epoch: 2.4217
EPOCH 20. Progress: 40.0%.
Train loss: 0.0014. Train Acc: 92.4650, Test loss: 0.0015. Test Acc: 92.3500. Time/epoch: 2.2873
EPOCH 30. Progress: 60.0%.
Train loss: 0.0011. Train Acc: 94.1775, Test loss: 0.0012. Test Acc: 94.1200. Time/epoch: 2.2804
EPOCH 40. Progress: 80.0%.
Train loss: 0.0010. Train Acc: 95.0900, Test loss: 0.0010. Test Acc: 95.1300. Time/epoch: 2.4266
EPOCH 50. Progress: 100.0%.
Train loss: 0.0009. Train Acc: 95.5025, Test loss: 0.0010. Test Acc: 95.5600. Time/epoch: 2.4387
Run history:
Accuracy/train | ▁▃▅▅▅▅▆▆▆▆▆▆▆▇▇▇▇▇▇▇▇▇▇█████████████████ |
Accuracy/val | ▁▃▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇▇▇▇▇▇▇███████████████ |
Loss/train | █▅▄▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▅▄▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 95.5025 |
Accuracy/val | 95.56 |
Loss/train | 0.0009 |
Loss/val | 0.00096 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_012850-ntymp54i/logs
wandb: Agent Starting Run: 8e8t06bq with config:
wandb: batch_size: 64
wandb: epochs: 50
wandb: learning_rate: 0.001
wandb: optimizer: rmsprop
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_013103-8e8t06bq
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0130. Train Acc: 72.5800, Test loss: 0.0128. Test Acc: 72.8100. Time/epoch: 3.1799
EPOCH 10. Progress: 20.0%.
Train loss: 0.0030. Train Acc: 92.1975, Test loss: 0.0032. Test Acc: 91.9100. Time/epoch: 3.1378
EPOCH 20. Progress: 40.0%.
Train loss: 0.0027. Train Acc: 93.4900, Test loss: 0.0028. Test Acc: 93.1500. Time/epoch: 3.1438
EPOCH 30. Progress: 60.0%.
Train loss: 0.0021. Train Acc: 95.3625, Test loss: 0.0023. Test Acc: 95.0000. Time/epoch: 3.0164
EPOCH 40. Progress: 80.0%.
Train loss: 0.0020. Train Acc: 95.2875, Test loss: 0.0022. Test Acc: 94.8700. Time/epoch: 3.1641
EPOCH 50. Progress: 100.0%.
Train loss: 0.0020. Train Acc: 95.5525, Test loss: 0.0022. Test Acc: 95.2500. Time/epoch: 3.1630
Run history:
Accuracy/train | ▁▃▆▇▂▄▅▆▇▇▇▇▇▇█▇▇▇██▇████████████▇██████ |
Accuracy/val | ▁▃▇▇▂▄▅▆▇▇▇▇▇▇█▇▇▇██▇████████████▇██████ |
Loss/train | █▄▃▂▅▃▃▂▂▂▁▁▂▂▁▁▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▄▃▂▅▄▃▂▂▂▁▁▂▂▁▁▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▂▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 95.5525 |
Accuracy/val | 95.25 |
Loss/train | 0.00197 |
Loss/val | 0.00217 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_013103-8e8t06bq/logs
wandb: Agent Starting Run: rvcbs4dg with config:
wandb: batch_size: 128
wandb: epochs: 50
wandb: learning_rate: 0.0003
wandb: optimizer: sgd
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_013355-rvcbs4dg
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0038. Train Acc: 82.9650, Test loss: 0.0038. Test Acc: 82.7400. Time/epoch: 2.1988
EPOCH 10. Progress: 20.0%.
Train loss: 0.0013. Train Acc: 93.0050, Test loss: 0.0013. Test Acc: 93.0800. Time/epoch: 2.3553
EPOCH 20. Progress: 40.0%.
Train loss: 0.0010. Train Acc: 95.3475, Test loss: 0.0010. Test Acc: 95.1500. Time/epoch: 2.3193
EPOCH 30. Progress: 60.0%.
Train loss: 0.0010. Train Acc: 94.9400, Test loss: 0.0010. Test Acc: 94.9600. Time/epoch: 2.3394
EPOCH 40. Progress: 80.0%.
Train loss: 0.0009. Train Acc: 95.6050, Test loss: 0.0009. Test Acc: 95.5400. Time/epoch: 2.1788
EPOCH 50. Progress: 100.0%.
Train loss: 0.0010. Train Acc: 95.0950, Test loss: 0.0010. Test Acc: 95.0300. Time/epoch: 2.1963
Run history:
Accuracy/train | ▁▇▇▇▇▇▇▆▇██▅███▇██▇▇███████▇▇█▇▇██▇█████ |
Accuracy/val | ▁▇▇▇█▇▇▆▇██▅▇█████▇▇█████▇█▇▇█▇▇████████ |
Loss/train | █▂▂▂▁▁▁▂▂▁▁▃▁▁▁▁▁▁▂▂▁▁▁▁▁▁▁▁▂▁▁▂▁▁▁▁▁▁▁▁ |
Loss/val | █▂▂▂▁▁▁▃▂▁▁▃▁▁▁▁▁▁▂▂▁▁▁▁▁▁▁▁▂▁▁▂▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 95.095 |
Accuracy/val | 95.03 |
Loss/train | 0.00097 |
Loss/val | 0.001 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_013355-rvcbs4dg/logs
wandb: Agent Starting Run: ykrhvl2b with config:
wandb: batch_size: 128
wandb: epochs: 20
wandb: learning_rate: 0.001
wandb: optimizer: adam
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_013602-ykrhvl2b
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0014. Train Acc: 92.3400, Test loss: 0.0014. Test Acc: 92.4800. Time/epoch: 2.4528
EPOCH 10. Progress: 50.0%.
Train loss: 0.0008. Train Acc: 95.9200, Test loss: 0.0010. Test Acc: 95.4400. Time/epoch: 2.4371
EPOCH 20. Progress: 100.0%.
Train loss: 0.0005. Train Acc: 97.6450, Test loss: 0.0008. Test Acc: 96.5700. Time/epoch: 2.2827
Run history:
Accuracy/train | ▂▃▂▄▅▁▆▆▆▅▆▆▆▅▆▇▇▅▇██ |
Accuracy/val | ▂▃▂▄▆▁▇▆▆▅▆▆▆▆▆▇▇▅▇██ |
Loss/train | ▇▇▇▅▅█▃▃▃▅▄▃▄▄▄▂▂▄▃▁▁ |
Loss/val | ▇▆▇▄▄█▂▂▂▄▃▄▃▄▄▂▂▄▃▁▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 97.645 |
Accuracy/val | 96.57 |
Loss/train | 0.00049 |
Loss/val | 0.00079 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_013602-ykrhvl2b/logs
wandb: Agent Starting Run: ru1sh0ei with config:
wandb: batch_size: 64
wandb: epochs: 50
wandb: learning_rate: 0.001
wandb: optimizer: sgd
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_013704-ru1sh0ei
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0076. Train Acc: 77.3225, Test loss: 0.0075. Test Acc: 78.0900. Time/epoch: 3.1420
EPOCH 10. Progress: 20.0%.
Train loss: 0.0026. Train Acc: 93.9200, Test loss: 0.0029. Test Acc: 93.4000. Time/epoch: 3.1229
EPOCH 20. Progress: 40.0%.
Train loss: 0.0020. Train Acc: 95.1150, Test loss: 0.0024. Test Acc: 94.2000. Time/epoch: 2.9649
EPOCH 30. Progress: 60.0%.
Train loss: 0.0017. Train Acc: 96.0825, Test loss: 0.0023. Test Acc: 95.0600. Time/epoch: 2.9383
EPOCH 40. Progress: 80.0%.
Train loss: 0.0017. Train Acc: 96.3525, Test loss: 0.0022. Test Acc: 95.1500. Time/epoch: 3.1102
EPOCH 50. Progress: 100.0%.
Train loss: 0.0016. Train Acc: 95.8775, Test loss: 0.0022. Test Acc: 94.9000. Time/epoch: 3.0799
Run history:
Accuracy/train | ▁▅▅▆▇▇▇▇▇▇▇▇▇▇█▇▇█▇████▇████▇██████▇████ |
Accuracy/val | ▁▅▅▆▇▇▇▇▇▇▇▇▇██▇▇█▇████▇████▇██████▇████ |
Loss/train | █▄▄▃▃▂▂▂▃▂▂▂▂▂▂▂▂▂▂▂▁▂▁▂▂▁▂▁▂▁▁▁▁▁▁▂▁▁▁▁ |
Loss/val | █▄▄▃▂▂▂▂▂▂▂▂▂▂▁▂▂▁▂▁▁▂▁▂▂▁▁▁▂▁▁▁▁▁▁▃▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 95.8775 |
Accuracy/val | 94.9 |
Loss/train | 0.00158 |
Loss/val | 0.00222 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_013704-ru1sh0ei/logs
wandb: Agent Starting Run: pxhxw92y with config:
wandb: batch_size: 64
wandb: epochs: 10
wandb: learning_rate: 3e-05
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_013951-pxhxw92y
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0042. Train Acc: 87.8425, Test loss: 0.0043. Test Acc: 87.7200. Time/epoch: 3.0504
EPOCH 10. Progress: 100.0%.
Train loss: 0.0023. Train Acc: 94.3600, Test loss: 0.0024. Test Acc: 94.1600. Time/epoch: 3.1346
Run history:
Accuracy/train | ▁▄▆▆▆▅▆▆█▇█ |
Accuracy/val | ▁▄▆▅▆▆▆▆█▇█ |
Loss/train | █▅▄▄▃▄▃▃▂▂▁ |
Loss/val | █▅▄▄▃▄▃▃▁▂▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 94.36 |
Accuracy/val | 94.16 |
Loss/train | 0.00226 |
Loss/val | 0.00243 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_013951-pxhxw92y/logs
wandb: Agent Starting Run: um2tdmbb with config:
wandb: batch_size: 64
wandb: epochs: 20
wandb: learning_rate: 0.0001
wandb: optimizer: sgd
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_014042-um2tdmbb
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0174. Train Acc: 60.3375, Test loss: 0.0172. Test Acc: 60.8500. Time/epoch: 3.0297
EPOCH 10. Progress: 50.0%.
Train loss: 0.0046. Train Acc: 87.9275, Test loss: 0.0048. Test Acc: 87.9800. Time/epoch: 3.1036
EPOCH 20. Progress: 100.0%.
Train loss: 0.0024. Train Acc: 93.5025, Test loss: 0.0025. Test Acc: 93.5100. Time/epoch: 3.1106
Run history:
Accuracy/train | ▁▂▂▂▂▂▂▂▂▅▇▇█████████ |
Accuracy/val | ▁▂▂▂▂▂▂▂▂▅▇▇█████████ |
Loss/train | █▇▇▇▇▆▆▆▆▃▂▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▇▇▇▇▆▆▆▆▃▂▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 93.5025 |
Accuracy/val | 93.51 |
Loss/train | 0.00244 |
Loss/val | 0.00249 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_014042-um2tdmbb/logs
wandb: Agent Starting Run: hcn68694 with config:
wandb: batch_size: 32
wandb: epochs: 50
wandb: learning_rate: 0.0001
wandb: optimizer: sgd
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_014159-hcn68694
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0060. Train Acc: 91.3650, Test loss: 0.0064. Test Acc: 91.2400. Time/epoch: 4.5928
EPOCH 10. Progress: 20.0%.
Train loss: 0.0039. Train Acc: 95.1425, Test loss: 0.0040. Test Acc: 95.1500. Time/epoch: 4.7674
EPOCH 20. Progress: 40.0%.
Train loss: 0.0026. Train Acc: 96.7850, Test loss: 0.0028. Test Acc: 96.5700. Time/epoch: 4.7427
EPOCH 30. Progress: 60.0%.
Train loss: 0.0034. Train Acc: 95.6125, Test loss: 0.0036. Test Acc: 95.4800. Time/epoch: 4.5831
EPOCH 40. Progress: 80.0%.
Train loss: 0.0026. Train Acc: 96.7900, Test loss: 0.0031. Test Acc: 96.3800. Time/epoch: 4.5847
EPOCH 50. Progress: 100.0%.
Train loss: 0.0019. Train Acc: 97.6125, Test loss: 0.0024. Test Acc: 97.1300. Time/epoch: 4.5635
Run history:
Accuracy/train | ▁▁▃▅▅▆▅▅▅▆▇▇▆▆▆▇▇▇▇▇▇▇▆▇▆█▇█▇▆▇██▇▇█▇█▇█ |
Accuracy/val | ▁▁▃▅▆▆▅▅▆▆▇▇▇▇▇▇▇▇▇▇█▇▆▇▆███▇▇▇███▇█▇█▇█ |
Loss/train | ▇█▆▄▄▃▄▄▄▃▃▃▃▃▃▂▂▂▂▂▂▂▃▂▃▂▂▁▂▃▂▁▁▁▂▁▂▁▂▁ |
Loss/val | ██▆▄▄▃▄▄▄▃▂▂▃▃▂▂▂▂▂▂▂▁▃▂▃▁▁▁▂▃▂▁▁▁▂▁▂▁▂▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 97.6125 |
Accuracy/val | 97.13 |
Loss/train | 0.00193 |
Loss/val | 0.00244 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_014159-hcn68694/logs
wandb: Agent Starting Run: 1j8th984 with config:
wandb: batch_size: 128
wandb: epochs: 20
wandb: learning_rate: 0.0001
wandb: optimizer: adam
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_014612-1j8th984
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0014. Train Acc: 92.4975, Test loss: 0.0014. Test Acc: 92.5700. Time/epoch: 2.4395
EPOCH 10. Progress: 50.0%.
Train loss: 0.0006. Train Acc: 97.0575, Test loss: 0.0007. Test Acc: 96.7800. Time/epoch: 2.2884
EPOCH 20. Progress: 100.0%.
Train loss: 0.0005. Train Acc: 97.5575, Test loss: 0.0006. Test Acc: 97.2100. Time/epoch: 2.4340
Run history:
Accuracy/train | ▁▄▄▅▅▆▆▅▇▆▇▇█▇█▇▇█▇▇█ |
Accuracy/val | ▁▄▅▅▄▆▆▅▇▆▇▇████▇█▇▇█ |
Loss/train | █▆▅▄▅▃▃▄▂▃▂▂▁▁▁▂▂▁▂▂▁ |
Loss/val | █▆▅▄▅▃▃▄▂▂▂▂▁▁▁▂▂▁▂▂▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 97.5575 |
Accuracy/val | 97.21 |
Loss/train | 0.00052 |
Loss/val | 0.0006 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_014612-1j8th984/logs
wandb: Agent Starting Run: qhzg268e with config:
wandb: batch_size: 64
wandb: epochs: 50
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_014718-qhzg268e
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0026. Train Acc: 93.4925, Test loss: 0.0026. Test Acc: 93.5700. Time/epoch: 3.1672
EPOCH 10. Progress: 20.0%.
Train loss: 0.0016. Train Acc: 96.0975, Test loss: 0.0018. Test Acc: 95.4600. Time/epoch: 3.1687
EPOCH 20. Progress: 40.0%.
Train loss: 0.0010. Train Acc: 97.6525, Test loss: 0.0014. Test Acc: 97.0900. Time/epoch: 3.3189
EPOCH 30. Progress: 60.0%.
Train loss: 0.0007. Train Acc: 98.3975, Test loss: 0.0013. Test Acc: 97.3400. Time/epoch: 3.3105
EPOCH 40. Progress: 80.0%.
Train loss: 0.0006. Train Acc: 98.4825, Test loss: 0.0015. Test Acc: 97.0300. Time/epoch: 3.3044
EPOCH 50. Progress: 100.0%.
Train loss: 0.0004. Train Acc: 99.1600, Test loss: 0.0013. Test Acc: 97.5900. Time/epoch: 3.3094
Run history:
Accuracy/train | ▁▂▃▄▄▅▅▅▄▆▆▅▆▆▆▆▆▄▆▆▇▇▇▆▇█▇▇▇██▇▇████▇██ |
Accuracy/val | ▁▂▄▄▄▆▆▆▄▇▇▅▇▇▇▇▇▅▅▆▇██▇▇█▇█▆██▆▇█▇██▇██ |
Loss/train | █▇▅▅▅▄▄▄▅▃▃▄▃▃▃▃▃▄▃▃▂▂▂▂▂▂▂▂▂▁▁▂▂▁▁▁▁▁▁▁ |
Loss/val | █▆▄▄▅▃▃▂▄▂▂▄▂▂▂▂▂▄▄▂▁▁▁▂▂▁▂▂▃▂▂▄▄▂▂▂▂▃▃▂ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 99.16 |
Accuracy/val | 97.59 |
Loss/train | 0.00038 |
Loss/val | 0.00129 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_014718-qhzg268e/logs
wandb: Agent Starting Run: a1co11pt with config:
wandb: batch_size: 128
wandb: epochs: 50
wandb: learning_rate: 3e-05
wandb: optimizer: adam
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_015021-a1co11pt
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0025. Train Acc: 87.2775, Test loss: 0.0025. Test Acc: 87.2400. Time/epoch: 2.4782
EPOCH 10. Progress: 20.0%.
Train loss: 0.0011. Train Acc: 94.2025, Test loss: 0.0012. Test Acc: 93.7700. Time/epoch: 2.4222
EPOCH 20. Progress: 40.0%.
Train loss: 0.0010. Train Acc: 94.8650, Test loss: 0.0011. Test Acc: 94.3300. Time/epoch: 2.4377
EPOCH 30. Progress: 60.0%.
Train loss: 0.0008. Train Acc: 96.0625, Test loss: 0.0009. Test Acc: 95.4800. Time/epoch: 2.3026
EPOCH 40. Progress: 80.0%.
Train loss: 0.0007. Train Acc: 96.4650, Test loss: 0.0008. Test Acc: 95.9900. Time/epoch: 2.4351
EPOCH 50. Progress: 100.0%.
Train loss: 0.0006. Train Acc: 97.0775, Test loss: 0.0008. Test Acc: 96.6400. Time/epoch: 2.4276
Run history:
Accuracy/train | ▁▃▃▄▅▅▅▅▆▆▆▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇██████▇███████ |
Accuracy/val | ▁▃▄▄▅▅▅▅▆▆▆▇▆▇▇▇▆▇▇▇▇▇▇▇▇▇▇████▇▇███████ |
Loss/train | █▆▅▅▄▃▃▃▃▃▃▂▃▂▂▂▂▂▂▂▂▂▂▂▂▂▂▁▁▁▁▁▂▁▁▁▁▁▁▁ |
Loss/val | █▆▅▅▃▃▃▃▃▃▃▂▃▂▂▂▃▂▂▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 97.0775 |
Accuracy/val | 96.64 |
Loss/train | 0.00062 |
Loss/val | 0.00075 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_015021-a1co11pt/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: 8lbqnae6 with config:
wandb: batch_size: 32
wandb: epochs: 10
wandb: learning_rate: 0.01
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_015243-8lbqnae6
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0481. Train Acc: 36.8250, Test loss: 0.0481. Test Acc: 37.5400. Time/epoch: 4.9159
EPOCH 10. Progress: 100.0%.
Train loss: 0.0481. Train Acc: 36.8250, Test loss: 0.0480. Test Acc: 37.5400. Time/epoch: 4.9081
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | ▇█▄▂▁▅▄▄█▂▂ |
Loss/val | ▇█▃▁▁▂▃▄▅▃▂ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.04806 |
Loss/val | 0.04796 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_015243-8lbqnae6/logs
wandb: Agent Starting Run: 8lxesosr with config:
wandb: batch_size: 32
wandb: epochs: 20
wandb: learning_rate: 0.001
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_015350-8lxesosr
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.1360. Train Acc: 45.6450, Test loss: 0.1391. Test Acc: 45.3500. Time/epoch: 4.7017
EPOCH 10. Progress: 50.0%.
Train loss: 0.0040. Train Acc: 95.3500, Test loss: 0.0046. Test Acc: 94.9800. Time/epoch: 4.6806
EPOCH 20. Progress: 100.0%.
Train loss: 0.0043. Train Acc: 95.4000, Test loss: 0.0054. Test Acc: 94.7700. Time/epoch: 4.8745
Run history:
Accuracy/train | ▁▇▆██▇▇█████████▇████ |
Accuracy/val | ▁▇▆██▇██████████▇████ |
Loss/train | █▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 95.4 |
Accuracy/val | 94.77 |
Loss/train | 0.00427 |
Loss/val | 0.00538 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_015350-8lxesosr/logs
wandb: Agent Starting Run: 24buqjcp with config:
wandb: batch_size: 64
wandb: epochs: 20
wandb: learning_rate: 3e-05
wandb: optimizer: adam
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_015551-24buqjcp
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0036. Train Acc: 89.9200, Test loss: 0.0037. Test Acc: 89.8600. Time/epoch: 3.1996
EPOCH 10. Progress: 50.0%.
Train loss: 0.0018. Train Acc: 95.2600, Test loss: 0.0019. Test Acc: 95.3200. Time/epoch: 3.3460
EPOCH 20. Progress: 100.0%.
Train loss: 0.0016. Train Acc: 96.1525, Test loss: 0.0017. Test Acc: 95.7300. Time/epoch: 3.3045
Run history:
Accuracy/train | ▁▃▄▅▅▆▆▇▇▆▇▇██▇▇█████ |
Accuracy/val | ▁▄▄▅▆▆▇▇▇▇▇███▇▇█████ |
Loss/train | █▆▅▄▃▃▃▂▂▂▂▂▁▁▂▂▁▁▁▁▁ |
Loss/val | █▆▅▄▃▃▂▂▂▂▂▂▁▁▂▂▁▁▁▁▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 96.1525 |
Accuracy/val | 95.73 |
Loss/train | 0.00157 |
Loss/val | 0.00169 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_015551-24buqjcp/logs
wandb: Agent Starting Run: t7ub61uh with config:
wandb: batch_size: 32
wandb: epochs: 20
wandb: learning_rate: 3e-05
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_015712-t7ub61uh
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0074. Train Acc: 89.7000, Test loss: 0.0076. Test Acc: 89.8600. Time/epoch: 4.9325
EPOCH 10. Progress: 50.0%.
Train loss: 0.0042. Train Acc: 94.5575, Test loss: 0.0043. Test Acc: 94.6700. Time/epoch: 4.8575
EPOCH 20. Progress: 100.0%.
Train loss: 0.0039. Train Acc: 94.9975, Test loss: 0.0040. Test Acc: 95.0800. Time/epoch: 4.8236
Run history:
Accuracy/train | ▁▄▄▆▆▆▆▇▆▆▇▇▆▆█▇█▇██▇ |
Accuracy/val | ▁▄▄▆▆▆▆▇▆▆▇▇▆▆█▇█▇█▇█ |
Loss/train | █▅▅▃▃▃▃▂▃▃▂▂▃▃▁▂▁▁▁▂▁ |
Loss/val | █▅▅▃▃▃▃▂▃▃▂▂▃▃▁▂▁▁▁▂▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 94.9975 |
Accuracy/val | 95.08 |
Loss/train | 0.00388 |
Loss/val | 0.00399 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_015712-t7ub61uh/logs
wandb: Agent Starting Run: dlyi88g3 with config:
wandb: batch_size: 128
wandb: epochs: 10
wandb: learning_rate: 0.0001
wandb: optimizer: sgd
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_015909-dlyi88g3
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0025. Train Acc: 87.0400, Test loss: 0.0025. Test Acc: 86.9100. Time/epoch: 2.3753
EPOCH 10. Progress: 100.0%.
Train loss: 0.0011. Train Acc: 93.8025, Test loss: 0.0011. Test Acc: 93.9700. Time/epoch: 2.3173
Run history:
Accuracy/train | ▁▃▁▄▇▅▆█▇█▇ |
Accuracy/val | ▁▃▁▅▇▆▆█▇█▇ |
Loss/train | █▅▆▄▂▃▃▁▂▁▁ |
Loss/val | █▅▆▄▂▃▃▁▂▁▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 93.8025 |
Accuracy/val | 93.97 |
Loss/train | 0.00112 |
Loss/val | 0.00113 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_015909-dlyi88g3/logs
wandb: Agent Starting Run: ak4nng79 with config:
wandb: batch_size: 32
wandb: epochs: 50
wandb: learning_rate: 1e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_015949-ak4nng79
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0119. Train Acc: 82.9050, Test loss: 0.0118. Test Acc: 83.2500. Time/epoch: 5.0588
EPOCH 10. Progress: 20.0%.
Train loss: 0.0042. Train Acc: 94.6050, Test loss: 0.0044. Test Acc: 94.5800. Time/epoch: 5.1459
EPOCH 20. Progress: 40.0%.
Train loss: 0.0034. Train Acc: 95.9725, Test loss: 0.0035. Test Acc: 95.8900. Time/epoch: 5.1579
EPOCH 30. Progress: 60.0%.
Train loss: 0.0031. Train Acc: 96.1425, Test loss: 0.0034. Test Acc: 95.9500. Time/epoch: 5.0730
EPOCH 40. Progress: 80.0%.
Train loss: 0.0027. Train Acc: 96.7825, Test loss: 0.0030. Test Acc: 96.4700. Time/epoch: 4.9959
EPOCH 50. Progress: 100.0%.
Train loss: 0.0025. Train Acc: 97.0150, Test loss: 0.0028. Test Acc: 96.8200. Time/epoch: 5.0264
Run history:
Accuracy/train | ▁▄▅▆▆▆▆▇▇▇▇▇▇▇▇▇▇▇▇█████▇█▇█████████████ |
Accuracy/val | ▁▄▅▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇█████▇███████████████ |
Loss/train | █▅▄▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▁▁▁▁▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▅▄▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 97.015 |
Accuracy/val | 96.82 |
Loss/train | 0.00253 |
Loss/val | 0.0028 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_015949-ak4nng79/logs
wandb: Agent Starting Run: 9605oqnw with config:
wandb: batch_size: 128
wandb: epochs: 10
wandb: learning_rate: 0.01
wandb: optimizer: sgd
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_020424-9605oqnw
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0122. Train Acc: 36.8250, Test loss: 0.0123. Test Acc: 37.5400. Time/epoch: 2.2035
EPOCH 10. Progress: 100.0%.
Train loss: 0.0122. Train Acc: 36.8250, Test loss: 0.0122. Test Acc: 37.5400. Time/epoch: 2.1998
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | █▄▂▁▁▁▅▃▃▃▃ |
Loss/val | █▄▁▁▃▂▇▂▂▃▃ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.01216 |
Loss/val | 0.01224 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_020424-9605oqnw/logs
wandb: Agent Starting Run: 32wrwz33 with config:
wandb: batch_size: 64
wandb: epochs: 50
wandb: learning_rate: 0.01
wandb: optimizer: adam
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_020501-32wrwz33
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0241. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 3.2372
EPOCH 10. Progress: 20.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0240. Test Acc: 37.5400. Time/epoch: 3.1972
EPOCH 20. Progress: 40.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 3.1618
EPOCH 30. Progress: 60.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0240. Test Acc: 37.5400. Time/epoch: 3.3073
EPOCH 40. Progress: 80.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0240. Test Acc: 37.5400. Time/epoch: 3.3188
EPOCH 50. Progress: 100.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 3.3351
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | █▂▂▅▃▁▂▂▁▂▃▂▂▂▂▁▂▂▃▁▂▃▂▁▂▂▂▃▁▁▁▂▁▃▂▂▂▁▁▂ |
Loss/val | █▂▂▅▄▃▂▃▂▃▃▃▅▃▃▂▃▃▂▃▃▆▃▂▂▃▃▃▂▂▁▃▃▃▃▅▁▃▁▃ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.02403 |
Loss/val | 0.02406 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_020501-32wrwz33/logs
wandb: Agent Starting Run: ould8q90 with config:
wandb: batch_size: 128
wandb: epochs: 50
wandb: learning_rate: 1e-05
wandb: optimizer: adam
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_020804-ould8q90
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0051. Train Acc: 77.3275, Test loss: 0.0052. Test Acc: 77.4300. Time/epoch: 2.4906
EPOCH 10. Progress: 20.0%.
Train loss: 0.0012. Train Acc: 94.1025, Test loss: 0.0012. Test Acc: 94.1800. Time/epoch: 2.4152
EPOCH 20. Progress: 40.0%.
Train loss: 0.0010. Train Acc: 94.8325, Test loss: 0.0010. Test Acc: 95.0300. Time/epoch: 2.2949
EPOCH 30. Progress: 60.0%.
Train loss: 0.0009. Train Acc: 95.5700, Test loss: 0.0009. Test Acc: 95.6500. Time/epoch: 2.2816
EPOCH 40. Progress: 80.0%.
Train loss: 0.0008. Train Acc: 95.9950, Test loss: 0.0008. Test Acc: 95.9600. Time/epoch: 2.4423
EPOCH 50. Progress: 100.0%.
Train loss: 0.0007. Train Acc: 96.2450, Test loss: 0.0008. Test Acc: 96.1800. Time/epoch: 2.4232
Run history:
Accuracy/train | ▁▄▅▆▇▇▇▇▇▇▇▇▇▇▇▇▇███████████████████████ |
Accuracy/val | ▁▄▄▆▇▇▇▇▇▇▇▇▇▇▇▇████████████████████████ |
Loss/train | █▄▄▃▂▂▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▄▄▃▂▂▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 96.245 |
Accuracy/val | 96.18 |
Loss/train | 0.00073 |
Loss/val | 0.00079 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_020804-ould8q90/logs
wandb: Agent Starting Run: 7fx470wl with config:
wandb: batch_size: 32
wandb: epochs: 20
wandb: learning_rate: 0.01
wandb: optimizer: sgd
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_021021-7fx470wl
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0481. Train Acc: 36.8250, Test loss: 0.0480. Test Acc: 37.5400. Time/epoch: 4.7811
EPOCH 10. Progress: 50.0%.
Train loss: 0.0481. Train Acc: 36.8250, Test loss: 0.0480. Test Acc: 37.5400. Time/epoch: 4.7463
EPOCH 20. Progress: 100.0%.
Train loss: 0.0481. Train Acc: 36.8250, Test loss: 0.0480. Test Acc: 37.5400. Time/epoch: 4.7215
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | ▄▄▃▁▁▁▅▃▁▄▄▁▂▆▆▆█▁▅▄▃ |
Loss/val | ▆▃▃▂▂▂▆▄▁▆▃▂▄▅██▇▁▄▆▂ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.04808 |
Loss/val | 0.04795 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_021021-7fx470wl/logs
wandb: Agent Starting Run: 5wjouk0d with config:
wandb: batch_size: 128
wandb: epochs: 20
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_021213-5wjouk0d
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0013. Train Acc: 92.9325, Test loss: 0.0013. Test Acc: 92.8700. Time/epoch: 2.4512
EPOCH 10. Progress: 50.0%.
Train loss: 0.0006. Train Acc: 96.8700, Test loss: 0.0007. Test Acc: 96.4300. Time/epoch: 2.4318
EPOCH 20. Progress: 100.0%.
Train loss: 0.0007. Train Acc: 96.5075, Test loss: 0.0008. Test Acc: 96.0000. Time/epoch: 2.4348
Run history:
Accuracy/train | ▁▂▄▁▆▅▆▆▇▇▇█▇█▇▇█▇▆▇▇ |
Accuracy/val | ▁▂▄▁▅▅▇▇▇▇▇██▇▇▇█▇▅▇▆ |
Loss/train | █▇▅█▄▄▂▂▂▂▂▁▂▁▁▁▁▁▃▁▂ |
Loss/val | █▇▆█▄▄▂▂▂▂▂▁▂▁▂▂▁▂▃▂▃ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 96.5075 |
Accuracy/val | 96.0 |
Loss/train | 0.00069 |
Loss/val | 0.00085 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_021213-5wjouk0d/logs
wandb: Agent Starting Run: ualodyxv with config:
wandb: batch_size: 128
wandb: epochs: 50
wandb: learning_rate: 0.01
wandb: optimizer: adam
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_021315-ualodyxv
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0121. Train Acc: 36.8250, Test loss: 0.0121. Test Acc: 37.5400. Time/epoch: 2.4980
EPOCH 10. Progress: 20.0%.
Train loss: 0.0120. Train Acc: 36.8250, Test loss: 0.0121. Test Acc: 37.5400. Time/epoch: 2.4229
EPOCH 20. Progress: 40.0%.
Train loss: 0.0120. Train Acc: 36.8250, Test loss: 0.0121. Test Acc: 37.5400. Time/epoch: 2.4428
EPOCH 30. Progress: 60.0%.
Train loss: 0.0120. Train Acc: 36.8250, Test loss: 0.0121. Test Acc: 37.5400. Time/epoch: 2.3018
EPOCH 40. Progress: 80.0%.
Train loss: 0.0120. Train Acc: 36.8250, Test loss: 0.0121. Test Acc: 37.5400. Time/epoch: 2.2865
EPOCH 50. Progress: 100.0%.
Train loss: 0.0120. Train Acc: 36.8250, Test loss: 0.0121. Test Acc: 37.5400. Time/epoch: 2.2946
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | █▄▂▄▃▅▂▅▃▂▃▁▃▇▂▁▂▄▂▂▂▂▂▂▂▁▂▂▂▂▂▂▁▁▃▂▁▂▁▁ |
Loss/val | ▅▄▃▃▃▆▄▄▄█▄▃▅▄▄▂▃▅▃▃▆▂▂▅▄▄▄▃▃▄▃▃▄▃▃▂▆▂▂▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.01203 |
Loss/val | 0.01208 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_021315-ualodyxv/logs
wandb: Agent Starting Run: aica9whg with config:
wandb: batch_size: 128
wandb: epochs: 50
wandb: learning_rate: 1e-05
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_021530-aica9whg
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0047. Train Acc: 78.7500, Test loss: 0.0047. Test Acc: 78.8200. Time/epoch: 2.3694
EPOCH 10. Progress: 20.0%.
Train loss: 0.0017. Train Acc: 89.8825, Test loss: 0.0018. Test Acc: 89.6000. Time/epoch: 2.2194
EPOCH 20. Progress: 40.0%.
Train loss: 0.0014. Train Acc: 92.1825, Test loss: 0.0015. Test Acc: 91.9300. Time/epoch: 2.3605
EPOCH 30. Progress: 60.0%.
Train loss: 0.0013. Train Acc: 93.3900, Test loss: 0.0013. Test Acc: 93.2300. Time/epoch: 2.3704
EPOCH 40. Progress: 80.0%.
Train loss: 0.0012. Train Acc: 93.8375, Test loss: 0.0012. Test Acc: 93.8600. Time/epoch: 2.2167
EPOCH 50. Progress: 100.0%.
Train loss: 0.0011. Train Acc: 94.0700, Test loss: 0.0012. Test Acc: 94.1000. Time/epoch: 2.2159
Run history:
Accuracy/train | ▁▄▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇▇▇▇▇▇▇████████████████ |
Accuracy/val | ▁▄▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇▇▇▇▇▇▇▇███████████████ |
Loss/train | █▅▄▃▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▅▄▃▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 94.07 |
Accuracy/val | 94.1 |
Loss/train | 0.00113 |
Loss/val | 0.00118 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_021530-aica9whg/logs
wandb: Agent Starting Run: ye109ifx with config:
wandb: batch_size: 64
wandb: epochs: 50
wandb: learning_rate: 0.0001
wandb: optimizer: sgd
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_021743-ye109ifx
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0037. Train Acc: 89.5775, Test loss: 0.0039. Test Acc: 89.3200. Time/epoch: 3.1174
EPOCH 10. Progress: 20.0%.
Train loss: 0.0017. Train Acc: 95.9275, Test loss: 0.0018. Test Acc: 95.7400. Time/epoch: 3.0752
EPOCH 20. Progress: 40.0%.
Train loss: 0.0014. Train Acc: 96.5225, Test loss: 0.0016. Test Acc: 96.3300. Time/epoch: 2.9782
EPOCH 30. Progress: 60.0%.
Train loss: 0.0013. Train Acc: 96.7325, Test loss: 0.0015. Test Acc: 96.3300. Time/epoch: 3.1177
EPOCH 40. Progress: 80.0%.
Train loss: 0.0012. Train Acc: 96.8750, Test loss: 0.0014. Test Acc: 96.6700. Time/epoch: 3.0941
EPOCH 50. Progress: 100.0%.
Train loss: 0.0009. Train Acc: 97.8125, Test loss: 0.0011. Test Acc: 97.4300. Time/epoch: 3.0942
Run history:
Accuracy/train | ▁▄▅▅▆▆▆▆▆▆▆▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇█▇██▇█████ |
Accuracy/val | ▁▄▅▆▆▆▆▆▇▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇██▇██▇█████ |
Loss/train | █▆▅▄▄▄▃▃▃▃▃▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▁▂▁▁▂▁▁▁▁▁ |
Loss/val | █▆▅▄▄▄▃▃▃▃▃▃▂▃▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▁▂▁▁▂▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 97.8125 |
Accuracy/val | 97.43 |
Loss/train | 0.00092 |
Loss/val | 0.00108 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_021743-ye109ifx/logs
wandb: Agent Starting Run: k6x3u2n4 with config:
wandb: batch_size: 32
wandb: epochs: 50
wandb: learning_rate: 1e-05
wandb: optimizer: sgd
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_022031-k6x3u2n4
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0143. Train Acc: 80.5825, Test loss: 0.0144. Test Acc: 80.4000. Time/epoch: 4.7606
EPOCH 10. Progress: 20.0%.
Train loss: 0.0045. Train Acc: 94.2575, Test loss: 0.0047. Test Acc: 94.1900. Time/epoch: 4.7643
EPOCH 20. Progress: 40.0%.
Train loss: 0.0041. Train Acc: 94.9200, Test loss: 0.0043. Test Acc: 94.8200. Time/epoch: 4.7542
EPOCH 30. Progress: 60.0%.
Train loss: 0.0038. Train Acc: 95.3125, Test loss: 0.0039. Test Acc: 95.0100. Time/epoch: 4.6119
EPOCH 40. Progress: 80.0%.
Train loss: 0.0038. Train Acc: 95.4925, Test loss: 0.0039. Test Acc: 95.3200. Time/epoch: 4.6420
EPOCH 50. Progress: 100.0%.
Train loss: 0.0035. Train Acc: 95.5825, Test loss: 0.0037. Test Acc: 95.3700. Time/epoch: 4.6310
Run history:
Accuracy/train | ▁▅▆▆▇▇▇▇▇▇▇█▇█▇▇█████▇█▇████████████████ |
Accuracy/val | ▁▅▆▆▇▇▇▇▇▇▇███▇▇█████▇█▇██████▇█████████ |
Loss/train | █▅▄▃▂▂▂▂▂▂▂▁▁▁▁▂▁▁▁▁▁▁▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▅▄▃▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 95.5825 |
Accuracy/val | 95.37 |
Loss/train | 0.00352 |
Loss/val | 0.00369 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_022031-k6x3u2n4/logs
wandb: Agent Starting Run: mty627wj with config:
wandb: batch_size: 32
wandb: epochs: 50
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_022444-mty627wj
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0068. Train Acc: 91.9800, Test loss: 0.0069. Test Acc: 91.9300. Time/epoch: 5.1930
EPOCH 10. Progress: 20.0%.
Train loss: 0.0018. Train Acc: 97.8925, Test loss: 0.0023. Test Acc: 97.3300. Time/epoch: 5.0212
EPOCH 20. Progress: 40.0%.
Train loss: 0.0024. Train Acc: 97.1275, Test loss: 0.0032. Test Acc: 96.6400. Time/epoch: 5.1637
EPOCH 30. Progress: 60.0%.
Train loss: 0.0014. Train Acc: 98.3925, Test loss: 0.0028. Test Acc: 97.4600. Time/epoch: 5.1462
EPOCH 40. Progress: 80.0%.
Train loss: 0.0009. Train Acc: 98.9500, Test loss: 0.0025. Test Acc: 97.5800. Time/epoch: 5.1569
EPOCH 50. Progress: 100.0%.
Train loss: 0.0012. Train Acc: 98.6050, Test loss: 0.0037. Test Acc: 97.0200. Time/epoch: 5.0122
Run history:
Accuracy/train | ▁▅▅▂▄▅▅▄▇▆▆▆▆▇▆▄▆▆▇▆▆▇▇█▇█▇▇██▇██▇██▆▇██ |
Accuracy/val | ▁▅▅▂▄▅▅▄▇▆▆▇▆▇▇▄▆▆▇▆▆█▇█▇█▇▇▇█▇█▇▇█▇▆▇▇▇ |
Loss/train | █▄▄▆▅▄▄▄▂▃▃▃▃▂▂▅▃▂▂▃▃▂▂▁▂▁▂▂▁▁▃▁▁▂▁▁▃▁▁▁ |
Loss/val | █▄▃▆▅▃▃▄▁▂▃▂▂▁▂▅▃▂▂▃▃▁▂▁▂▁▂▃▂▂▅▂▃▃▂▃▅▄▃▃ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.605 |
Accuracy/val | 97.02 |
Loss/train | 0.00118 |
Loss/val | 0.00372 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_022444-mty627wj/logs
wandb: Agent Starting Run: yjbe5i0g with config:
wandb: batch_size: 64
wandb: epochs: 10
wandb: learning_rate: 1e-05
wandb: optimizer: adam
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_022918-yjbe5i0g
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0078. Train Acc: 84.5950, Test loss: 0.0078. Test Acc: 84.4300. Time/epoch: 3.3518
EPOCH 10. Progress: 100.0%.
Train loss: 0.0025. Train Acc: 93.1525, Test loss: 0.0026. Test Acc: 93.2400. Time/epoch: 3.1908
Run history:
Accuracy/train | ▁▅▆▆▇▇▇▇███ |
Accuracy/val | ▁▅▆▆▇▇▇▇███ |
Loss/train | █▄▃▂▂▂▁▁▁▁▁ |
Loss/val | █▄▃▂▂▂▁▁▁▁▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 93.1525 |
Accuracy/val | 93.24 |
Loss/train | 0.00253 |
Loss/val | 0.00261 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_022918-yjbe5i0g/logs
wandb: Agent Starting Run: 6048t5bg with config:
wandb: batch_size: 128
wandb: epochs: 10
wandb: learning_rate: 3e-05
wandb: optimizer: adam
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_023008-6048t5bg
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0020. Train Acc: 90.9550, Test loss: 0.0020. Test Acc: 91.2400. Time/epoch: 2.4864
EPOCH 10. Progress: 100.0%.
Train loss: 0.0010. Train Acc: 95.1750, Test loss: 0.0010. Test Acc: 95.1600. Time/epoch: 2.4245
Run history:
Accuracy/train | ▁▄▅▆▆▇▇▇▇▇█ |
Accuracy/val | ▁▄▅▆▆▇▇▇▇▇█ |
Loss/train | █▅▄▃▂▂▂▂▁▂▁ |
Loss/val | █▄▃▃▂▂▂▂▁▂▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 95.175 |
Accuracy/val | 95.16 |
Loss/train | 0.00097 |
Loss/val | 0.00101 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_023008-6048t5bg/logs
wandb: Agent Starting Run: mgan5bka with config:
wandb: batch_size: 64
wandb: epochs: 50
wandb: learning_rate: 1e-05
wandb: optimizer: sgd
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_023051-mgan5bka
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0055. Train Acc: 85.7550, Test loss: 0.0055. Test Acc: 86.4100. Time/epoch: 3.1400
EPOCH 10. Progress: 20.0%.
Train loss: 0.0028. Train Acc: 93.4300, Test loss: 0.0029. Test Acc: 93.2700. Time/epoch: 3.1073
EPOCH 20. Progress: 40.0%.
Train loss: 0.0024. Train Acc: 94.1525, Test loss: 0.0025. Test Acc: 94.1400. Time/epoch: 3.0903
EPOCH 30. Progress: 60.0%.
Train loss: 0.0022. Train Acc: 94.7525, Test loss: 0.0023. Test Acc: 94.7300. Time/epoch: 2.9781
EPOCH 40. Progress: 80.0%.
Train loss: 0.0020. Train Acc: 95.3200, Test loss: 0.0021. Test Acc: 95.2500. Time/epoch: 2.9601
EPOCH 50. Progress: 100.0%.
Train loss: 0.0019. Train Acc: 95.0275, Test loss: 0.0020. Test Acc: 95.1000. Time/epoch: 2.9362
Run history:
Accuracy/train | ▁▄▅▅▆▆▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇█▇████████▇████████ |
Accuracy/val | ▁▃▅▅▅▆▆▆▆▆▆▇▇▆▇▇▇▇▇▇▇█▇█▇█▇█████████████ |
Loss/train | █▅▄▄▄▃▃▃▃▃▂▂▂▂▂▂▂▂▂▂▂▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▅▅▄▄▃▃▃▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▁▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 95.0275 |
Accuracy/val | 95.1 |
Loss/train | 0.00194 |
Loss/val | 0.00204 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_023051-mgan5bka/logs
wandb: Agent Starting Run: 8yc0qcsu with config:
wandb: batch_size: 128
wandb: epochs: 10
wandb: learning_rate: 3e-05
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_023338-8yc0qcsu
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0021. Train Acc: 88.7475, Test loss: 0.0022. Test Acc: 88.9100. Time/epoch: 2.3702
EPOCH 10. Progress: 100.0%.
Train loss: 0.0012. Train Acc: 93.6400, Test loss: 0.0012. Test Acc: 94.0300. Time/epoch: 2.2140
Run history:
Accuracy/train | ▁▃▄▆▇▄▃█▇▁█ |
Accuracy/val | ▁▃▄▆▇▄▃▇▆▁█ |
Loss/train | █▅▄▃▂▃▅▂▃▇▁ |
Loss/val | █▅▄▃▂▃▅▂▃▇▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 93.64 |
Accuracy/val | 94.03 |
Loss/train | 0.00121 |
Loss/val | 0.00124 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_023338-8yc0qcsu/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: w3rprb9t with config:
wandb: batch_size: 64
wandb: epochs: 10
wandb: learning_rate: 0.01
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_023425-w3rprb9t
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0240. Test Acc: 37.5400. Time/epoch: 3.2045
EPOCH 10. Progress: 100.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 3.1797
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | ▁█▆▃▆▄▂▄▃▄▃ |
Loss/val | ▁█▆▅▆▃▆▇▂▂▅ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.02402 |
Loss/val | 0.02407 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_023425-w3rprb9t/logs
wandb: Agent Starting Run: efloip58 with config:
wandb: batch_size: 64
wandb: epochs: 50
wandb: learning_rate: 3e-05
wandb: optimizer: sgd
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_023511-efloip58
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0044. Train Acc: 90.6625, Test loss: 0.0044. Test Acc: 90.9400. Time/epoch: 3.1424
EPOCH 10. Progress: 20.0%.
Train loss: 0.0024. Train Acc: 94.0600, Test loss: 0.0024. Test Acc: 94.2700. Time/epoch: 3.1304
EPOCH 20. Progress: 40.0%.
Train loss: 0.0018. Train Acc: 95.4925, Test loss: 0.0019. Test Acc: 95.5100. Time/epoch: 2.9462
EPOCH 30. Progress: 60.0%.
Train loss: 0.0016. Train Acc: 96.1650, Test loss: 0.0017. Test Acc: 96.1700. Time/epoch: 3.0749
EPOCH 40. Progress: 80.0%.
Train loss: 0.0016. Train Acc: 95.9875, Test loss: 0.0017. Test Acc: 95.9400. Time/epoch: 3.0883
EPOCH 50. Progress: 100.0%.
Train loss: 0.0016. Train Acc: 95.9375, Test loss: 0.0017. Test Acc: 95.6600. Time/epoch: 3.1140
Run history:
Accuracy/train | ▁▄▄▅▅▆▆▆▅▅▆▅▆▆▆▇▇▆▆▇▆▇▇▇▇▇▇█▇▇▇▇█▇█████▇ |
Accuracy/val | ▁▄▄▅▅▆▅▆▅▅▆▅▆▆▆▇▇▆▆▇▆▇▇▇█▇▇█▇▇█▇█▇█████▇ |
Loss/train | █▅▄▄▃▃▃▃▃▃▂▃▂▂▂▂▂▂▃▂▂▂▂▂▁▂▂▁▁▂▁▁▁▂▁▁▁▁▁▁ |
Loss/val | █▅▄▄▃▃▃▃▃▃▂▃▂▂▃▂▂▂▃▂▂▂▂▂▁▂▂▁▁▂▁▁▁▂▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 95.9375 |
Accuracy/val | 95.66 |
Loss/train | 0.00159 |
Loss/val | 0.00169 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_023511-efloip58/logs
wandb: Agent Starting Run: 58g5zuda with config:
wandb: batch_size: 32
wandb: epochs: 10
wandb: learning_rate: 0.01
wandb: optimizer: adam
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_023759-58g5zuda
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0481. Train Acc: 36.8250, Test loss: 0.0480. Test Acc: 37.5400. Time/epoch: 5.2325
EPOCH 10. Progress: 100.0%.
Train loss: 0.0480. Train Acc: 36.8250, Test loss: 0.0479. Test Acc: 37.5400. Time/epoch: 5.1512
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | █▃▆▅▇▃█▄▁▃▁ |
Loss/val | █▂▆▄█▃▄▃▁▂▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.04805 |
Loss/val | 0.04794 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_023759-58g5zuda/logs
wandb: Agent Starting Run: 69htsr9g with config:
wandb: batch_size: 128
wandb: epochs: 10
wandb: learning_rate: 0.001
wandb: optimizer: sgd
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_023909-69htsr9g
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0041. Train Acc: 76.7550, Test loss: 0.0041. Test Acc: 77.0200. Time/epoch: 2.2282
EPOCH 10. Progress: 100.0%.
Train loss: 0.0013. Train Acc: 92.8875, Test loss: 0.0014. Test Acc: 92.7800. Time/epoch: 2.3363
Run history:
Accuracy/train | ▁▆▆▇▅▇▇███▇ |
Accuracy/val | ▁▆▆▇▅▇▇███▇ |
Loss/train | █▃▃▂▄▂▂▁▁▁▁ |
Loss/val | █▃▃▂▅▂▂▁▁▁▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 92.8875 |
Accuracy/val | 92.78 |
Loss/train | 0.00131 |
Loss/val | 0.00139 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_023909-69htsr9g/logs
wandb: Agent Starting Run: zykk0qgn with config:
wandb: batch_size: 32
wandb: epochs: 20
wandb: learning_rate: 1e-05
wandb: optimizer: adam
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_023949-zykk0qgn
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0110. Train Acc: 86.2175, Test loss: 0.0112. Test Acc: 86.1000. Time/epoch: 5.0716
EPOCH 10. Progress: 50.0%.
Train loss: 0.0043. Train Acc: 94.6700, Test loss: 0.0045. Test Acc: 94.7200. Time/epoch: 5.0484
EPOCH 20. Progress: 100.0%.
Train loss: 0.0035. Train Acc: 95.6950, Test loss: 0.0037. Test Acc: 95.6200. Time/epoch: 5.1391
Run history:
Accuracy/train | ▁▃▄▅▆▆▆▇▇▇▇▇▇▇███▇█▇█ |
Accuracy/val | ▁▃▄▅▆▆▆▇▇▇▇▇▇▇███▇█▇█ |
Loss/train | █▅▄▄▃▃▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁ |
Loss/val | █▅▄▄▃▃▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 95.695 |
Accuracy/val | 95.62 |
Loss/train | 0.00349 |
Loss/val | 0.00367 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_023949-zykk0qgn/logs
wandb: Agent Starting Run: lpnx987r with config:
wandb: batch_size: 64
wandb: epochs: 10
wandb: learning_rate: 0.0003
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_024151-lpnx987r
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0029. Train Acc: 92.3125, Test loss: 0.0029. Test Acc: 92.3300. Time/epoch: 3.0446
EPOCH 10. Progress: 100.0%.
Train loss: 0.0023. Train Acc: 93.5900, Test loss: 0.0024. Test Acc: 93.7000. Time/epoch: 3.0265
Run history:
Accuracy/train | ▁▆▇▇▅▆▄█▄▄▆ |
Accuracy/val | ▁▇▇▇▅▆▅█▃▄▆ |
Loss/train | █▅▄▅▃▃▄▁▄▄▃ |
Loss/val | █▄▄▄▃▃▄▁▄▄▃ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 93.59 |
Accuracy/val | 93.7 |
Loss/train | 0.00235 |
Loss/val | 0.00236 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_024151-lpnx987r/logs
wandb: Agent Starting Run: 1sytqfqj with config:
wandb: batch_size: 128
wandb: epochs: 50
wandb: learning_rate: 0.0001
wandb: optimizer: sgd
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_024239-1sytqfqj
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0019. Train Acc: 91.2225, Test loss: 0.0019. Test Acc: 91.1300. Time/epoch: 2.3752
EPOCH 10. Progress: 20.0%.
Train loss: 0.0010. Train Acc: 95.2700, Test loss: 0.0010. Test Acc: 95.0900. Time/epoch: 2.1876
EPOCH 20. Progress: 40.0%.
Train loss: 0.0008. Train Acc: 95.9575, Test loss: 0.0008. Test Acc: 95.9300. Time/epoch: 2.3217
EPOCH 30. Progress: 60.0%.
Train loss: 0.0008. Train Acc: 95.8325, Test loss: 0.0009. Test Acc: 95.5600. Time/epoch: 2.3351
EPOCH 40. Progress: 80.0%.
Train loss: 0.0007. Train Acc: 96.5900, Test loss: 0.0007. Test Acc: 96.3200. Time/epoch: 2.3392
EPOCH 50. Progress: 100.0%.
Train loss: 0.0007. Train Acc: 96.2000, Test loss: 0.0008. Test Acc: 95.9700. Time/epoch: 2.1825
Run history:
Accuracy/train | ▂▁▅▂▆▆▅▅▆▆▆▇▇▇▇▇▇▇▇▇▇▇█▇▇▇▆█▇██████▇█▇█▇ |
Accuracy/val | ▂▁▅▂▆▆▆▆▆▅▆▇▆▇▇▇▇▇▇▇▇▇██▇▇▆█▇██████▇█▇█▇ |
Loss/train | █▇▄▆▃▃▄▃▃▃▃▂▂▂▂▂▂▂▂▂▂▂▁▂▂▂▂▁▂▁▁▁▁▁▁▁▁▂▁▂ |
Loss/val | █▇▄▆▃▃▃▃▃▃▃▂▂▂▂▂▂▂▂▂▂▂▁▁▂▂▂▁▂▁▁▁▁▁▁▁▁▂▁▂ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 96.2 |
Accuracy/val | 95.97 |
Loss/train | 0.00074 |
Loss/val | 0.0008 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_024239-1sytqfqj/logs
wandb: Agent Starting Run: b6eyrf08 with config:
wandb: batch_size: 64
wandb: epochs: 50
wandb: learning_rate: 0.0001
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_024450-b6eyrf08
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0047. Train Acc: 86.9175, Test loss: 0.0047. Test Acc: 86.9200. Time/epoch: 3.2241
EPOCH 10. Progress: 20.0%.
Train loss: 0.0015. Train Acc: 96.1675, Test loss: 0.0016. Test Acc: 96.0600. Time/epoch: 3.0156
EPOCH 20. Progress: 40.0%.
Train loss: 0.0010. Train Acc: 97.7150, Test loss: 0.0012. Test Acc: 97.2600. Time/epoch: 3.0039
EPOCH 30. Progress: 60.0%.
Train loss: 0.0007. Train Acc: 98.4500, Test loss: 0.0009. Test Acc: 97.9400. Time/epoch: 3.1780
EPOCH 40. Progress: 80.0%.
Train loss: 0.0005. Train Acc: 98.8300, Test loss: 0.0009. Test Acc: 98.2600. Time/epoch: 3.1700
EPOCH 50. Progress: 100.0%.
Train loss: 0.0006. Train Acc: 98.6625, Test loss: 0.0009. Test Acc: 97.7700. Time/epoch: 3.1696
Run history:
Accuracy/train | ▁▅▅▅▆▆▇▆▆▇▆▇▇▇▇▆▇▇▇▇▇▇▇██▆▇██▇███▇██████ |
Accuracy/val | ▁▅▅▅▆▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇█████▆███▇██████████ |
Loss/train | █▅▄▄▃▃▃▃▃▂▃▂▂▂▂▃▂▂▂▂▂▂▂▁▁▃▂▁▁▂▁▂▁▂▁▁▁▁▁▁ |
Loss/val | █▄▄▄▃▃▂▃▂▂▂▂▂▂▂▃▁▁▂▂▁▁▁▁▁▃▁▁▁▂▁▁▁▂▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.6625 |
Accuracy/val | 97.77 |
Loss/train | 0.00057 |
Loss/val | 0.00095 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_024450-b6eyrf08/logs
wandb: Agent Starting Run: w3vdhzz8 with config:
wandb: batch_size: 128
wandb: epochs: 50
wandb: learning_rate: 0.01
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_024743-w3vdhzz8
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0121. Train Acc: 36.8250, Test loss: 0.0121. Test Acc: 37.5400. Time/epoch: 2.4030
EPOCH 10. Progress: 20.0%.
Train loss: 0.0121. Train Acc: 36.8250, Test loss: 0.0121. Test Acc: 37.5400. Time/epoch: 2.3531
EPOCH 20. Progress: 40.0%.
Train loss: 0.0121. Train Acc: 36.8250, Test loss: 0.0122. Test Acc: 37.5400. Time/epoch: 2.2054
EPOCH 30. Progress: 60.0%.
Train loss: 0.0121. Train Acc: 36.8250, Test loss: 0.0122. Test Acc: 37.5400. Time/epoch: 2.2200
EPOCH 40. Progress: 80.0%.
Train loss: 0.0121. Train Acc: 36.8250, Test loss: 0.0122. Test Acc: 37.5400. Time/epoch: 2.3810
EPOCH 50. Progress: 100.0%.
Train loss: 0.0120. Train Acc: 36.8250, Test loss: 0.0121. Test Acc: 37.5400. Time/epoch: 2.3692
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | ▃▆▅█▆▅▅▅▂▇▂▆▂█▄▅▄▄▅▃▅▄▂▄▃▁▂▄▂▂▆▂▁▁▂▃▂▂▄▁ |
Loss/val | ▂▆▆█▆▆▅▅▁▆▃▇▃█▄▅▄▄▅▄▅▄▂▅▅▂▂▄▁▂▆▂▂▁▃▄▃▂▃▂ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.01205 |
Loss/val | 0.01212 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_024743-w3vdhzz8/logs
wandb: Agent Starting Run: eu9lai07 with config:
wandb: batch_size: 128
wandb: epochs: 10
wandb: learning_rate: 3e-05
wandb: optimizer: sgd
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_024954-eu9lai07
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0044. Train Acc: 75.5350, Test loss: 0.0044. Test Acc: 76.2800. Time/epoch: 2.2035
EPOCH 10. Progress: 100.0%.
Train loss: 0.0013. Train Acc: 93.4050, Test loss: 0.0014. Test Acc: 93.2300. Time/epoch: 2.3293
Run history:
Accuracy/train | ▁▆▇▇█▇█████ |
Accuracy/val | ▁▆▇▇█▇█████ |
Loss/train | █▃▂▂▁▂▁▁▁▁▁ |
Loss/val | █▃▂▂▁▂▁▁▁▁▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 93.405 |
Accuracy/val | 93.23 |
Loss/train | 0.00134 |
Loss/val | 0.00142 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_024954-eu9lai07/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: u7xrakak with config:
wandb: batch_size: 128
wandb: epochs: 50
wandb: learning_rate: 0.0003
wandb: optimizer: sgd
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_025041-u7xrakak
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0033. Train Acc: 81.8575, Test loss: 0.0033. Test Acc: 81.8200. Time/epoch: 2.2008
EPOCH 10. Progress: 20.0%.
Train loss: 0.0013. Train Acc: 93.2875, Test loss: 0.0013. Test Acc: 93.1900. Time/epoch: 2.1925
EPOCH 20. Progress: 40.0%.
Train loss: 0.0013. Train Acc: 93.7175, Test loss: 0.0013. Test Acc: 93.5500. Time/epoch: 2.3314
EPOCH 30. Progress: 60.0%.
Train loss: 0.0009. Train Acc: 95.6000, Test loss: 0.0010. Test Acc: 95.1500. Time/epoch: 2.3217
EPOCH 40. Progress: 80.0%.
Train loss: 0.0008. Train Acc: 96.1400, Test loss: 0.0009. Test Acc: 95.5400. Time/epoch: 2.2083
EPOCH 50. Progress: 100.0%.
Train loss: 0.0007. Train Acc: 96.5650, Test loss: 0.0009. Test Acc: 95.7400. Time/epoch: 2.2010
Run history:
Accuracy/train | ▁▄▆▆▆▆▅▆▆▇▆▇▇▇▇▇▇▇▆▇██▇▇██████████▇█████ |
Accuracy/val | ▁▄▆▆▇▇▆▆▇▇▇▇▇▇▇▇▇█▇███████████████▇█████ |
Loss/train | █▆▄▃▃▃▄▃▃▂▂▂▂▂▂▂▃▂▃▂▂▁▁▂▁▁▁▁▁▁▁▁▁▁▂▁▁▁▁▁ |
Loss/val | █▆▃▃▂▂▄▃▂▂▂▂▂▂▂▂▂▂▃▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▂▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 96.565 |
Accuracy/val | 95.74 |
Loss/train | 0.0007 |
Loss/val | 0.00088 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_025041-u7xrakak/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: p4whnt5d with config:
wandb: batch_size: 128
wandb: epochs: 10
wandb: learning_rate: 0.01
wandb: optimizer: adam
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_025259-p4whnt5d
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0120. Train Acc: 36.8250, Test loss: 0.0121. Test Acc: 37.5400. Time/epoch: 2.4557
EPOCH 10. Progress: 100.0%.
Train loss: 0.0120. Train Acc: 36.8250, Test loss: 0.0121. Test Acc: 37.5400. Time/epoch: 2.3005
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | ▃▂▁▄▇▄▆▅█▃▂ |
Loss/val | ▄▄▁▄▆▅██▅▂▇ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.01203 |
Loss/val | 0.01213 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_025259-p4whnt5d/logs
wandb: Agent Starting Run: 9mzw55p6 with config:
wandb: batch_size: 64
wandb: epochs: 50
wandb: learning_rate: 3e-05
wandb: optimizer: sgd
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_025339-9mzw55p6
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0041. Train Acc: 89.8300, Test loss: 0.0042. Test Acc: 89.6100. Time/epoch: 3.1495
EPOCH 10. Progress: 20.0%.
Train loss: 0.0020. Train Acc: 94.8225, Test loss: 0.0021. Test Acc: 94.7100. Time/epoch: 3.1173
EPOCH 20. Progress: 40.0%.
Train loss: 0.0017. Train Acc: 95.6725, Test loss: 0.0019. Test Acc: 95.5400. Time/epoch: 2.9793
EPOCH 30. Progress: 60.0%.
Train loss: 0.0017. Train Acc: 95.6575, Test loss: 0.0019. Test Acc: 95.4800. Time/epoch: 3.1003
EPOCH 40. Progress: 80.0%.
Train loss: 0.0022. Train Acc: 94.2775, Test loss: 0.0023. Test Acc: 94.3300. Time/epoch: 3.0977
EPOCH 50. Progress: 100.0%.
Train loss: 0.0015. Train Acc: 96.1125, Test loss: 0.0017. Test Acc: 95.9600. Time/epoch: 3.1133
Run history:
Accuracy/train | ▁▄▅▅▆▆▆▆▆▆▇▆▇▇▆▇▇▆▇▇█▇██▇▇█▇██▇██████▇██ |
Accuracy/val | ▁▄▅▅▆▆▆▆▇▆▇▆▆▇▇▇▇▆▇▇████▇▇█▇█████████▇██ |
Loss/train | █▅▄▄▃▃▃▃▂▃▂▃▂▂▂▂▂▃▂▂▁▁▁▁▂▂▁▂▁▁▁▁▁▁▁▁▁▂▁▁ |
Loss/val | █▅▄▄▃▃▃▃▂▃▂▃▂▂▂▂▂▃▂▂▁▁▂▁▂▂▂▂▁▁▁▁▁▁▁▁▁▂▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 96.1125 |
Accuracy/val | 95.96 |
Loss/train | 0.00151 |
Loss/val | 0.00168 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_025339-9mzw55p6/logs
wandb: Agent Starting Run: migt86gf with config:
wandb: batch_size: 64
wandb: epochs: 20
wandb: learning_rate: 0.01
wandb: optimizer: sgd
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_025627-migt86gf
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0241. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 2.9943
EPOCH 10. Progress: 50.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0240. Test Acc: 37.5400. Time/epoch: 3.1021
EPOCH 20. Progress: 100.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 3.0975
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | █▂▄▁▃▂▂▅▂▄▁▃▆▁▁▂▂▁▂▃▁ |
Loss/val | █▅▃▃▄▁▄▆▅▆▃▅▇▂▄▂▃▃▂▄▅ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.02402 |
Loss/val | 0.02407 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_025627-migt86gf/logs
wandb: Agent Starting Run: 3zun05t5 with config:
wandb: batch_size: 32
wandb: epochs: 20
wandb: learning_rate: 1e-05
wandb: optimizer: sgd
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_025747-3zun05t5
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0106. Train Acc: 87.3925, Test loss: 0.0108. Test Acc: 86.9600. Time/epoch: 4.6284
EPOCH 10. Progress: 50.0%.
Train loss: 0.0048. Train Acc: 93.9650, Test loss: 0.0050. Test Acc: 93.9400. Time/epoch: 4.7316
EPOCH 20. Progress: 100.0%.
Train loss: 0.0058. Train Acc: 92.3425, Test loss: 0.0060. Test Acc: 92.1000. Time/epoch: 4.7718
Run history:
Accuracy/train | ▁▃▅▆▆▆▇▇▇▇▇▇▇▇▇▇████▆ |
Accuracy/val | ▁▃▅▆▆▆▇▇▇▇▇▇▇▇█▇████▆ |
Loss/train | █▅▄▃▃▃▂▂▂▂▂▁▂▁▁▂▁▁▁▁▃ |
Loss/val | █▅▄▃▃▃▂▂▂▂▂▁▂▁▁▂▁▁▁▁▃ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 92.3425 |
Accuracy/val | 92.1 |
Loss/train | 0.00576 |
Loss/val | 0.00596 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_025747-3zun05t5/logs
wandb: Agent Starting Run: 6742a047 with config:
wandb: batch_size: 128
wandb: epochs: 10
wandb: learning_rate: 0.01
wandb: optimizer: adam
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_025939-6742a047
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0120. Train Acc: 36.8250, Test loss: 0.0121. Test Acc: 37.5400. Time/epoch: 2.3244
EPOCH 10. Progress: 100.0%.
Train loss: 0.0120. Train Acc: 36.8250, Test loss: 0.0121. Test Acc: 37.5400. Time/epoch: 2.4324
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | █▂▅▁▇▂▁▃▄▂▂ |
Loss/val | █▃▇▁▅▆▅▄█▄▆ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.01203 |
Loss/val | 0.01212 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_025939-6742a047/logs
wandb: Agent Starting Run: 7xfwvxrr with config:
wandb: batch_size: 64
wandb: epochs: 20
wandb: learning_rate: 0.001
wandb: optimizer: sgd
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_030020-7xfwvxrr
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0151. Train Acc: 63.0500, Test loss: 0.0151. Test Acc: 63.6700. Time/epoch: 3.0093
EPOCH 10. Progress: 50.0%.
Train loss: 0.0048. Train Acc: 88.4175, Test loss: 0.0052. Test Acc: 88.3000. Time/epoch: 3.0877
EPOCH 20. Progress: 100.0%.
Train loss: 0.0036. Train Acc: 92.3075, Test loss: 0.0046. Test Acc: 90.6500. Time/epoch: 3.1176
Run history:
Accuracy/train | ▂▁▃▅▅▅▆▆▇▇▇▇▇▇██▇█▇██ |
Accuracy/val | ▂▁▃▅▅▅▆▆▇▇▇▇▇▇████▇██ |
Loss/train | █▇▆▃▃▃▃▃▂▂▂▂▂▂▁▁▂▁▂▁▁ |
Loss/val | █▇▅▃▃▃▂▃▂▂▂▂▂▂▁▁▁▁▂▁▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 92.3075 |
Accuracy/val | 90.65 |
Loss/train | 0.00355 |
Loss/val | 0.00455 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_030020-7xfwvxrr/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: agga0njv with config:
wandb: batch_size: 128
wandb: epochs: 20
wandb: learning_rate: 1e-05
wandb: optimizer: adam
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_030146-agga0njv
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0054. Train Acc: 75.3475, Test loss: 0.0054. Test Acc: 76.1300. Time/epoch: 2.3289
EPOCH 10. Progress: 50.0%.
Train loss: 0.0017. Train Acc: 91.4675, Test loss: 0.0017. Test Acc: 91.8000. Time/epoch: 2.4321
EPOCH 20. Progress: 100.0%.
Train loss: 0.0013. Train Acc: 92.9650, Test loss: 0.0014. Test Acc: 92.8700. Time/epoch: 2.4259
Run history:
Accuracy/train | ▁▅▆▆▆▇▇▇▇▇▇▇█████████ |
Accuracy/val | ▁▄▆▆▆▆▇▇▇▇█▇█████████ |
Loss/train | █▅▄▃▃▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▅▄▃▃▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 92.965 |
Accuracy/val | 92.87 |
Loss/train | 0.00135 |
Loss/val | 0.00138 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_030146-agga0njv/logs
wandb: Agent Starting Run: tjhkbl9x with config:
wandb: batch_size: 32
wandb: epochs: 10
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_030252-tjhkbl9x
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0072. Train Acc: 89.4800, Test loss: 0.0072. Test Acc: 89.7000. Time/epoch: 5.2330
EPOCH 10. Progress: 100.0%.
Train loss: 0.0038. Train Acc: 95.0225, Test loss: 0.0043. Test Acc: 94.7500. Time/epoch: 5.1294
Run history:
Accuracy/train | ▁▅▆▆▆▇▅█▇█▆ |
Accuracy/val | ▁▅▆▆▆▇▅█▇▇▆ |
Loss/train | █▄▄▃▃▂▅▁▂▁▃ |
Loss/val | █▄▄▃▃▂▅▁▂▁▃ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 95.0225 |
Accuracy/val | 94.75 |
Loss/train | 0.00385 |
Loss/val | 0.00431 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_030252-tjhkbl9x/logs
wandb: Agent Starting Run: simxgk4b with config:
wandb: batch_size: 32
wandb: epochs: 20
wandb: learning_rate: 0.01
wandb: optimizer: rmsprop
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_030403-simxgk4b
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0481. Train Acc: 36.8250, Test loss: 0.0480. Test Acc: 37.5400. Time/epoch: 4.9203
EPOCH 10. Progress: 50.0%.
Train loss: 0.0482. Train Acc: 36.8250, Test loss: 0.0481. Test Acc: 37.5400. Time/epoch: 4.8459
EPOCH 20. Progress: 100.0%.
Train loss: 0.0481. Train Acc: 36.8250, Test loss: 0.0480. Test Acc: 37.5400. Time/epoch: 4.8674
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | ▁▁▄▄▄▃▄▇▄▄▆▃▂▅▂█▃▃▃▄▂ |
Loss/val | ▂▁▄▅▅▂▃█▃▂▇▂▃▅▃█▂▅▅▂▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.04808 |
Loss/val | 0.04796 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_030403-simxgk4b/logs
wandb: Agent Starting Run: bv8vyks7 with config:
wandb: batch_size: 32
wandb: epochs: 10
wandb: learning_rate: 1e-05
wandb: optimizer: sgd
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_030600-bv8vyks7
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0106. Train Acc: 87.1825, Test loss: 0.0107. Test Acc: 87.0900. Time/epoch: 4.7402
EPOCH 10. Progress: 100.0%.
Train loss: 0.0047. Train Acc: 94.4275, Test loss: 0.0049. Test Acc: 94.4800. Time/epoch: 4.7193
Run history:
Accuracy/train | ▁▅▆▆▇▇▇▇█▇█ |
Accuracy/val | ▁▅▆▆▇▇▇▇█▇█ |
Loss/train | █▄▃▂▂▂▂▁▁▂▁ |
Loss/val | █▄▃▃▂▂▂▁▁▂▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 94.4275 |
Accuracy/val | 94.48 |
Loss/train | 0.00474 |
Loss/val | 0.00494 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_030600-bv8vyks7/logs
wandb: Agent Starting Run: uiatywb3 with config:
wandb: batch_size: 128
wandb: epochs: 50
wandb: learning_rate: 0.0003
wandb: optimizer: rmsprop
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_030704-uiatywb3
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0031. Train Acc: 82.7000, Test loss: 0.0031. Test Acc: 82.7900. Time/epoch: 2.2303
EPOCH 10. Progress: 20.0%.
Train loss: 0.0011. Train Acc: 93.6525, Test loss: 0.0011. Test Acc: 93.5700. Time/epoch: 2.3759
EPOCH 20. Progress: 40.0%.
Train loss: 0.0006. Train Acc: 96.8750, Test loss: 0.0007. Test Acc: 96.6500. Time/epoch: 2.3505
EPOCH 30. Progress: 60.0%.
Train loss: 0.0007. Train Acc: 96.8975, Test loss: 0.0007. Test Acc: 96.6100. Time/epoch: 2.3367
EPOCH 40. Progress: 80.0%.
Train loss: 0.0014. Train Acc: 93.4575, Test loss: 0.0015. Test Acc: 93.1800. Time/epoch: 2.2386
EPOCH 50. Progress: 100.0%.
Train loss: 0.0008. Train Acc: 96.0250, Test loss: 0.0008. Test Acc: 95.7100. Time/epoch: 2.2163
Run history:
Accuracy/train | ▁▅▄▆▅▅▆▇▆▇▇▇▇█▇▇▇▇▇█▄▇▇█▇██▅▅█▇▆█▇▆████▇ |
Accuracy/val | ▁▆▄▆▅▅▆▇▆▇▇▇▇██▇█▇▇█▄▇▇████▅▅█▇▇█▇▆████▇ |
Loss/train | █▃▅▃▄▅▃▂▃▂▂▂▃▂▂▂▂▂▂▂▅▂▂▁▂▁▁▅▅▂▂▃▁▂▃▁▂▁▁▂ |
Loss/val | █▃▅▃▄▄▃▂▃▂▂▂▂▁▁▂▁▂▂▁▅▂▂▁▂▁▁▅▄▁▂▃▁▂▃▁▂▁▁▂ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 96.025 |
Accuracy/val | 95.71 |
Loss/train | 0.00076 |
Loss/val | 0.00084 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_030704-uiatywb3/logs
wandb: Agent Starting Run: zovc4bqy with config:
wandb: batch_size: 64
wandb: epochs: 20
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_030915-zovc4bqy
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0035. Train Acc: 89.5725, Test loss: 0.0036. Test Acc: 89.5100. Time/epoch: 3.3588
EPOCH 10. Progress: 50.0%.
Train loss: 0.0017. Train Acc: 95.7350, Test loss: 0.0019. Test Acc: 95.2800. Time/epoch: 3.1717
EPOCH 20. Progress: 100.0%.
Train loss: 0.0009. Train Acc: 97.8425, Test loss: 0.0014. Test Acc: 96.8700. Time/epoch: 3.1696
Run history:
Accuracy/train | ▁▄▅▅▅▆▁▆▇▇▆▇▇▆▇▇▅▇███ |
Accuracy/val | ▁▅▅▅▆▆▁▇▇█▆▇▇▆█▇▅▇███ |
Loss/train | █▅▄▄▄▃█▃▂▂▃▃▃▃▂▂▇▂▂▁▁ |
Loss/val | █▄▃▃▃▂█▂▁▁▃▂▃▃▂▂█▂▂▁▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 97.8425 |
Accuracy/val | 96.87 |
Loss/train | 0.00089 |
Loss/val | 0.00137 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_030915-zovc4bqy/logs
wandb: Agent Starting Run: z5r2tlkg with config:
wandb: batch_size: 128
wandb: epochs: 50
wandb: learning_rate: 1e-05
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_031041-z5r2tlkg
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0026. Train Acc: 89.0050, Test loss: 0.0026. Test Acc: 88.8600. Time/epoch: 2.3906
EPOCH 10. Progress: 20.0%.
Train loss: 0.0011. Train Acc: 94.3475, Test loss: 0.0012. Test Acc: 94.2700. Time/epoch: 2.2251
EPOCH 20. Progress: 40.0%.
Train loss: 0.0010. Train Acc: 95.2050, Test loss: 0.0011. Test Acc: 94.9500. Time/epoch: 2.2297
EPOCH 30. Progress: 60.0%.
Train loss: 0.0009. Train Acc: 95.3600, Test loss: 0.0010. Test Acc: 95.2900. Time/epoch: 2.3617
EPOCH 40. Progress: 80.0%.
Train loss: 0.0009. Train Acc: 95.7775, Test loss: 0.0009. Test Acc: 95.5500. Time/epoch: 2.3671
EPOCH 50. Progress: 100.0%.
Train loss: 0.0009. Train Acc: 95.9625, Test loss: 0.0009. Test Acc: 95.7900. Time/epoch: 2.2033
Run history:
Accuracy/train | ▁▃▄▅▅▆▅▆▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇█▇██████████▇████ |
Accuracy/val | ▁▄▅▅▅▆▅▇▆▆▇▇▇▇▇▇▇▇▇▇▇▇█▇▇██▇▇█████▇█▇███ |
Loss/train | █▅▄▃▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▁▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▅▄▄▃▂▃▂▂▂▂▂▂▂▂▂▂▁▂▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 95.9625 |
Accuracy/val | 95.79 |
Loss/train | 0.00088 |
Loss/val | 0.00092 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_031041-z5r2tlkg/logs
wandb: Agent Starting Run: 9ogv0d1d with config:
wandb: batch_size: 128
wandb: epochs: 50
wandb: learning_rate: 0.0003
wandb: optimizer: sgd
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_031254-9ogv0d1d
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0013. Train Acc: 93.2350, Test loss: 0.0014. Test Acc: 93.1000. Time/epoch: 2.3610
EPOCH 10. Progress: 20.0%.
Train loss: 0.0009. Train Acc: 95.3750, Test loss: 0.0010. Test Acc: 95.3200. Time/epoch: 2.3356
EPOCH 20. Progress: 40.0%.
Train loss: 0.0006. Train Acc: 97.2500, Test loss: 0.0006. Test Acc: 97.0500. Time/epoch: 2.1837
EPOCH 30. Progress: 60.0%.
Train loss: 0.0006. Train Acc: 96.9925, Test loss: 0.0007. Test Acc: 96.6600. Time/epoch: 2.3134
EPOCH 40. Progress: 80.0%.
Train loss: 0.0006. Train Acc: 96.8000, Test loss: 0.0007. Test Acc: 96.4400. Time/epoch: 2.3188
EPOCH 50. Progress: 100.0%.
Train loss: 0.0005. Train Acc: 97.5625, Test loss: 0.0006. Test Acc: 97.2300. Time/epoch: 2.3414
Run history:
Accuracy/train | ▆▁▆▇▅▇▇▇▇▇▇▇▇▇▇▇█▇▇▇██▇██████▇██████████ |
Accuracy/val | ▆▁▆▇▅▇▇▇▇▇▇▇▇▇▇██▇▇▇█████████▇██████████ |
Loss/train | ▃█▂▂▃▂▂▂▂▂▂▂▂▁▁▁▁▂▂▂▁▁▁▁▁▁▁▁▁▂▁▁▁▁▁▁▁▁▁▁ |
Loss/val | ▃█▂▂▃▂▂▂▂▂▂▂▁▁▁▁▁▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 97.5625 |
Accuracy/val | 97.23 |
Loss/train | 0.0005 |
Loss/val | 0.00062 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_031254-9ogv0d1d/logs
wandb: Agent Starting Run: vhvf0jcd with config:
wandb: batch_size: 128
wandb: epochs: 10
wandb: learning_rate: 0.01
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_031505-vhvf0jcd
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0047. Train Acc: 77.7925, Test loss: 0.0046. Test Acc: 78.7000. Time/epoch: 2.4174
EPOCH 10. Progress: 100.0%.
Train loss: 0.0120. Train Acc: 36.8250, Test loss: 0.0121. Test Acc: 37.5400. Time/epoch: 2.3413
Run history:
Accuracy/train | █▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | █▁▁▁▁▁▁▁▁▁▁ |
Loss/train | ▁██████████ |
Loss/val | ▁██████████ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.01203 |
Loss/val | 0.01214 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_031505-vhvf0jcd/logs
wandb: Agent Starting Run: 5jzm4hd6 with config:
wandb: batch_size: 32
wandb: epochs: 20
wandb: learning_rate: 0.001
wandb: optimizer: rmsprop
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_031546-5jzm4hd6
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0195. Train Acc: 78.7525, Test loss: 0.0194. Test Acc: 79.0700. Time/epoch: 4.9323
EPOCH 10. Progress: 50.0%.
Train loss: 0.0050. Train Acc: 94.3575, Test loss: 0.0053. Test Acc: 93.9700. Time/epoch: 4.8345
EPOCH 20. Progress: 100.0%.
Train loss: 0.0047. Train Acc: 94.2750, Test loss: 0.0050. Test Acc: 93.8500. Time/epoch: 4.8189
Run history:
Accuracy/train | ▄▅▆▇▇▇██████▁▇█▇█████ |
Accuracy/val | ▄▅▆▇▇▇██████▁▇█▇█████ |
Loss/train | ▄▃▂▂▁▁▁▁▁▁▁▁█▁▁▁▁▁▁▁▁ |
Loss/val | ▄▃▂▂▁▁▁▁▁▁▁▁█▁▁▁▁▁▁▁▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 94.275 |
Accuracy/val | 93.85 |
Loss/train | 0.0047 |
Loss/val | 0.005 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_031546-5jzm4hd6/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: x5wzmb9m with config:
wandb: batch_size: 32
wandb: epochs: 20
wandb: learning_rate: 1e-05
wandb: optimizer: sgd
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_031748-x5wzmb9m
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0136. Train Acc: 81.9050, Test loss: 0.0138. Test Acc: 81.6700. Time/epoch: 4.7866
EPOCH 10. Progress: 50.0%.
Train loss: 0.0047. Train Acc: 93.9850, Test loss: 0.0049. Test Acc: 94.1600. Time/epoch: 4.7301
EPOCH 20. Progress: 100.0%.
Train loss: 0.0041. Train Acc: 94.7500, Test loss: 0.0042. Test Acc: 95.0900. Time/epoch: 4.7042
Run history:
Accuracy/train | ▁▂▃▄▅▆▇▆▇▇███████▇███ |
Accuracy/val | ▁▂▃▄▅▆▇▆▇▇███████▇███ |
Loss/train | █▆▆▄▄▃▂▂▂▂▁▁▁▁▁▁▁▂▁▁▁ |
Loss/val | █▆▆▅▄▃▂▂▂▂▁▂▁▁▁▁▁▂▁▁▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 94.75 |
Accuracy/val | 95.09 |
Loss/train | 0.00407 |
Loss/val | 0.00423 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_031748-x5wzmb9m/logs
wandb: Agent Starting Run: jd4zr49s with config:
wandb: batch_size: 32
wandb: epochs: 20
wandb: learning_rate: 3e-05
wandb: optimizer: adam
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_031940-jd4zr49s
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0078. Train Acc: 89.4400, Test loss: 0.0081. Test Acc: 89.3800. Time/epoch: 5.2359
EPOCH 10. Progress: 50.0%.
Train loss: 0.0036. Train Acc: 95.1000, Test loss: 0.0038. Test Acc: 95.2400. Time/epoch: 5.1533
EPOCH 20. Progress: 100.0%.
Train loss: 0.0028. Train Acc: 96.6600, Test loss: 0.0032. Test Acc: 96.2400. Time/epoch: 5.1585
Run history:
Accuracy/train | ▁▂▃▂▆▆▆▆▆▆▆▇▆▆▇▇█▇█▇█ |
Accuracy/val | ▁▂▄▂▆▆▆▇▇▇▇▇▆▇▇██▇█▇█ |
Loss/train | █▆▅▇▃▃▃▂▂▂▂▂▃▂▂▁▁▂▁▂▁ |
Loss/val | █▆▅▆▃▃▃▂▂▂▂▂▃▂▂▁▁▁▁▂▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 96.66 |
Accuracy/val | 96.24 |
Loss/train | 0.00278 |
Loss/val | 0.00316 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_031940-jd4zr49s/logs
wandb: Agent Starting Run: p9k6cxx7 with config:
wandb: batch_size: 128
wandb: epochs: 20
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_032143-p9k6cxx7
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0018. Train Acc: 88.2000, Test loss: 0.0018. Test Acc: 88.5900. Time/epoch: 2.3159
EPOCH 10. Progress: 50.0%.
Train loss: 0.0007. Train Acc: 96.4925, Test loss: 0.0008. Test Acc: 96.2200. Time/epoch: 2.4209
EPOCH 20. Progress: 100.0%.
Train loss: 0.0005. Train Acc: 97.6750, Test loss: 0.0006. Test Acc: 97.1800. Time/epoch: 2.4273
Run history:
Accuracy/train | ▁▅▆▇▆▆▇▇▇▇▇▇█▇▇██████ |
Accuracy/val | ▁▅▇▇▆▆▇▇▇▇▇▇█████████ |
Loss/train | █▅▄▃▄▄▃▂▃▂▂▃▁▂▁▁▁▁▁▁▁ |
Loss/val | █▄▃▃▄▄▂▂▃▂▂▂▁▂▁▁▁▁▁▂▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 97.675 |
Accuracy/val | 97.18 |
Loss/train | 0.00048 |
Loss/val | 0.00061 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_032143-p9k6cxx7/logs
wandb: Agent Starting Run: 9zx8scos with config:
wandb: batch_size: 64
wandb: epochs: 50
wandb: learning_rate: 0.0001
wandb: optimizer: adam
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_032244-9zx8scos
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0028. Train Acc: 92.2725, Test loss: 0.0029. Test Acc: 92.2900. Time/epoch: 3.3926
EPOCH 10. Progress: 20.0%.
Train loss: 0.0018. Train Acc: 95.2300, Test loss: 0.0019. Test Acc: 95.0900. Time/epoch: 3.3430
EPOCH 20. Progress: 40.0%.
Train loss: 0.0011. Train Acc: 97.3800, Test loss: 0.0013. Test Acc: 96.9100. Time/epoch: 3.3288
EPOCH 30. Progress: 60.0%.
Train loss: 0.0009. Train Acc: 97.5450, Test loss: 0.0013. Test Acc: 97.0000. Time/epoch: 3.1773
EPOCH 40. Progress: 80.0%.
Train loss: 0.0008. Train Acc: 98.1075, Test loss: 0.0012. Test Acc: 97.3100. Time/epoch: 3.2019
EPOCH 50. Progress: 100.0%.
Train loss: 0.0005. Train Acc: 98.7525, Test loss: 0.0012. Test Acc: 97.6100. Time/epoch: 3.3130
Run history:
Accuracy/train | ▁▃▄▄▅▄▅▄▄▆▆▆▆▆▆▆▆▇▇▇▆▇▇▇▆▇▇▇▇▇▇▇▇█▆█████ |
Accuracy/val | ▁▃▄▅▆▄▅▅▄▆▇▆▆▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇█▆█████ |
Loss/train | █▆▆▅▄▅▅▅▅▃▃▄▃▃▃▃▃▃▂▂▃▂▂▂▂▂▂▂▂▂▂▂▂▁▃▁▁▁▁▁ |
Loss/val | █▆▅▅▃▅▄▄▄▃▂▃▂▂▃▂▂▂▂▂▂▂▂▁▂▂▁▁▁▂▂▂▂▁▃▁▁▁▁▂ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.7525 |
Accuracy/val | 97.61 |
Loss/train | 0.00054 |
Loss/val | 0.0012 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_032244-9zx8scos/logs
wandb: Agent Starting Run: zyau70g3 with config:
wandb: batch_size: 64
wandb: epochs: 20
wandb: learning_rate: 0.01
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_032547-zyau70g3
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0241. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 3.0341
EPOCH 10. Progress: 50.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0240. Test Acc: 37.5400. Time/epoch: 3.0451
EPOCH 20. Progress: 100.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 3.0080
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | ████▁████████████████ |
Loss/val | ████▁████████████████ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.02402 |
Loss/val | 0.02406 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_032547-zyau70g3/logs
wandb: Agent Starting Run: 2luvylas with config:
wandb: batch_size: 64
wandb: epochs: 10
wandb: learning_rate: 3e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_032703-2luvylas
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0042. Train Acc: 89.3825, Test loss: 0.0043. Test Acc: 89.0800. Time/epoch: 3.3587
EPOCH 10. Progress: 100.0%.
Train loss: 0.0019. Train Acc: 95.4400, Test loss: 0.0020. Test Acc: 95.3200. Time/epoch: 3.1627
Run history:
Accuracy/train | ▁▄▅▅▇▇▆▆▆▇█ |
Accuracy/val | ▁▄▅▆▇▇▆▇▆▇█ |
Loss/train | █▅▄▃▂▂▃▂▂▁▁ |
Loss/val | █▅▄▃▂▂▃▂▂▁▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 95.44 |
Accuracy/val | 95.32 |
Loss/train | 0.00189 |
Loss/val | 0.00202 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_032703-2luvylas/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: tvzq27e3 with config:
wandb: batch_size: 64
wandb: epochs: 10
wandb: learning_rate: 1e-05
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_032800-tvzq27e3
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0061. Train Acc: 86.3300, Test loss: 0.0062. Test Acc: 86.3900. Time/epoch: 3.2002
EPOCH 10. Progress: 100.0%.
Train loss: 0.0026. Train Acc: 93.7600, Test loss: 0.0027. Test Acc: 93.9700. Time/epoch: 3.1527
Run history:
Accuracy/train | ▁▃▄▅▅▆▆▆▇██ |
Accuracy/val | ▁▃▄▅▅▆▆▆▇▇█ |
Loss/train | █▅▄▃▃▂▂▂▂▁▁ |
Loss/val | █▅▄▃▃▂▂▂▂▁▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 93.76 |
Accuracy/val | 93.97 |
Loss/train | 0.00261 |
Loss/val | 0.00265 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_032800-tvzq27e3/logs
wandb: Agent Starting Run: p67cfog1 with config:
wandb: batch_size: 64
wandb: epochs: 10
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_032846-p67cfog1
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0026. Train Acc: 92.8100, Test loss: 0.0027. Test Acc: 92.8000. Time/epoch: 3.3845
EPOCH 10. Progress: 100.0%.
Train loss: 0.0019. Train Acc: 94.9050, Test loss: 0.0021. Test Acc: 94.7100. Time/epoch: 3.3136
Run history:
Accuracy/train | ▁▅▆▅▅█▇▆▇█▄ |
Accuracy/val | ▁▅▆▆▅█▇▆▇█▄ |
Loss/train | █▄▄▄▄▁▂▃▂▁▅ |
Loss/val | █▃▃▄▃▁▁▃▂▁▅ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 94.905 |
Accuracy/val | 94.71 |
Loss/train | 0.00194 |
Loss/val | 0.00209 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_032846-p67cfog1/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: dvziqyxq with config:
wandb: batch_size: 32
wandb: epochs: 50
wandb: learning_rate: 0.0001
wandb: optimizer: rmsprop
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_032944-dvziqyxq
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0057. Train Acc: 92.3600, Test loss: 0.0058. Test Acc: 92.3700. Time/epoch: 4.8779
EPOCH 10. Progress: 20.0%.
Train loss: 0.0031. Train Acc: 95.9550, Test loss: 0.0034. Test Acc: 95.5800. Time/epoch: 4.8753
EPOCH 20. Progress: 40.0%.
Train loss: 0.0022. Train Acc: 97.1100, Test loss: 0.0026. Test Acc: 96.7300. Time/epoch: 4.8943
EPOCH 30. Progress: 60.0%.
Train loss: 0.0017. Train Acc: 98.1425, Test loss: 0.0021. Test Acc: 97.7400. Time/epoch: 4.7056
EPOCH 40. Progress: 80.0%.
Train loss: 0.0033. Train Acc: 96.1825, Test loss: 0.0037. Test Acc: 95.9100. Time/epoch: 4.6866
EPOCH 50. Progress: 100.0%.
Train loss: 0.0013. Train Acc: 98.5625, Test loss: 0.0017. Test Acc: 98.2800. Time/epoch: 4.8479
Run history:
Accuracy/train | ▄▆▆▁▇▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇█▇███▇██▇██▇█▇██████ |
Accuracy/val | ▅▆▆▁▇▇▇▆▆▇▇▇▇▇▇▇▇▇▇▇█▇███▇██▇██▇█▇██████ |
Loss/train | ▄▃▃█▂▂▂▃▂▂▂▂▂▂▂▁▂▂▂▂▁▂▁▁▁▂▁▁▂▁▁▁▁▂▁▁▁▁▁▁ |
Loss/val | ▄▃▃█▂▂▂▂▂▂▂▂▁▂▂▁▂▂▂▂▁▂▁▁▁▁▁▁▂▁▁▁▁▂▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.5625 |
Accuracy/val | 98.28 |
Loss/train | 0.00128 |
Loss/val | 0.00174 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_032944-dvziqyxq/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: cb4b5suj with config:
wandb: batch_size: 128
wandb: epochs: 50
wandb: learning_rate: 0.0001
wandb: optimizer: rmsprop
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_033411-cb4b5suj
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0020. Train Acc: 89.2950, Test loss: 0.0021. Test Acc: 89.4500. Time/epoch: 2.2336
EPOCH 10. Progress: 20.0%.
Train loss: 0.0017. Train Acc: 90.8825, Test loss: 0.0018. Test Acc: 90.8000. Time/epoch: 2.3476
EPOCH 20. Progress: 40.0%.
Train loss: 0.0006. Train Acc: 96.9800, Test loss: 0.0007. Test Acc: 96.8900. Time/epoch: 2.3485
EPOCH 30. Progress: 60.0%.
Train loss: 0.0005. Train Acc: 97.8550, Test loss: 0.0005. Test Acc: 97.7900. Time/epoch: 2.3385
EPOCH 40. Progress: 80.0%.
Train loss: 0.0004. Train Acc: 98.0175, Test loss: 0.0005. Test Acc: 97.7300. Time/epoch: 2.2109
EPOCH 50. Progress: 100.0%.
Train loss: 0.0006. Train Acc: 97.0625, Test loss: 0.0007. Test Acc: 96.8300. Time/epoch: 2.3406
Run history:
Accuracy/train | ▁▃▄▅▆▆▆▄▂▄▆▇▇▇▆▇▇▇█▇▇█▇▇███▇▅█▇██▇▆██▇▇▇ |
Accuracy/val | ▁▃▄▅▆▆▆▄▂▄▇▇▇▇▆▇▇██▇▇█▇▇███▇▅█▇███▆██▇▇▇ |
Loss/train | █▆▅▄▃▃▃▅▇▅▃▂▂▂▃▂▂▂▁▂▂▂▂▂▁▁▁▂▄▁▂▁▁▂▃▁▁▂▂▂ |
Loss/val | █▆▅▄▃▃▃▅▇▅▂▂▂▂▂▂▂▁▁▂▂▁▁▂▁▁▁▂▄▁▂▁▁▁▃▁▁▂▂▂ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 97.0625 |
Accuracy/val | 96.83 |
Loss/train | 0.00061 |
Loss/val | 0.00069 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_033411-cb4b5suj/logs
wandb: Agent Starting Run: 9vuy6t60 with config:
wandb: batch_size: 128
wandb: epochs: 50
wandb: learning_rate: 0.0003
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_033622-9vuy6t60
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0019. Train Acc: 89.9600, Test loss: 0.0020. Test Acc: 89.9600. Time/epoch: 2.2468
EPOCH 10. Progress: 20.0%.
Train loss: 0.0006. Train Acc: 96.7925, Test loss: 0.0007. Test Acc: 96.6300. Time/epoch: 2.2197
EPOCH 20. Progress: 40.0%.
Train loss: 0.0006. Train Acc: 96.9175, Test loss: 0.0007. Test Acc: 96.5100. Time/epoch: 2.3593
EPOCH 30. Progress: 60.0%.
Train loss: 0.0004. Train Acc: 98.1800, Test loss: 0.0005. Test Acc: 97.5100. Time/epoch: 2.3331
EPOCH 40. Progress: 80.0%.
Train loss: 0.0004. Train Acc: 97.9050, Test loss: 0.0006. Test Acc: 97.0400. Time/epoch: 2.3245
EPOCH 50. Progress: 100.0%.
Train loss: 0.0002. Train Acc: 98.9500, Test loss: 0.0005. Test Acc: 97.9400. Time/epoch: 2.2019
Run history:
Accuracy/train | ▃▄▅▁▆▆▃▇▇▇▆▆▆▅▇▇▇▇▇▇▇▇▇▇██▇▇▇▆▇▇▇█▇█████ |
Accuracy/val | ▃▄▅▁▇▆▃▇▇▇▇▆▇▅▇▇▇▇▇▇▇▇█▇██▇▇█▆▇▇▇█▇█████ |
Loss/train | ▆▄▄█▃▃▇▂▂▂▃▃▃▄▂▂▂▂▂▂▂▂▁▂▁▁▂▂▂▄▂▂▂▁▂▁▁▁▁▁ |
Loss/val | ▅▄▃█▂▃▆▂▂▂▂▂▂▃▂▂▂▂▂▂▂▂▁▁▁▁▁▂▁▄▂▂▂▁▂▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.95 |
Accuracy/val | 97.94 |
Loss/train | 0.00024 |
Loss/val | 0.0005 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_033622-9vuy6t60/logs
wandb: Agent Starting Run: huppqm1m with config:
wandb: batch_size: 64
wandb: epochs: 20
wandb: learning_rate: 0.0003
wandb: optimizer: sgd
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_033833-huppqm1m
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0040. Train Acc: 88.9275, Test loss: 0.0041. Test Acc: 88.8800. Time/epoch: 3.1435
EPOCH 10. Progress: 50.0%.
Train loss: 0.0019. Train Acc: 95.1400, Test loss: 0.0020. Test Acc: 95.1000. Time/epoch: 2.9824
EPOCH 20. Progress: 100.0%.
Train loss: 0.0016. Train Acc: 95.7625, Test loss: 0.0017. Test Acc: 95.8300. Time/epoch: 2.9552
Run history:
Accuracy/train | ▁▆▄▆▇▄▇██▇▇█▇████▇█▇█ |
Accuracy/val | ▁▆▄▆▇▄███▇▇▇▇████▇█▇█ |
Loss/train | █▃▅▃▂▆▁▁▁▂▂▁▁▁▁▁▁▂▁▂▁ |
Loss/val | █▃▅▃▂▆▁▁▁▂▂▁▁▁▁▁▁▂▁▂▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 95.7625 |
Accuracy/val | 95.83 |
Loss/train | 0.00164 |
Loss/val | 0.00169 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_033833-huppqm1m/logs
wandb: Agent Starting Run: jpoemwhv with config:
wandb: batch_size: 128
wandb: epochs: 10
wandb: learning_rate: 0.0003
wandb: optimizer: sgd
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_033950-jpoemwhv
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0025. Train Acc: 85.6625, Test loss: 0.0026. Test Acc: 85.9400. Time/epoch: 2.3635
EPOCH 10. Progress: 100.0%.
Train loss: 0.0008. Train Acc: 95.6950, Test loss: 0.0009. Test Acc: 95.4900. Time/epoch: 2.1930
Run history:
Accuracy/train | ▁▆▆▇▇▇█▇▇██ |
Accuracy/val | ▁▆▅▇▇▇█▇▇██ |
Loss/train | █▃▃▂▂▂▁▂▂▁▁ |
Loss/val | █▃▃▂▂▂▁▂▂▁▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 95.695 |
Accuracy/val | 95.49 |
Loss/train | 0.00085 |
Loss/val | 0.00091 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_033950-jpoemwhv/logs
wandb: Agent Starting Run: m2mggbud with config:
wandb: batch_size: 64
wandb: epochs: 10
wandb: learning_rate: 0.0001
wandb: optimizer: rmsprop
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_034030-m2mggbud
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0044. Train Acc: 87.3125, Test loss: 0.0044. Test Acc: 87.4500. Time/epoch: 3.1746
EPOCH 10. Progress: 100.0%.
Train loss: 0.0019. Train Acc: 95.3650, Test loss: 0.0019. Test Acc: 95.1000. Time/epoch: 3.1354
Run history:
Accuracy/train | ▁▆▆▇▇▇████▇ |
Accuracy/val | ▁▆▇▇▇▇▇███▇ |
Loss/train | █▄▃▂▂▂▂▁▁▁▂ |
Loss/val | █▃▃▂▂▂▂▁▁▁▂ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 95.365 |
Accuracy/val | 95.1 |
Loss/train | 0.00186 |
Loss/val | 0.00194 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_034030-m2mggbud/logs
wandb: Agent Starting Run: 39ddzhco with config:
wandb: batch_size: 64
wandb: epochs: 20
wandb: learning_rate: 1e-05
wandb: optimizer: sgd
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_034121-39ddzhco
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0085. Train Acc: 79.1825, Test loss: 0.0087. Test Acc: 78.7600. Time/epoch: 3.1127
EPOCH 10. Progress: 50.0%.
Train loss: 0.0029. Train Acc: 92.4450, Test loss: 0.0031. Test Acc: 92.1300. Time/epoch: 3.0869
EPOCH 20. Progress: 100.0%.
Train loss: 0.0025. Train Acc: 93.7350, Test loss: 0.0027. Test Acc: 93.3700. Time/epoch: 3.0732
Run history:
Accuracy/train | ▁▃▅▆▆▆▇▇▇▇▇▇▇▇▇██████ |
Accuracy/val | ▁▃▅▆▆▆▇▇▇▇▇▇▇████████ |
Loss/train | █▅▄▃▃▂▂▂▂▂▂▁▂▁▁▁▁▁▁▁▁ |
Loss/val | █▅▄▃▃▂▂▂▂▂▂▁▂▁▁▁▁▁▁▁▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 93.735 |
Accuracy/val | 93.37 |
Loss/train | 0.0025 |
Loss/val | 0.00266 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_034121-39ddzhco/logs
wandb: Agent Starting Run: s9ih4ev0 with config:
wandb: batch_size: 64
wandb: epochs: 50
wandb: learning_rate: 0.001
wandb: optimizer: adam
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_034237-s9ih4ev0
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0038. Train Acc: 91.0400, Test loss: 0.0039. Test Acc: 90.8100. Time/epoch: 3.3814
EPOCH 10. Progress: 20.0%.
Train loss: 0.0024. Train Acc: 93.5725, Test loss: 0.0026. Test Acc: 93.3100. Time/epoch: 3.2949
EPOCH 20. Progress: 40.0%.
Train loss: 0.0009. Train Acc: 98.0000, Test loss: 0.0013. Test Acc: 97.1200. Time/epoch: 3.2832
EPOCH 30. Progress: 60.0%.
Train loss: 0.0010. Train Acc: 97.7750, Test loss: 0.0016. Test Acc: 96.7800. Time/epoch: 3.1826
EPOCH 40. Progress: 80.0%.
Train loss: 0.0006. Train Acc: 98.6025, Test loss: 0.0017. Test Acc: 96.9600. Time/epoch: 3.2852
EPOCH 50. Progress: 100.0%.
Train loss: 0.0013. Train Acc: 96.8175, Test loss: 0.0028. Test Acc: 95.3000. Time/epoch: 3.3088
Run history:
Accuracy/train | ▁▅▂▆▂▆▅▆▃▅▆▆▆▇▆▇▇▇▇▆▆▇▇▇▇▇▇▇█▇▇██▇██▇██▆ |
Accuracy/val | ▁▆▃▇▂▇▆▇▄▆▇▆▆█▇▇█▇▇▆▆██▇█▇▇▇██▇█████▇██▆ |
Loss/train | █▄▆▃█▃▄▃▅▄▃▃▃▂▃▂▂▂▂▃▃▂▂▃▂▂▂▂▁▂▂▁▁▁▁▁▂▁▁▃ |
Loss/val | ▇▂▅▂█▂▃▂▄▃▂▂▂▂▃▂▁▂▂▃▂▁▁▄▂▂▂▃▂▃▂▁▂▂▃▂▃▂▂▄ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 96.8175 |
Accuracy/val | 95.3 |
Loss/train | 0.0013 |
Loss/val | 0.00278 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_034237-s9ih4ev0/logs
wandb: Agent Starting Run: mfega71i with config:
wandb: batch_size: 128
wandb: epochs: 20
wandb: learning_rate: 0.01
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_034540-mfega71i
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0121. Train Acc: 37.4350, Test loss: 0.0122. Test Acc: 38.0400. Time/epoch: 2.2479
EPOCH 10. Progress: 50.0%.
Train loss: 0.0122. Train Acc: 36.8250, Test loss: 0.0123. Test Acc: 37.5400. Time/epoch: 2.1978
EPOCH 20. Progress: 100.0%.
Train loss: 0.0122. Train Acc: 36.8250, Test loss: 0.0122. Test Acc: 37.5400. Time/epoch: 2.3595
Run history:
Accuracy/train | ▆▅█▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▅▅█▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | ▁▃▁▆▅▆▆▇▇██▆▆▆▆▇▇█▆█▇ |
Loss/val | ▁▃▁▆▆▇▅▆▅▇▇▆▅▅▆▇▆█▅█▇ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.01216 |
Loss/val | 0.01224 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_034540-mfega71i/logs
wandb: Agent Starting Run: sagxbth3 with config:
wandb: batch_size: 128
wandb: epochs: 10
wandb: learning_rate: 0.01
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_034642-sagxbth3
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0120. Train Acc: 36.8250, Test loss: 0.0121. Test Acc: 37.5400. Time/epoch: 2.2179
EPOCH 10. Progress: 100.0%.
Train loss: 0.0120. Train Acc: 36.8250, Test loss: 0.0121. Test Acc: 37.5400. Time/epoch: 2.3562
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | ▄▁▄█▄▂▃▄▂▃▂ |
Loss/val | ▄▃▅█▆▃▃▆▄▂▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.01203 |
Loss/val | 0.01209 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_034642-sagxbth3/logs
wandb: Agent Starting Run: eko31h9c with config:
wandb: batch_size: 32
wandb: epochs: 20
wandb: learning_rate: 0.01
wandb: optimizer: adam
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_034723-eko31h9c
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0481. Train Acc: 36.8250, Test loss: 0.0480. Test Acc: 37.5400. Time/epoch: 5.0831
EPOCH 10. Progress: 50.0%.
Train loss: 0.0481. Train Acc: 36.8250, Test loss: 0.0480. Test Acc: 37.5400. Time/epoch: 4.9927
EPOCH 20. Progress: 100.0%.
Train loss: 0.0481. Train Acc: 36.8250, Test loss: 0.0480. Test Acc: 37.5400. Time/epoch: 5.1511
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | ▂▂▄▄▄▁▅▁▁▂▃▂▂▁█▃▄▁▂▂▂ |
Loss/val | ▂▂▄▃▃▁▄▁▂▃▂▂▂▁█▃▅▂▂▃▃ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.04805 |
Loss/val | 0.04797 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_034723-eko31h9c/logs
wandb: Agent Starting Run: rc4w0al7 with config:
wandb: batch_size: 32
wandb: epochs: 50
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_034925-rc4w0al7
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0059. Train Acc: 91.7375, Test loss: 0.0061. Test Acc: 91.7000. Time/epoch: 5.0144
EPOCH 10. Progress: 20.0%.
Train loss: 0.0025. Train Acc: 96.8450, Test loss: 0.0028. Test Acc: 96.5600. Time/epoch: 4.9937
EPOCH 20. Progress: 40.0%.
Train loss: 0.0015. Train Acc: 98.2525, Test loss: 0.0022. Test Acc: 97.6300. Time/epoch: 5.1812
EPOCH 30. Progress: 60.0%.
Train loss: 0.0027. Train Acc: 96.6925, Test loss: 0.0039. Test Acc: 96.0000. Time/epoch: 5.1661
EPOCH 40. Progress: 80.0%.
Train loss: 0.0015. Train Acc: 98.0425, Test loss: 0.0034. Test Acc: 96.6400. Time/epoch: 5.1761
EPOCH 50. Progress: 100.0%.
Train loss: 0.0009. Train Acc: 98.9125, Test loss: 0.0035. Test Acc: 97.4000. Time/epoch: 5.0519
Run history:
Accuracy/train | ▁▃▃▅▂▄▅▅▆▆▇▅▆▆▆▆▇▇▅▅▇▆▆▇▆▇▇▇█▆▇▇███▇████ |
Accuracy/val | ▁▄▃▆▂▅▆▆▆▇▇▅▇▇▇▆█▇▆▅▇▆▆█▆████▆█▇███▇▇██▇ |
Loss/train | █▆▆▅▇▅▄▄▃▃▃▄▃▃▃▄▂▂▄▄▂▃▄▂▄▂▂▂▂▃▁▂▁▁▁▂▁▁▁▁ |
Loss/val | █▅▅▃▇▄▃▃▂▂▁▃▂▂▂▃▁▁▄▄▂▃▄▁▄▂▂▁▁▅▁▂▂▂▂▃▃▁▂▃ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.9125 |
Accuracy/val | 97.4 |
Loss/train | 0.00089 |
Loss/val | 0.00354 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_034925-rc4w0al7/logs
wandb: Agent Starting Run: 3hue7myw with config:
wandb: batch_size: 128
wandb: epochs: 20
wandb: learning_rate: 0.0001
wandb: optimizer: adam
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_035401-3hue7myw
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0017. Train Acc: 90.8700, Test loss: 0.0018. Test Acc: 90.8500. Time/epoch: 2.4444
EPOCH 10. Progress: 50.0%.
Train loss: 0.0007. Train Acc: 96.5750, Test loss: 0.0008. Test Acc: 96.2600. Time/epoch: 2.4537
EPOCH 20. Progress: 100.0%.
Train loss: 0.0006. Train Acc: 97.2350, Test loss: 0.0007. Test Acc: 96.7600. Time/epoch: 2.3120
Run history:
Accuracy/train | ▁▅▅▆▆▇▆▆▆▇▇▇▇█▇████▇█ |
Accuracy/val | ▁▅▅▆▆▇▆▆▇▇▇▇██▇████▇█ |
Loss/train | █▅▄▄▃▂▃▃▃▂▂▂▂▁▂▁▁▁▁▁▁ |
Loss/val | █▅▄▄▃▂▃▃▃▂▂▂▁▁▂▁▁▁▁▂▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 97.235 |
Accuracy/val | 96.76 |
Loss/train | 0.00056 |
Loss/val | 0.00067 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_035401-3hue7myw/logs
wandb: Agent Starting Run: g2qv1hr9 with config:
wandb: batch_size: 128
wandb: epochs: 10
wandb: learning_rate: 0.01
wandb: optimizer: adam
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_035508-g2qv1hr9
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0121. Train Acc: 36.8250, Test loss: 0.0121. Test Acc: 37.5400. Time/epoch: 2.4737
EPOCH 10. Progress: 100.0%.
Train loss: 0.0120. Train Acc: 36.8250, Test loss: 0.0121. Test Acc: 37.5400. Time/epoch: 2.4183
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | █▄▅▂▁▃▂▂▅▁▁ |
Loss/val | █▃▆▃▃▂▆▁▃▃▂ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.01203 |
Loss/val | 0.0121 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_035508-g2qv1hr9/logs
wandb: Agent Starting Run: 14i7qqb3 with config:
wandb: batch_size: 32
wandb: epochs: 10
wandb: learning_rate: 0.0001
wandb: optimizer: sgd
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_035549-14i7qqb3
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0076. Train Acc: 89.9925, Test loss: 0.0079. Test Acc: 89.6700. Time/epoch: 4.7964
EPOCH 10. Progress: 100.0%.
Train loss: 0.0032. Train Acc: 96.0875, Test loss: 0.0036. Test Acc: 95.7100. Time/epoch: 4.7119
Run history:
Accuracy/train | ▁▄▇▇▇▆█▇▇▇█ |
Accuracy/val | ▁▅▇▇█▆█▇▇▇█ |
Loss/train | █▄▂▂▂▃▁▃▂▂▁ |
Loss/val | █▄▂▂▂▃▁▂▂▂▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 96.0875 |
Accuracy/val | 95.71 |
Loss/train | 0.00317 |
Loss/val | 0.00357 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_035549-14i7qqb3/logs
wandb: Agent Starting Run: ikirp9xn with config:
wandb: batch_size: 32
wandb: epochs: 20
wandb: learning_rate: 0.0001
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_035655-ikirp9xn
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0043. Train Acc: 94.4825, Test loss: 0.0045. Test Acc: 94.4700. Time/epoch: 4.9078
EPOCH 10. Progress: 50.0%.
Train loss: 0.0020. Train Acc: 97.6225, Test loss: 0.0024. Test Acc: 97.2900. Time/epoch: 4.8971
EPOCH 20. Progress: 100.0%.
Train loss: 0.0015. Train Acc: 98.1250, Test loss: 0.0021. Test Acc: 97.5600. Time/epoch: 4.8745
Run history:
Accuracy/train | ▂▃▂▁▄▄▄▆▆▇▇▇▇▆██▇████ |
Accuracy/val | ▃▃▂▁▅▅▃▆▇▇▇▇▇▆██▇███▇ |
Loss/train | ▇▆▇█▅▅▆▃▃▃▂▂▂▃▁▁▁▁▁▁▁ |
Loss/val | ▆▆▆█▄▄▆▃▂▂▂▂▂▃▁▁▁▁▁▁▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 98.125 |
Accuracy/val | 97.56 |
Loss/train | 0.00153 |
Loss/val | 0.00214 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_035655-ikirp9xn/logs
wandb: Agent Starting Run: xbpuwg2m with config:
wandb: batch_size: 64
wandb: epochs: 50
wandb: learning_rate: 0.0001
wandb: optimizer: adam
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_035852-xbpuwg2m
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0029. Train Acc: 92.8025, Test loss: 0.0030. Test Acc: 92.4700. Time/epoch: 3.3691
EPOCH 10. Progress: 20.0%.
Train loss: 0.0013. Train Acc: 96.9200, Test loss: 0.0014. Test Acc: 96.7400. Time/epoch: 3.3041
EPOCH 20. Progress: 40.0%.
Train loss: 0.0011. Train Acc: 97.2725, Test loss: 0.0013. Test Acc: 96.8900. Time/epoch: 3.2984
EPOCH 30. Progress: 60.0%.
Train loss: 0.0007. Train Acc: 98.3425, Test loss: 0.0010. Test Acc: 97.8500. Time/epoch: 3.1525
EPOCH 40. Progress: 80.0%.
Train loss: 0.0005. Train Acc: 98.6950, Test loss: 0.0009. Test Acc: 98.1000. Time/epoch: 3.3082
EPOCH 50. Progress: 100.0%.
Train loss: 0.0005. Train Acc: 98.6475, Test loss: 0.0010. Test Acc: 97.9400. Time/epoch: 3.2932
Run history:
Accuracy/train | ▁▃▂▃▅▄▆▅▆▆▆▆▆▆▆▇▆▆▆▆▇▆▇▅▇▇▇█▇▇█▇██▇█▇██▇ |
Accuracy/val | ▁▄▃▃▅▅▆▅▆▆▇▇▇▇▇▇▆▇▇▆▇▇▇▆▇█▇█▇▇█▇██▇█▇██▇ |
Loss/train | █▅▆▆▄▄▄▄▃▃▃▃▃▃▃▂▃▂▃▃▂▃▂▄▂▂▂▁▂▂▁▂▁▁▂▁▂▁▁▁ |
Loss/val | █▅▆▆▃▄▃▃▃▂▂▂▂▂▂▂▂▂▂▃▂▂▁▃▁▁▂▁▂▂▁▂▁▁▂▁▂▁▁▂ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.6475 |
Accuracy/val | 97.94 |
Loss/train | 0.00053 |
Loss/val | 0.00104 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_035852-xbpuwg2m/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: bms9a5ow with config:
wandb: batch_size: 64
wandb: epochs: 20
wandb: learning_rate: 1e-05
wandb: optimizer: sgd
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_040201-bms9a5ow
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0086. Train Acc: 83.8575, Test loss: 0.0087. Test Acc: 83.9500. Time/epoch: 2.9495
EPOCH 10. Progress: 50.0%.
Train loss: 0.0029. Train Acc: 92.1350, Test loss: 0.0031. Test Acc: 91.9500. Time/epoch: 3.0603
EPOCH 20. Progress: 100.0%.
Train loss: 0.0026. Train Acc: 93.2900, Test loss: 0.0027. Test Acc: 93.1500. Time/epoch: 3.0438
Run history:
Accuracy/train | ▁▃▅▅▆▆▇▇▇▇▇▇▇████████ |
Accuracy/val | ▁▃▅▅▆▆▇▇▇▇▇▇▇████████ |
Loss/train | █▅▃▃▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▅▃▃▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 93.29 |
Accuracy/val | 93.15 |
Loss/train | 0.00255 |
Loss/val | 0.00269 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_040201-bms9a5ow/logs
wandb: Agent Starting Run: ihr6pabg with config:
wandb: batch_size: 128
wandb: epochs: 50
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_040317-ihr6pabg
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0016. Train Acc: 90.3525, Test loss: 0.0017. Test Acc: 90.4900. Time/epoch: 2.2637
EPOCH 10. Progress: 20.0%.
Train loss: 0.0007. Train Acc: 96.8375, Test loss: 0.0007. Test Acc: 96.4900. Time/epoch: 2.3961
EPOCH 20. Progress: 40.0%.
Train loss: 0.0007. Train Acc: 96.5400, Test loss: 0.0008. Test Acc: 95.9700. Time/epoch: 2.4040
EPOCH 30. Progress: 60.0%.
Train loss: 0.0004. Train Acc: 98.0225, Test loss: 0.0006. Test Acc: 97.0300. Time/epoch: 2.3816
EPOCH 40. Progress: 80.0%.
Train loss: 0.0004. Train Acc: 97.9450, Test loss: 0.0007. Test Acc: 96.8300. Time/epoch: 2.2781
EPOCH 50. Progress: 100.0%.
Train loss: 0.0003. Train Acc: 98.3350, Test loss: 0.0007. Test Acc: 97.1100. Time/epoch: 2.2493
Run history:
Accuracy/train | ▁▄▃▅▅▄▅▆▆▆▅▇▆▇▆▆▆▆▇▄▇▇▇▇▇▇▇▇█▇██████▇▇██ |
Accuracy/val | ▁▄▃▅▅▅▆▆▇▇▅▇▇▇▇▇▆▇▇▃▇▇▇▇▇█▇██▇██████▇▇██ |
Loss/train | █▆▆▅▄▅▄▄▃▃▄▃▃▂▃▃▃▃▂▆▂▂▃▂▂▂▂▂▁▂▁▂▁▁▁▁▂▂▁▁ |
Loss/val | █▅▆▄▄▅▃▃▂▂▄▂▂▁▂▃▂▂▂▇▁▁▂▂▁▁▃▂▁▂▁▁▁▁▁▁▂▂▁▂ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.335 |
Accuracy/val | 97.11 |
Loss/train | 0.00035 |
Loss/val | 0.00074 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_040317-ihr6pabg/logs
wandb: Agent Starting Run: 4ecbpj83 with config:
wandb: batch_size: 32
wandb: epochs: 50
wandb: learning_rate: 3e-05
wandb: optimizer: sgd
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_040529-4ecbpj83
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0304. Train Acc: 83.0275, Test loss: 0.0309. Test Acc: 83.3500. Time/epoch: 4.7452
EPOCH 10. Progress: 20.0%.
Train loss: 0.0061. Train Acc: 92.8800, Test loss: 0.0062. Test Acc: 93.0900. Time/epoch: 4.5664
EPOCH 20. Progress: 40.0%.
Train loss: 0.0056. Train Acc: 93.4800, Test loss: 0.0057. Test Acc: 93.3600. Time/epoch: 4.5281
EPOCH 30. Progress: 60.0%.
Train loss: 0.0054. Train Acc: 93.1425, Test loss: 0.0054. Test Acc: 93.2300. Time/epoch: 4.7129
EPOCH 40. Progress: 80.0%.
Train loss: 0.0052. Train Acc: 93.7025, Test loss: 0.0053. Test Acc: 93.6900. Time/epoch: 4.6930
EPOCH 50. Progress: 100.0%.
Train loss: 0.0052. Train Acc: 93.7325, Test loss: 0.0052. Test Acc: 93.8400. Time/epoch: 4.7197
Run history:
Accuracy/train | ▁▄▅▅▆▆▆▇▇▇▇▆▇▇▇▇██████▇▇▇▇█▇▇██████▇████ |
Accuracy/val | ▁▄▅▅▆▆▆▇▇▇▇▇▇▇▇▇███████▇▇▇██▇███████████ |
Loss/train | █▇▆▆▅▅▂▂▁▁▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▇▆▆▅▅▂▂▁▁▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 93.7325 |
Accuracy/val | 93.84 |
Loss/train | 0.00516 |
Loss/val | 0.00522 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_040529-4ecbpj83/logs
wandb: Agent Starting Run: ddvk082j with config:
wandb: batch_size: 128
wandb: epochs: 50
wandb: learning_rate: 3e-05
wandb: optimizer: sgd
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_040938-ddvk082j
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0033. Train Acc: 84.9600, Test loss: 0.0034. Test Acc: 85.0000. Time/epoch: 2.1726
EPOCH 10. Progress: 20.0%.
Train loss: 0.0012. Train Acc: 93.7450, Test loss: 0.0012. Test Acc: 93.8900. Time/epoch: 2.2998
EPOCH 20. Progress: 40.0%.
Train loss: 0.0010. Train Acc: 94.7875, Test loss: 0.0011. Test Acc: 95.0600. Time/epoch: 2.2911
EPOCH 30. Progress: 60.0%.
Train loss: 0.0010. Train Acc: 95.1850, Test loss: 0.0010. Test Acc: 95.1300. Time/epoch: 2.1656
EPOCH 40. Progress: 80.0%.
Train loss: 0.0009. Train Acc: 95.5050, Test loss: 0.0010. Test Acc: 95.6000. Time/epoch: 2.1626
EPOCH 50. Progress: 100.0%.
Train loss: 0.0008. Train Acc: 95.7200, Test loss: 0.0009. Test Acc: 95.7500. Time/epoch: 2.1521
Run history:
Accuracy/train | ▁▃▃▅▆▆▆▆▇▇▇▇▇▆▇▇▇▇▇█▇█▇██▇▇▇██▇█▆███████ |
Accuracy/val | ▁▃▃▅▆▆▇▆▇▇▇▇▇▆▇▇█▇▇▇▇▇▇██▇▇▇█▇██▆███████ |
Loss/train | █▆▅▄▃▃▂▃▂▂▂▂▂▂▂▂▁▁▁▁▂▁▁▁▁▂▁▂▁▁▁▁▂▁▁▁▁▁▁▁ |
Loss/val | █▆▅▄▃▃▂▂▂▂▂▂▂▂▂▂▁▁▁▁▂▁▁▁▁▁▁▂▁▁▁▁▂▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 95.72 |
Accuracy/val | 95.75 |
Loss/train | 0.00085 |
Loss/val | 0.00092 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_040938-ddvk082j/logs
wandb: Agent Starting Run: ccaoqtld with config:
wandb: batch_size: 128
wandb: epochs: 10
wandb: learning_rate: 0.001
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_041146-ccaoqtld
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0053. Train Acc: 63.4450, Test loss: 0.0053. Test Acc: 64.0900. Time/epoch: 2.3517
EPOCH 10. Progress: 100.0%.
Train loss: 0.0026. Train Acc: 86.4825, Test loss: 0.0026. Test Acc: 86.9600. Time/epoch: 2.1717
Run history:
Accuracy/train | ▁▁▄▃▅▅▇▄▁█▇ |
Accuracy/val | ▁▁▄▃▅▅▇▄▁█▇ |
Loss/train | ▄▅▃▄▂▂▂▂█▁▁ |
Loss/val | ▄▅▃▄▂▂▂▂█▁▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 86.4825 |
Accuracy/val | 86.96 |
Loss/train | 0.00261 |
Loss/val | 0.00265 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_041146-ccaoqtld/logs
wandb: Agent Starting Run: tv6lmibh with config:
wandb: batch_size: 32
wandb: epochs: 20
wandb: learning_rate: 0.01
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_041227-tv6lmibh
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0482. Train Acc: 36.8250, Test loss: 0.0481. Test Acc: 37.5400. Time/epoch: 4.8126
EPOCH 10. Progress: 50.0%.
Train loss: 0.0480. Train Acc: 36.8250, Test loss: 0.0480. Test Acc: 37.5400. Time/epoch: 4.8172
EPOCH 20. Progress: 100.0%.
Train loss: 0.0480. Train Acc: 36.8250, Test loss: 0.0480. Test Acc: 37.5400. Time/epoch: 4.7995
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | █▃▃▂▁▁▁▃▁▂▁▂▁▃▂▃▁▃▃▂▁ |
Loss/val | █▄▂▂▁▂▁▂▁▁▂▂▂▃▁▂▁▄▃▁▂ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.04804 |
Loss/val | 0.04795 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_041227-tv6lmibh/logs
wandb: Agent Starting Run: w39caajm with config:
wandb: batch_size: 64
wandb: epochs: 50
wandb: learning_rate: 3e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_041419-w39caajm
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0036. Train Acc: 91.1700, Test loss: 0.0037. Test Acc: 91.2600. Time/epoch: 3.3021
EPOCH 10. Progress: 20.0%.
Train loss: 0.0017. Train Acc: 95.7500, Test loss: 0.0018. Test Acc: 95.4500. Time/epoch: 3.2997
EPOCH 20. Progress: 40.0%.
Train loss: 0.0014. Train Acc: 96.6900, Test loss: 0.0015. Test Acc: 96.2900. Time/epoch: 3.1159
EPOCH 30. Progress: 60.0%.
Train loss: 0.0013. Train Acc: 96.6850, Test loss: 0.0015. Test Acc: 96.2900. Time/epoch: 3.3020
EPOCH 40. Progress: 80.0%.
Train loss: 0.0010. Train Acc: 97.5825, Test loss: 0.0012. Test Acc: 97.1500. Time/epoch: 3.2864
EPOCH 50. Progress: 100.0%.
Train loss: 0.0010. Train Acc: 97.5925, Test loss: 0.0012. Test Acc: 97.1400. Time/epoch: 3.2681
Run history:
Accuracy/train | ▁▃▃▄▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇█▇█▇▇▇███████ |
Accuracy/val | ▁▃▃▄▅▅▅▆▆▆▆▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇█▇▇▇█▇██▇██ |
Loss/train | █▆▅▅▄▄▄▃▃▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▁▂▁▂▂▂▁▁▁▁▁▁▁ |
Loss/val | █▆▅▅▄▄▄▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▁▁▁▂▁▂▂▂▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 97.5925 |
Accuracy/val | 97.14 |
Loss/train | 0.00099 |
Loss/val | 0.0012 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_041419-w39caajm/logs
wandb: Agent Starting Run: iprutlfn with config:
wandb: batch_size: 128
wandb: epochs: 10
wandb: learning_rate: 0.0001
wandb: optimizer: adam
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_041716-iprutlfn
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0020. Train Acc: 90.0725, Test loss: 0.0021. Test Acc: 90.0000. Time/epoch: 2.4462
EPOCH 10. Progress: 100.0%.
Train loss: 0.0010. Train Acc: 94.9400, Test loss: 0.0010. Test Acc: 94.8700. Time/epoch: 2.3934
Run history:
Accuracy/train | ▁▂▄▅▇███▇█▇ |
Accuracy/val | ▁▂▄▆▇▇██▇█▇ |
Loss/train | █▆▅▃▂▂▂▁▂▁▂ |
Loss/val | █▆▅▃▂▂▂▁▂▁▂ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 94.94 |
Accuracy/val | 94.87 |
Loss/train | 0.00096 |
Loss/val | 0.00104 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_041716-iprutlfn/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: rmk7xwg2 with config:
wandb: batch_size: 128
wandb: epochs: 20
wandb: learning_rate: 0.001
wandb: optimizer: sgd
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_041803-rmk7xwg2
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0036. Train Acc: 77.4625, Test loss: 0.0036. Test Acc: 77.7900. Time/epoch: 2.3357
EPOCH 10. Progress: 50.0%.
Train loss: 0.0038. Train Acc: 78.8350, Test loss: 0.0038. Test Acc: 79.0700. Time/epoch: 2.3126
EPOCH 20. Progress: 100.0%.
Train loss: 0.0032. Train Acc: 81.2675, Test loss: 0.0032. Test Acc: 81.9000. Time/epoch: 2.3034
Run history:
Accuracy/train | ▅▁▆▇▇██▅▅▅▅▆▆▆▆▆▆▆▆▅▆ |
Accuracy/val | ▅▁▆▇███▅▅▅▅▅▆▆▆▅▆▆▆▅▆ |
Loss/train | ▂█▄▃▂▂▁▃▃▃▂▂▂▂▂▂▂▂▂▂▂ |
Loss/val | ▂█▄▃▂▂▁▄▃▃▂▂▂▂▂▂▂▂▂▂▂ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 81.2675 |
Accuracy/val | 81.9 |
Loss/train | 0.00318 |
Loss/val | 0.00321 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_041803-rmk7xwg2/logs
wandb: Agent Starting Run: 1wevhc82 with config:
wandb: batch_size: 64
wandb: epochs: 50
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_041904-1wevhc82
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0024. Train Acc: 93.7875, Test loss: 0.0025. Test Acc: 93.8200. Time/epoch: 3.3504
EPOCH 10. Progress: 20.0%.
Train loss: 0.0012. Train Acc: 96.7600, Test loss: 0.0015. Test Acc: 96.1400. Time/epoch: 3.2640
EPOCH 20. Progress: 40.0%.
Train loss: 0.0007. Train Acc: 98.2800, Test loss: 0.0011. Test Acc: 97.5600. Time/epoch: 3.3123
EPOCH 30. Progress: 60.0%.
Train loss: 0.0007. Train Acc: 98.5250, Test loss: 0.0013. Test Acc: 97.4900. Time/epoch: 3.3069
EPOCH 40. Progress: 80.0%.
Train loss: 0.0005. Train Acc: 98.8725, Test loss: 0.0014. Test Acc: 97.7500. Time/epoch: 3.1509
EPOCH 50. Progress: 100.0%.
Train loss: 0.0006. Train Acc: 98.5400, Test loss: 0.0014. Test Acc: 97.1700. Time/epoch: 3.1518
Run history:
Accuracy/train | ▁▁▃▄▃▅▅▅▅▅▅▆▄▆▄▅▇▆▇▆▇▇▇▇▇▇▇▆█▅█▇▇██▇▇██▇ |
Accuracy/val | ▁▁▄▄▄▅▅▅▅▅▆▆▄▇▄▅▇▇▇▆█▇▇▇▇▇█▇█▅█▇▆▇█▇▇██▇ |
Loss/train | ██▆▅▆▄▄▄▄▄▄▃▅▃▅▅▂▃▂▃▂▂▂▂▂▂▂▃▁▅▁▂▂▁▁▂▂▁▁▂ |
Loss/val | ██▅▄▅▃▃▃▃▃▃▂▅▁▄▄▁▂▁▃▁▂▂▂▂▂▁▃▁▇▂▂▃▂▂▃▃▂▁▃ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.54 |
Accuracy/val | 97.17 |
Loss/train | 0.00055 |
Loss/val | 0.00143 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_041904-1wevhc82/logs
wandb: Agent Starting Run: xhucx4ro with config:
wandb: batch_size: 64
wandb: epochs: 50
wandb: learning_rate: 1e-05
wandb: optimizer: sgd
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_042204-xhucx4ro
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0141. Train Acc: 68.0175, Test loss: 0.0140. Test Acc: 68.3800. Time/epoch: 3.1224
EPOCH 10. Progress: 20.0%.
Train loss: 0.0032. Train Acc: 91.7075, Test loss: 0.0033. Test Acc: 92.0200. Time/epoch: 2.9470
EPOCH 20. Progress: 40.0%.
Train loss: 0.0027. Train Acc: 93.5925, Test loss: 0.0029. Test Acc: 93.3000. Time/epoch: 2.9227
EPOCH 30. Progress: 60.0%.
Train loss: 0.0024. Train Acc: 94.1850, Test loss: 0.0025. Test Acc: 93.8900. Time/epoch: 2.9237
EPOCH 40. Progress: 80.0%.
Train loss: 0.0022. Train Acc: 94.2875, Test loss: 0.0023. Test Acc: 94.2000. Time/epoch: 3.0559
EPOCH 50. Progress: 100.0%.
Train loss: 0.0019. Train Acc: 95.2075, Test loss: 0.0020. Test Acc: 95.2100. Time/epoch: 3.0550
Run history:
Accuracy/train | ▁▅▆▆▇▇▇▇▇▇▇▇▇▇█▇████████████████████████ |
Accuracy/val | ▁▅▆▆▇▇▇▇▇▇▇▇▇▇███▇██████████████████████ |
Loss/train | █▄▃▂▂▂▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▄▃▂▂▂▂▂▂▂▂▂▂▂▁▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 95.2075 |
Accuracy/val | 95.21 |
Loss/train | 0.00193 |
Loss/val | 0.00204 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_042204-xhucx4ro/logs
wandb: Agent Starting Run: iv54em4c with config:
wandb: batch_size: 32
wandb: epochs: 50
wandb: learning_rate: 0.01
wandb: optimizer: sgd
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_042453-iv54em4c
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0480. Train Acc: 36.8250, Test loss: 0.0479. Test Acc: 37.5400. Time/epoch: 4.5864
EPOCH 10. Progress: 20.0%.
Train loss: 0.0481. Train Acc: 36.8250, Test loss: 0.0479. Test Acc: 37.5400. Time/epoch: 4.5563
EPOCH 20. Progress: 40.0%.
Train loss: 0.0481. Train Acc: 36.8250, Test loss: 0.0480. Test Acc: 37.5400. Time/epoch: 4.6828
EPOCH 30. Progress: 60.0%.
Train loss: 0.0481. Train Acc: 36.8250, Test loss: 0.0480. Test Acc: 37.5400. Time/epoch: 4.7069
EPOCH 40. Progress: 80.0%.
Train loss: 0.0481. Train Acc: 36.8250, Test loss: 0.0480. Test Acc: 37.5400. Time/epoch: 4.7404
EPOCH 50. Progress: 100.0%.
Train loss: 0.0482. Train Acc: 36.8250, Test loss: 0.0481. Test Acc: 37.5400. Time/epoch: 4.6482
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | ▁▃▂▂▃▃▂▂▂▂▂▂▄▃▅▃▅▇▁▁█▅█▂▃▃▅▁▄▂▄▃▂▂▁▄▅▁▃▇ |
Loss/val | ▁▃▂▄▃▃▃▃▁▂▁▂▅▂▅▂▄▄▁▂█▄█▂▃▃▅▂▄▂▄▅▁▂▂▃▃▁▃▇ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.04817 |
Loss/val | 0.04809 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_042453-iv54em4c/logs
wandb: Agent Starting Run: ma6pe9c9 with config:
wandb: batch_size: 32
wandb: epochs: 50
wandb: learning_rate: 1e-05
wandb: optimizer: sgd
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_042901-ma6pe9c9
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0153. Train Acc: 80.8250, Test loss: 0.0152. Test Acc: 80.6200. Time/epoch: 4.7573
EPOCH 10. Progress: 20.0%.
Train loss: 0.0045. Train Acc: 94.4025, Test loss: 0.0046. Test Acc: 94.7300. Time/epoch: 4.7037
EPOCH 20. Progress: 40.0%.
Train loss: 0.0041. Train Acc: 94.7325, Test loss: 0.0043. Test Acc: 94.8600. Time/epoch: 4.6952
EPOCH 30. Progress: 60.0%.
Train loss: 0.0035. Train Acc: 95.7775, Test loss: 0.0037. Test Acc: 95.6700. Time/epoch: 4.6677
EPOCH 40. Progress: 80.0%.
Train loss: 0.0035. Train Acc: 95.6200, Test loss: 0.0036. Test Acc: 95.5900. Time/epoch: 4.5579
EPOCH 50. Progress: 100.0%.
Train loss: 0.0030. Train Acc: 96.2000, Test loss: 0.0033. Test Acc: 96.2100. Time/epoch: 4.5332
Run history:
Accuracy/train | ▁▃▄▅▆▆▇▇▇▇▇▇▇▇▇▇▇█▇█▇███████████████████ |
Accuracy/val | ▁▃▄▅▆▆▇▇▇▇▇▇▇▇▇▇▇█▇█████████████████████ |
Loss/train | █▆▅▄▃▃▂▂▂▂▂▂▂▂▂▂▂▁▁▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▆▅▄▃▃▂▂▂▂▂▂▂▂▂▂▂▁▁▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 96.2 |
Accuracy/val | 96.21 |
Loss/train | 0.00305 |
Loss/val | 0.00328 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_042901-ma6pe9c9/logs
wandb: Agent Starting Run: 23nqvcc2 with config:
wandb: batch_size: 128
wandb: epochs: 10
wandb: learning_rate: 0.001
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_043309-23nqvcc2
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0048. Train Acc: 73.7925, Test loss: 0.0049. Test Acc: 74.1700. Time/epoch: 2.3877
EPOCH 10. Progress: 100.0%.
Train loss: 0.0081. Train Acc: 57.1475, Test loss: 0.0081. Test Acc: 57.7900. Time/epoch: 2.2014
Run history:
Accuracy/train | ▅▅▆▆▆▆▇███▁ |
Accuracy/val | ▅▅▆▆▆▆▇███▁ |
Loss/train | ▄▄▃▂▂▂▂▁▁▁█ |
Loss/val | ▄▄▃▂▂▃▂▁▁▁█ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 57.1475 |
Accuracy/val | 57.79 |
Loss/train | 0.00814 |
Loss/val | 0.00813 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_043309-23nqvcc2/logs
wandb: Agent Starting Run: 8xl53zs7 with config:
wandb: batch_size: 64
wandb: epochs: 20
wandb: learning_rate: 1e-05
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_043349-8xl53zs7
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0059. Train Acc: 84.4050, Test loss: 0.0059. Test Acc: 84.3900. Time/epoch: 3.1628
EPOCH 10. Progress: 50.0%.
Train loss: 0.0026. Train Acc: 93.5075, Test loss: 0.0027. Test Acc: 93.4200. Time/epoch: 3.1191
EPOCH 20. Progress: 100.0%.
Train loss: 0.0023. Train Acc: 94.1400, Test loss: 0.0023. Test Acc: 94.0900. Time/epoch: 3.1040
Run history:
Accuracy/train | ▁▃▄▅▆▇▇▇▇▇██▇█▇██████ |
Accuracy/val | ▁▃▄▅▆▆▇▇▇▇▇▇▇█▇██████ |
Loss/train | █▅▄▄▃▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁ |
Loss/val | █▅▄▄▃▂▂▂▂▂▂▂▂▁▂▁▁▁▁▁▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 94.14 |
Accuracy/val | 94.09 |
Loss/train | 0.00227 |
Loss/val | 0.00234 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_043349-8xl53zs7/logs
wandb: Agent Starting Run: fzw96h8a with config:
wandb: batch_size: 64
wandb: epochs: 10
wandb: learning_rate: 3e-05
wandb: optimizer: sgd
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_043506-fzw96h8a
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0053. Train Acc: 85.2075, Test loss: 0.0055. Test Acc: 84.7800. Time/epoch: 3.1110
EPOCH 10. Progress: 100.0%.
Train loss: 0.0026. Train Acc: 93.2875, Test loss: 0.0027. Test Acc: 93.2000. Time/epoch: 3.0699
Run history:
Accuracy/train | ▁▄▅▆▇▇▇████ |
Accuracy/val | ▁▄▆▆▇▇▇████ |
Loss/train | █▅▃▃▂▂▂▁▁▁▁ |
Loss/val | █▅▃▃▂▂▂▁▁▁▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 93.2875 |
Accuracy/val | 93.2 |
Loss/train | 0.00258 |
Loss/val | 0.00269 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_043506-fzw96h8a/logs
wandb: Agent Starting Run: zyqvr0bs with config:
wandb: batch_size: 64
wandb: epochs: 20
wandb: learning_rate: 0.0001
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_043552-zyqvr0bs
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0035. Train Acc: 89.7875, Test loss: 0.0036. Test Acc: 89.6900. Time/epoch: 3.1379
EPOCH 10. Progress: 50.0%.
Train loss: 0.0024. Train Acc: 93.0025, Test loss: 0.0025. Test Acc: 92.8200. Time/epoch: 3.1572
EPOCH 20. Progress: 100.0%.
Train loss: 0.0018. Train Acc: 95.6375, Test loss: 0.0019. Test Acc: 95.6900. Time/epoch: 3.1587
Run history:
Accuracy/train | ▁▄▃▅▄▆▅▇▅▆▅▆▅▆█▇▅▇▇▆█ |
Accuracy/val | ▁▄▃▅▄▆▅▆▅▅▅▆▅▆▇▇▅▇▇▆█ |
Loss/train | █▅▆▄▄▃▃▂▄▃▃▂▄▃▁▁▄▁▁▃▁ |
Loss/val | █▅▆▄▄▃▃▂▄▃▄▂▄▃▁▁▅▁▁▃▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 95.6375 |
Accuracy/val | 95.69 |
Loss/train | 0.00184 |
Loss/val | 0.00193 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_043552-zyqvr0bs/logs
wandb: Agent Starting Run: dkbivil6 with config:
wandb: batch_size: 128
wandb: epochs: 10
wandb: learning_rate: 0.0001
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_043717-dkbivil6
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0016. Train Acc: 92.0450, Test loss: 0.0016. Test Acc: 92.0200. Time/epoch: 2.3793
EPOCH 10. Progress: 100.0%.
Train loss: 0.0011. Train Acc: 93.6850, Test loss: 0.0012. Test Acc: 93.6100. Time/epoch: 2.3126
Run history:
Accuracy/train | ▄▁▅▆▇▇▆▆██▇ |
Accuracy/val | ▄▁▆▆▇▇▆▆█▇▇ |
Loss/train | ▇█▄▄▃▃▄▃▁▁▁ |
Loss/val | ▇█▄▅▃▂▄▃▁▁▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 93.685 |
Accuracy/val | 93.61 |
Loss/train | 0.00114 |
Loss/val | 0.00117 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_043717-dkbivil6/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: 6x9y411z with config:
wandb: batch_size: 64
wandb: epochs: 10
wandb: learning_rate: 3e-05
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_043803-6x9y411z
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0049. Train Acc: 87.2225, Test loss: 0.0049. Test Acc: 87.0700. Time/epoch: 3.0262
EPOCH 10. Progress: 100.0%.
Train loss: 0.0023. Train Acc: 94.0150, Test loss: 0.0024. Test Acc: 93.9400. Time/epoch: 3.1293
Run history:
Accuracy/train | ▁▄▃▆▆▇▇▇▇▇█ |
Accuracy/val | ▁▄▃▆▆▇█████ |
Loss/train | █▅▅▃▃▂▂▂▂▁▁ |
Loss/val | █▅▅▃▃▂▂▁▂▁▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 94.015 |
Accuracy/val | 93.94 |
Loss/train | 0.0023 |
Loss/val | 0.00237 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_043803-6x9y411z/logs
wandb: Agent Starting Run: 7fv4ximh with config:
wandb: batch_size: 128
wandb: epochs: 10
wandb: learning_rate: 0.001
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_043856-7fv4ximh
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0063. Train Acc: 63.7975, Test loss: 0.0063. Test Acc: 64.4500. Time/epoch: 2.2445
EPOCH 10. Progress: 100.0%.
Train loss: 0.0029. Train Acc: 83.5575, Test loss: 0.0029. Test Acc: 83.8900. Time/epoch: 2.3428
Run history:
Accuracy/train | ▁▇▇██▅▆▆▇▆▇ |
Accuracy/val | ▁▆▇██▅▆▆▆▆▇ |
Loss/train | █▂▂▂▁▃▁▂▂▄▁ |
Loss/val | █▂▂▂▁▃▁▂▂▄▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 83.5575 |
Accuracy/val | 83.89 |
Loss/train | 0.00291 |
Loss/val | 0.00293 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_043856-7fv4ximh/logs
wandb: Agent Starting Run: jv089cio with config:
wandb: batch_size: 128
wandb: epochs: 20
wandb: learning_rate: 0.0001
wandb: optimizer: adam
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_043937-jv089cio
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0014. Train Acc: 92.1825, Test loss: 0.0015. Test Acc: 91.9300. Time/epoch: 2.3079
EPOCH 10. Progress: 50.0%.
Train loss: 0.0008. Train Acc: 96.1775, Test loss: 0.0009. Test Acc: 95.7400. Time/epoch: 2.2664
EPOCH 20. Progress: 100.0%.
Train loss: 0.0007. Train Acc: 96.4850, Test loss: 0.0009. Test Acc: 95.9300. Time/epoch: 2.4115
Run history:
Accuracy/train | ▁▃▃▅▆▆▆▆▆▇▇▇▇▇▇▇████▇ |
Accuracy/val | ▁▃▄▅▇▇▇▇▆▇▇█▇▇█▇▇███▇ |
Loss/train | █▇▆▅▃▃▃▃▃▂▃▂▂▂▂▂▂▂▁▁▂ |
Loss/val | █▇▆▄▃▃▃▃▃▂▂▂▂▂▂▂▁▂▁▁▂ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 96.485 |
Accuracy/val | 95.93 |
Loss/train | 0.00074 |
Loss/val | 0.00085 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_043937-jv089cio/logs
wandb: Agent Starting Run: ie0howoj with config:
wandb: batch_size: 32
wandb: epochs: 20
wandb: learning_rate: 0.0001
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_044039-ie0howoj
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0114. Train Acc: 85.0550, Test loss: 0.0114. Test Acc: 85.0300. Time/epoch: 4.6808
EPOCH 10. Progress: 50.0%.
Train loss: 0.0038. Train Acc: 95.1400, Test loss: 0.0038. Test Acc: 95.3300. Time/epoch: 4.7925
EPOCH 20. Progress: 100.0%.
Train loss: 0.0036. Train Acc: 95.3850, Test loss: 0.0036. Test Acc: 95.4900. Time/epoch: 4.8198
Run history:
Accuracy/train | ▁▇▆▇▆█▇▇█▇██▇█▆█▇█▇██ |
Accuracy/val | ▁▇▆▇▆█▇▇█▇██▇█▆█▇█▇██ |
Loss/train | █▂▃▂▃▁▂▂▁▂▁▁▂▁▂▁▁▁▂▁▁ |
Loss/val | █▂▃▂▃▁▂▂▁▂▁▁▂▁▂▁▁▁▂▁▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 95.385 |
Accuracy/val | 95.49 |
Loss/train | 0.00356 |
Loss/val | 0.00364 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_044039-ie0howoj/logs
wandb: Agent Starting Run: y8m14jm2 with config:
wandb: batch_size: 32
wandb: epochs: 10
wandb: learning_rate: 0.0003
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_044230-y8m14jm2
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0079. Train Acc: 89.1475, Test loss: 0.0078. Test Acc: 89.2300. Time/epoch: 4.7174
EPOCH 10. Progress: 100.0%.
Train loss: 0.0047. Train Acc: 93.5375, Test loss: 0.0047. Test Acc: 93.7300. Time/epoch: 4.8036
Run history:
Accuracy/train | ▅▁▇█▇▇▇█▇█▇ |
Accuracy/val | ▅▁▇█▇▇▇█▇█▇ |
Loss/train | ▄█▂▁▂▂▂▁▁▁▁ |
Loss/val | ▄█▃▁▂▂▂▁▁▁▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 93.5375 |
Accuracy/val | 93.73 |
Loss/train | 0.00468 |
Loss/val | 0.00474 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_044230-y8m14jm2/logs
wandb: Agent Starting Run: p3mnzq2j with config:
wandb: batch_size: 128
wandb: epochs: 20
wandb: learning_rate: 0.0003
wandb: optimizer: sgd
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_044336-p3mnzq2j
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0016. Train Acc: 91.4575, Test loss: 0.0017. Test Acc: 91.7700. Time/epoch: 2.2012
EPOCH 10. Progress: 50.0%.
Train loss: 0.0010. Train Acc: 95.2800, Test loss: 0.0010. Test Acc: 94.8800. Time/epoch: 2.1679
EPOCH 20. Progress: 100.0%.
Train loss: 0.0006. Train Acc: 96.7925, Test loss: 0.0007. Test Acc: 96.6300. Time/epoch: 2.2994
Run history:
Accuracy/train | ▂▁▅▅▆▆▆▆▆▇▆▅▇▇▇▇██▆██ |
Accuracy/val | ▂▁▅▅▆▆▆▆▆▆▆▅▇▇▇▇██▆██ |
Loss/train | ▇█▄▄▄▃▃▃▃▃▃▅▂▂▂▂▁▁▄▁▁ |
Loss/val | ██▄▄▄▃▃▃▃▂▃▅▂▂▂▂▁▁▄▁▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 96.7925 |
Accuracy/val | 96.63 |
Loss/train | 0.00065 |
Loss/val | 0.0007 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_044336-p3mnzq2j/logs
wandb: Agent Starting Run: f6w6u2cx with config:
wandb: batch_size: 32
wandb: epochs: 10
wandb: learning_rate: 0.0003
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_044437-f6w6u2cx
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0077. Train Acc: 88.8800, Test loss: 0.0078. Test Acc: 89.0600. Time/epoch: 4.7254
EPOCH 10. Progress: 100.0%.
Train loss: 0.0041. Train Acc: 94.6425, Test loss: 0.0042. Test Acc: 94.8000. Time/epoch: 4.6793
Run history:
Accuracy/train | ▁▅▆▆▄▇██▄▇█ |
Accuracy/val | ▁▅▆▆▅▇██▄▇█ |
Loss/train | █▄▂▃▅▂▁▂▅▂▁ |
Loss/val | █▄▃▃▅▂▁▂▅▂▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 94.6425 |
Accuracy/val | 94.8 |
Loss/train | 0.0041 |
Loss/val | 0.0042 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_044437-f6w6u2cx/logs
wandb: Agent Starting Run: qpvp5b2e with config:
wandb: batch_size: 32
wandb: epochs: 20
wandb: learning_rate: 1e-05
wandb: optimizer: rmsprop
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_044543-qpvp5b2e
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0116. Train Acc: 87.1425, Test loss: 0.0117. Test Acc: 87.2200. Time/epoch: 4.8218
EPOCH 10. Progress: 50.0%.
Train loss: 0.0041. Train Acc: 94.7775, Test loss: 0.0043. Test Acc: 94.7900. Time/epoch: 4.6649
EPOCH 20. Progress: 100.0%.
Train loss: 0.0033. Train Acc: 95.9400, Test loss: 0.0035. Test Acc: 95.8000. Time/epoch: 4.6596
Run history:
Accuracy/train | ▁▃▄▅▆▆▆▆▇▇▇▇▇▇▇██████ |
Accuracy/val | ▁▃▄▅▅▆▆▆▇▇▇▇▇█▇██████ |
Loss/train | █▅▄▃▃▃▂▂▂▂▂▂▂▁▂▁▁▁▁▁▁ |
Loss/val | █▅▄▃▃▃▂▂▂▂▂▂▂▁▂▁▁▁▁▁▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 95.94 |
Accuracy/val | 95.8 |
Loss/train | 0.00332 |
Loss/val | 0.00352 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_044543-qpvp5b2e/logs
wandb: Agent Starting Run: q48xmpg1 with config:
wandb: batch_size: 128
wandb: epochs: 20
wandb: learning_rate: 0.0001
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_044739-q48xmpg1
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0022. Train Acc: 87.7325, Test loss: 0.0022. Test Acc: 87.8600. Time/epoch: 2.3428
EPOCH 10. Progress: 50.0%.
Train loss: 0.0013. Train Acc: 93.1575, Test loss: 0.0013. Test Acc: 92.9800. Time/epoch: 2.1956
EPOCH 20. Progress: 100.0%.
Train loss: 0.0012. Train Acc: 93.6150, Test loss: 0.0012. Test Acc: 93.5400. Time/epoch: 2.2199
Run history:
Accuracy/train | ▂▄▄▅▆▅▆▄▅▁▇▆▇▇▅█▇▆▄█▇ |
Accuracy/val | ▂▄▄▅▆▅▆▅▅▁▆▆▇▇▅██▆▄█▇ |
Loss/train | ▆▄▄▃▂▃▂▄▃█▂▂▁▂▃▁▁▂▄▁▂ |
Loss/val | ▆▄▄▃▂▃▂▄▃█▂▂▂▂▃▁▁▂▄▁▂ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 93.615 |
Accuracy/val | 93.54 |
Loss/train | 0.00121 |
Loss/val | 0.00125 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_044739-q48xmpg1/logs
wandb: Agent Starting Run: d67tqps8 with config:
wandb: batch_size: 64
wandb: epochs: 10
wandb: learning_rate: 0.001
wandb: optimizer: adam
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_044842-d67tqps8
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0030. Train Acc: 91.3375, Test loss: 0.0031. Test Acc: 91.4300. Time/epoch: 3.3121
EPOCH 10. Progress: 100.0%.
Train loss: 0.0027. Train Acc: 92.4125, Test loss: 0.0029. Test Acc: 92.1500. Time/epoch: 3.1438
Run history:
Accuracy/train | ▁▅▅▆█▇▆▆▇█▂ |
Accuracy/val | ▁▅▅▆█▇▆▆▇█▂ |
Loss/train | █▄▄▄▂▂▄▃▁▁▇ |
Loss/val | █▃▃▃▁▁▄▃▁▁▇ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 92.4125 |
Accuracy/val | 92.15 |
Loss/train | 0.00272 |
Loss/val | 0.00291 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_044842-d67tqps8/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: qrx1ovtv with config:
wandb: batch_size: 32
wandb: epochs: 50
wandb: learning_rate: 0.0001
wandb: optimizer: sgd
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_044938-qrx1ovtv
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0076. Train Acc: 89.5575, Test loss: 0.0079. Test Acc: 89.4100. Time/epoch: 4.7665
EPOCH 10. Progress: 20.0%.
Train loss: 0.0033. Train Acc: 95.7075, Test loss: 0.0035. Test Acc: 95.4600. Time/epoch: 4.5480
EPOCH 20. Progress: 40.0%.
Train loss: 0.0032. Train Acc: 95.9850, Test loss: 0.0034. Test Acc: 95.7300. Time/epoch: 4.5604
EPOCH 30. Progress: 60.0%.
Train loss: 0.0022. Train Acc: 97.3125, Test loss: 0.0025. Test Acc: 96.7700. Time/epoch: 4.6915
EPOCH 40. Progress: 80.0%.
Train loss: 0.0025. Train Acc: 96.8350, Test loss: 0.0029. Test Acc: 96.3100. Time/epoch: 4.6664
EPOCH 50. Progress: 100.0%.
Train loss: 0.0020. Train Acc: 97.3450, Test loss: 0.0026. Test Acc: 96.6500. Time/epoch: 4.7361
Run history:
Accuracy/train | ▁▅▄▆▆▆▆▇▆▆▇▇▇▆▆▇▇▇▇▇▇▅█▇██▇████▇████████ |
Accuracy/val | ▁▅▄▆▇▇▇▇▇▆▇█▇▇▇▇▇█▇▇█▅█▇██▇█████████████ |
Loss/train | █▄▅▃▃▃▃▂▃▃▂▂▂▃▂▂▂▂▂▂▂▅▁▂▁▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▄▅▃▃▂▂▂▂▃▂▂▂▃▂▂▂▁▁▂▁▅▁▂▁▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 97.345 |
Accuracy/val | 96.65 |
Loss/train | 0.00202 |
Loss/val | 0.00257 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_044938-qrx1ovtv/logs
wandb: Agent Starting Run: r0tcydda with config:
wandb: batch_size: 32
wandb: epochs: 50
wandb: learning_rate: 0.0003
wandb: optimizer: sgd
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_045347-r0tcydda
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0065. Train Acc: 91.3400, Test loss: 0.0066. Test Acc: 91.3500. Time/epoch: 4.7255
EPOCH 10. Progress: 20.0%.
Train loss: 0.0027. Train Acc: 96.7075, Test loss: 0.0029. Test Acc: 96.6900. Time/epoch: 4.7231
EPOCH 20. Progress: 40.0%.
Train loss: 0.0021. Train Acc: 97.3500, Test loss: 0.0025. Test Acc: 97.1000. Time/epoch: 4.6715
EPOCH 30. Progress: 60.0%.
Train loss: 0.0023. Train Acc: 97.2850, Test loss: 0.0029. Test Acc: 96.6300. Time/epoch: 4.5619
EPOCH 40. Progress: 80.0%.
Train loss: 0.0011. Train Acc: 98.8325, Test loss: 0.0019. Test Acc: 97.8100. Time/epoch: 4.6892
EPOCH 50. Progress: 100.0%.
Train loss: 0.0010. Train Acc: 98.7925, Test loss: 0.0021. Test Acc: 97.6700. Time/epoch: 4.7450
Run history:
Accuracy/train | ▁▄▄▄▅▆▆▆▆▅▆▆▇▆▆▇▇▇▇▇▇▆▇▇▆▇▅▇▇▇▇█▇█▇█████ |
Accuracy/val | ▁▄▄▄▅▆▆▆▇▅▆▇█▇▇▇▇▇▇▇▇▇▇▇▆▇▅█▇▇▇█▇█▇█████ |
Loss/train | █▅▅▅▄▄▃▃▃▄▃▃▂▃▃▂▂▂▂▂▂▃▂▂▃▂▄▁▂▂▁▁▁▁▂▁▁▁▁▁ |
Loss/val | █▅▅▄▄▃▃▂▂▄▂▂▁▂▂▂▂▂▂▂▂▂▂▂▃▂▄▁▂▂▁▂▁▁▂▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.7925 |
Accuracy/val | 97.67 |
Loss/train | 0.00099 |
Loss/val | 0.00214 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_045347-r0tcydda/logs
wandb: Agent Starting Run: c8zovo8a with config:
wandb: batch_size: 32
wandb: epochs: 10
wandb: learning_rate: 0.01
wandb: optimizer: sgd
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_045800-c8zovo8a
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0481. Train Acc: 36.8250, Test loss: 0.0479. Test Acc: 37.5400. Time/epoch: 4.6026
EPOCH 10. Progress: 100.0%.
Train loss: 0.0481. Train Acc: 36.8250, Test loss: 0.0480. Test Acc: 37.5400. Time/epoch: 4.5430
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | ▄▄▄▅▂▄▁▂█▆▆ |
Loss/val | ▂▁▃▃▃▃▁▂█▃▆ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.04807 |
Loss/val | 0.04799 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_045800-c8zovo8a/logs
wandb: Agent Starting Run: v3panwv7 with config:
wandb: batch_size: 32
wandb: epochs: 50
wandb: learning_rate: 3e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_045906-v3panwv7
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0075. Train Acc: 90.4825, Test loss: 0.0077. Test Acc: 90.5300. Time/epoch: 5.1299
EPOCH 10. Progress: 20.0%.
Train loss: 0.0039. Train Acc: 94.7775, Test loss: 0.0041. Test Acc: 94.7800. Time/epoch: 4.9728
EPOCH 20. Progress: 40.0%.
Train loss: 0.0028. Train Acc: 96.6000, Test loss: 0.0030. Test Acc: 96.3700. Time/epoch: 4.9783
EPOCH 30. Progress: 60.0%.
Train loss: 0.0024. Train Acc: 97.0150, Test loss: 0.0027. Test Acc: 96.6700. Time/epoch: 5.1013
EPOCH 40. Progress: 80.0%.
Train loss: 0.0023. Train Acc: 97.0275, Test loss: 0.0027. Test Acc: 96.8100. Time/epoch: 5.1476
EPOCH 50. Progress: 100.0%.
Train loss: 0.0019. Train Acc: 97.7550, Test loss: 0.0024. Test Acc: 97.1600. Time/epoch: 5.1112
Run history:
Accuracy/train | ▁▁▃▄▅▅▅▅▅▆▆▅▆▆▆▇▇▆▇▇▇▆▇▆▇▇▇▇▇█▆▇▇█████▇█ |
Accuracy/val | ▁▁▃▄▅▅▅▆▆▆▆▅▆▆▇▇▇▆▇▇▇▇▇▆▇██▇▇█▆▇▇█████▇█ |
Loss/train | █▇▆▅▄▄▄▄▃▃▃▄▃▃▃▂▂▃▂▂▂▃▂▃▂▂▂▂▂▁▃▂▂▁▁▂▁▁▂▁ |
Loss/val | █▇▆▅▄▄▃▃▃▃▃▃▂▃▂▂▂▃▂▂▂▂▂▃▁▂▁▂▂▁▃▂▂▁▁▁▁▁▂▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 97.755 |
Accuracy/val | 97.16 |
Loss/train | 0.00187 |
Loss/val | 0.0024 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_045906-v3panwv7/logs
wandb: Agent Starting Run: un4qy5px with config:
wandb: batch_size: 128
wandb: epochs: 50
wandb: learning_rate: 3e-05
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_050340-un4qy5px
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0020. Train Acc: 89.7425, Test loss: 0.0021. Test Acc: 89.4600. Time/epoch: 2.3800
EPOCH 10. Progress: 20.0%.
Train loss: 0.0010. Train Acc: 94.5250, Test loss: 0.0011. Test Acc: 94.5200. Time/epoch: 2.3447
EPOCH 20. Progress: 40.0%.
Train loss: 0.0009. Train Acc: 95.1150, Test loss: 0.0010. Test Acc: 94.9200. Time/epoch: 2.3370
EPOCH 30. Progress: 60.0%.
Train loss: 0.0007. Train Acc: 96.2550, Test loss: 0.0008. Test Acc: 95.8100. Time/epoch: 2.1747
EPOCH 40. Progress: 80.0%.
Train loss: 0.0008. Train Acc: 96.0600, Test loss: 0.0009. Test Acc: 95.6000. Time/epoch: 2.1792
EPOCH 50. Progress: 100.0%.
Train loss: 0.0006. Train Acc: 97.1825, Test loss: 0.0007. Test Acc: 96.7400. Time/epoch: 2.3394
Run history:
Accuracy/train | ▁▁▃▃▄▅▃▅▅▅▆▅▆▁▆▆▆▆▇▅▇▇▇▇▇▆▇▇▇█▆▇▇▇█▇▇▇██ |
Accuracy/val | ▁▂▃▄▅▅▄▅▆▅▆▅▆▁▆▆▆▇▇▅▇▇▇▇▇▆█▇▇█▆▇▇▇█▇▇▇██ |
Loss/train | █▇▅▅▄▄▅▄▃▄▃▄▃▇▃▃▃▂▂▃▂▂▂▂▂▃▂▂▂▁▃▂▂▂▁▂▂▂▁▁ |
Loss/val | █▇▅▅▄▄▅▄▃▄▃▄▃█▃▃▃▂▂▃▂▂▂▂▂▃▁▂▂▁▃▂▂▂▁▂▂▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 97.1825 |
Accuracy/val | 96.74 |
Loss/train | 0.00059 |
Loss/val | 0.00069 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_050340-un4qy5px/logs
wandb: Agent Starting Run: 5bv13r7r with config:
wandb: batch_size: 64
wandb: epochs: 10
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_050553-5bv13r7r
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0027. Train Acc: 92.7775, Test loss: 0.0027. Test Acc: 92.5800. Time/epoch: 3.1591
EPOCH 10. Progress: 100.0%.
Train loss: 0.0017. Train Acc: 95.4900, Test loss: 0.0019. Test Acc: 95.2800. Time/epoch: 3.1443
Run history:
Accuracy/train | ▁▄▃▂▇▆▇▇██▆ |
Accuracy/val | ▁▅▃▃▇▆█▇██▆ |
Loss/train | █▄▆▇▂▃▂▂▁▁▃ |
Loss/val | █▄▆▇▁▃▁▂▁▁▃ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 95.49 |
Accuracy/val | 95.28 |
Loss/train | 0.00172 |
Loss/val | 0.00192 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_050553-5bv13r7r/logs
wandb: Agent Starting Run: 1awg7lyq with config:
wandb: batch_size: 64
wandb: epochs: 10
wandb: learning_rate: 0.0003
wandb: optimizer: sgd
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_050643-1awg7lyq
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0026. Train Acc: 92.7900, Test loss: 0.0028. Test Acc: 92.6800. Time/epoch: 3.1191
EPOCH 10. Progress: 100.0%.
Train loss: 0.0014. Train Acc: 96.4925, Test loss: 0.0016. Test Acc: 96.2300. Time/epoch: 2.9118
Run history:
Accuracy/train | ▁▅▆▄▆▇▇▇▆██ |
Accuracy/val | ▁▄▆▄▆▆▇█▆▇█ |
Loss/train | █▅▄▅▃▃▂▂▃▂▁ |
Loss/val | █▅▃▄▂▂▂▁▂▁▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 96.4925 |
Accuracy/val | 96.23 |
Loss/train | 0.0014 |
Loss/val | 0.00158 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_050643-1awg7lyq/logs
wandb: Agent Starting Run: kpzaqqgd with config:
wandb: batch_size: 128
wandb: epochs: 10
wandb: learning_rate: 3e-05
wandb: optimizer: rmsprop
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_050730-kpzaqqgd
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0022. Train Acc: 87.7200, Test loss: 0.0023. Test Acc: 87.8400. Time/epoch: 2.3700
EPOCH 10. Progress: 100.0%.
Train loss: 0.0011. Train Acc: 93.9700, Test loss: 0.0012. Test Acc: 93.9100. Time/epoch: 2.3287
Run history:
Accuracy/train | ▁▃▄▆▆▆███▆█ |
Accuracy/val | ▁▃▄▆▆▆███▅█ |
Loss/train | █▅▅▃▃▃▁▁▂▃▁ |
Loss/val | █▅▄▃▂▃▁▁▁▃▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 93.97 |
Accuracy/val | 93.91 |
Loss/train | 0.00113 |
Loss/val | 0.0012 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_050730-kpzaqqgd/logs
wandb: Agent Starting Run: od3d8ngm with config:
wandb: batch_size: 128
wandb: epochs: 10
wandb: learning_rate: 0.0001
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_050818-od3d8ngm
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0019. Train Acc: 90.1950, Test loss: 0.0019. Test Acc: 90.2800. Time/epoch: 2.3884
EPOCH 10. Progress: 100.0%.
Train loss: 0.0016. Train Acc: 91.3125, Test loss: 0.0016. Test Acc: 91.1800. Time/epoch: 2.3164
Run history:
Accuracy/train | ▇▇▇███▁▇█▇▇ |
Accuracy/val | ▇▇▇███▁▇█▇▇ |
Loss/train | ▂▂▂▁▁▁█▂▁▁▂ |
Loss/val | ▂▂▂▁▁▁█▂▁▁▂ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 91.3125 |
Accuracy/val | 91.18 |
Loss/train | 0.00159 |
Loss/val | 0.00164 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_050818-od3d8ngm/logs
wandb: Agent Starting Run: 5u6w994s with config:
wandb: batch_size: 64
wandb: epochs: 50
wandb: learning_rate: 0.001
wandb: optimizer: sgd
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_050854-5u6w994s
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0099. Train Acc: 74.6150, Test loss: 0.0100. Test Acc: 74.7000. Time/epoch: 3.1162
EPOCH 10. Progress: 20.0%.
Train loss: 0.0033. Train Acc: 92.4725, Test loss: 0.0039. Test Acc: 91.4400. Time/epoch: 3.0775
EPOCH 20. Progress: 40.0%.
Train loss: 0.0025. Train Acc: 95.0675, Test loss: 0.0037. Test Acc: 93.0400. Time/epoch: 3.0610
EPOCH 30. Progress: 60.0%.
Train loss: 0.0023. Train Acc: 95.3075, Test loss: 0.0042. Test Acc: 92.5200. Time/epoch: 2.9474
EPOCH 40. Progress: 80.0%.
Train loss: 0.0009. Train Acc: 98.0850, Test loss: 0.0029. Test Acc: 94.6600. Time/epoch: 2.9260
EPOCH 50. Progress: 100.0%.
Train loss: 0.0008. Train Acc: 98.2650, Test loss: 0.0031. Test Acc: 94.7600. Time/epoch: 2.9314
Run history:
Accuracy/train | ▁▄▃▅▆▆▆▆▆▆▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇█▇█▇█████████ |
Accuracy/val | ▁▄▄▅▆▆▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇█████████ |
Loss/train | █▅▅▄▄▃▃▃▃▃▃▃▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁ |
Loss/val | █▄▅▃▃▂▂▂▂▂▂▂▂▂▂▂▂▂▁▁▂▂▂▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.265 |
Accuracy/val | 94.76 |
Loss/train | 0.00077 |
Loss/val | 0.00307 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_050854-5u6w994s/logs
wandb: Agent Starting Run: 85n9g74f with config:
wandb: batch_size: 64
wandb: epochs: 50
wandb: learning_rate: 0.001
wandb: optimizer: adam
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_051144-85n9g74f
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0024. Train Acc: 93.3700, Test loss: 0.0025. Test Acc: 93.2400. Time/epoch: 3.3243
EPOCH 10. Progress: 20.0%.
Train loss: 0.0017. Train Acc: 96.1225, Test loss: 0.0018. Test Acc: 95.9500. Time/epoch: 3.1756
EPOCH 20. Progress: 40.0%.
Train loss: 0.0012. Train Acc: 97.3975, Test loss: 0.0015. Test Acc: 96.5800. Time/epoch: 3.1586
EPOCH 30. Progress: 60.0%.
Train loss: 0.0010. Train Acc: 97.4225, Test loss: 0.0014. Test Acc: 96.7000. Time/epoch: 3.1708
EPOCH 40. Progress: 80.0%.
Train loss: 0.0012. Train Acc: 97.2975, Test loss: 0.0017. Test Acc: 96.5400. Time/epoch: 3.2793
EPOCH 50. Progress: 100.0%.
Train loss: 0.0008. Train Acc: 98.0125, Test loss: 0.0013. Test Acc: 97.2000. Time/epoch: 3.3170
Run history:
Accuracy/train | ▃▂▃▁▅▅▄▅▆▆▆▅▆▆▅▅▇▆▇▆▇▇▆▇▇▆█▇▅▇▇▆█▇▆▇▇███ |
Accuracy/val | ▃▂▃▁▆▅▅▅▆▇▆▅▆▇▅▅▇▆▇▇█▇▆▇▇▆█▇▅█▇▇██▆█▇███ |
Loss/train | ▆▇▆█▄▅▅▅▄▃▄▄▄▃▄▄▂▄▂▃▂▂▄▂▂▃▂▂▅▂▂▃▁▁▃▂▃▁▁▁ |
Loss/val | ▆▇▅█▃▄▄▄▃▁▃▄▃▃▄▄▂▃▂▃▁▂▄▁▂▃▁▂▆▁▂▂▂▁▃▁▃▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.0125 |
Accuracy/val | 97.2 |
Loss/train | 0.00083 |
Loss/val | 0.00129 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_051144-85n9g74f/logs
wandb: Agent Starting Run: ujqcuip6 with config:
wandb: batch_size: 32
wandb: epochs: 50
wandb: learning_rate: 3e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_051442-ujqcuip6
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0067. Train Acc: 91.5300, Test loss: 0.0069. Test Acc: 91.5500. Time/epoch: 5.0092
EPOCH 10. Progress: 20.0%.
Train loss: 0.0035. Train Acc: 95.7025, Test loss: 0.0039. Test Acc: 95.3100. Time/epoch: 5.0090
EPOCH 20. Progress: 40.0%.
Train loss: 0.0030. Train Acc: 96.2850, Test loss: 0.0035. Test Acc: 95.8500. Time/epoch: 5.1127
EPOCH 30. Progress: 60.0%.
Train loss: 0.0023. Train Acc: 97.2225, Test loss: 0.0028. Test Acc: 96.6000. Time/epoch: 5.1614
EPOCH 40. Progress: 80.0%.
Train loss: 0.0022. Train Acc: 97.3725, Test loss: 0.0028. Test Acc: 96.6000. Time/epoch: 5.1437
EPOCH 50. Progress: 100.0%.
Train loss: 0.0020. Train Acc: 97.5775, Test loss: 0.0027. Test Acc: 96.8700. Time/epoch: 5.1046
Run history:
Accuracy/train | ▁▃▄▄▄▅▄▅▆▆▆▆▅▇▆▅▆▇▇▇▇▇▇▇▇▇▇▇█▇█▆▇███▇███ |
Accuracy/val | ▁▄▄▅▅▅▄▅▆▆▇▆▆▇▆▅▆▇▇▇▇▇▇▇▇▇▇▇█▇█▆▇███▇███ |
Loss/train | █▆▅▅▅▄▅▄▃▃▃▃▃▂▃▄▃▂▂▂▂▂▂▂▂▂▂▂▁▂▁▃▁▁▁▁▂▁▁▁ |
Loss/val | █▆▅▄▄▄▅▄▃▃▃▃▃▂▃▄▃▂▂▂▂▂▂▂▂▂▂▂▁▂▁▃▂▁▁▁▂▁▁▂ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 97.5775 |
Accuracy/val | 96.87 |
Loss/train | 0.00201 |
Loss/val | 0.00273 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_051442-ujqcuip6/logs
wandb: Agent Starting Run: u69utldz with config:
wandb: batch_size: 32
wandb: epochs: 10
wandb: learning_rate: 0.01
wandb: optimizer: adam
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_051917-u69utldz
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0482. Train Acc: 36.8250, Test loss: 0.0480. Test Acc: 37.5400. Time/epoch: 5.1869
EPOCH 10. Progress: 100.0%.
Train loss: 0.0481. Train Acc: 36.8250, Test loss: 0.0480. Test Acc: 37.5400. Time/epoch: 5.1436
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | █▄▇▅▃▃▁▂▁▃▂ |
Loss/val | █▄█▇▆▃▂▁▂▂▃ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.04806 |
Loss/val | 0.04797 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_051917-u69utldz/logs
wandb: Agent Starting Run: xcl9in94 with config:
wandb: batch_size: 32
wandb: epochs: 20
wandb: learning_rate: 1e-05
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_052026-xcl9in94
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0084. Train Acc: 88.6625, Test loss: 0.0084. Test Acc: 88.4500. Time/epoch: 4.7097
EPOCH 10. Progress: 50.0%.
Train loss: 0.0040. Train Acc: 94.9450, Test loss: 0.0042. Test Acc: 95.1500. Time/epoch: 4.6628
EPOCH 20. Progress: 100.0%.
Train loss: 0.0033. Train Acc: 95.9900, Test loss: 0.0036. Test Acc: 96.0000. Time/epoch: 4.8030
Run history:
Accuracy/train | ▁▄▅▆▅▆▆▆▆▇▇▇▇▇▇▇▇████ |
Accuracy/val | ▁▄▅▆▅▆▆▆▇▇▇▇▇▇▇█▇█▇██ |
Loss/train | █▅▄▃▄▃▃▃▂▂▂▂▂▂▂▁▁▁▁▁▁ |
Loss/val | █▅▄▃▄▃▃▃▂▂▂▂▂▂▂▁▁▁▁▁▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 95.99 |
Accuracy/val | 96.0 |
Loss/train | 0.00332 |
Loss/val | 0.00358 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_052026-xcl9in94/logs
wandb: Agent Starting Run: 7cxdc1z4 with config:
wandb: batch_size: 32
wandb: epochs: 50
wandb: learning_rate: 3e-05
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_052224-7cxdc1z4
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0056. Train Acc: 92.7550, Test loss: 0.0057. Test Acc: 92.7800. Time/epoch: 4.7130
EPOCH 10. Progress: 20.0%.
Train loss: 0.0043. Train Acc: 94.2050, Test loss: 0.0045. Test Acc: 94.2900. Time/epoch: 4.6583
EPOCH 20. Progress: 40.0%.
Train loss: 0.0035. Train Acc: 95.8050, Test loss: 0.0036. Test Acc: 95.5500. Time/epoch: 4.6534
EPOCH 30. Progress: 60.0%.
Train loss: 0.0035. Train Acc: 95.9175, Test loss: 0.0037. Test Acc: 95.7400. Time/epoch: 4.8396
EPOCH 40. Progress: 80.0%.
Train loss: 0.0033. Train Acc: 95.9150, Test loss: 0.0034. Test Acc: 95.9900. Time/epoch: 4.8309
EPOCH 50. Progress: 100.0%.
Train loss: 0.0033. Train Acc: 96.0400, Test loss: 0.0034. Test Acc: 95.9800. Time/epoch: 4.8290
Run history:
Accuracy/train | ▁▂▁▄▅▅▃▅▄▆▆▅▇▄▅▇▇▇▇▇▇▇▇▇▇▇▇▅▇█▇▇█▇██▅██▇ |
Accuracy/val | ▁▂▁▄▅▅▃▅▄▆▇▅▆▄▅▇▆▆▇▆▇▇▇▇▇▇▇▅▇▇▆▇█▇██▅██▇ |
Loss/train | █▇▇▄▄▄▆▄▄▃▃▄▃▅▃▂▂▃▂▂▂▂▁▂▂▂▂▃▂▁▂▂▁▂▁▁▄▁▁▂ |
Loss/val | █▇▇▄▄▄▆▄▅▃▃▃▃▅▄▂▂▃▂▂▂▂▁▂▂▂▂▄▂▁▂▂▁▂▁▁▄▁▁▂ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 96.04 |
Accuracy/val | 95.98 |
Loss/train | 0.00333 |
Loss/val | 0.00345 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_052224-7cxdc1z4/logs
wandb: Agent Starting Run: ne93obuu with config:
wandb: batch_size: 32
wandb: epochs: 10
wandb: learning_rate: 0.001
wandb: optimizer: sgd
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_052640-ne93obuu
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0489. Train Acc: 36.8250, Test loss: 0.0488. Test Acc: 37.5400. Time/epoch: 4.6089
EPOCH 10. Progress: 100.0%.
Train loss: 0.0485. Train Acc: 36.8250, Test loss: 0.0484. Test Acc: 37.5400. Time/epoch: 4.6947
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | █▃▁▂▂▂▁▁▂▁▁ |
Loss/val | █▃▁▂▂▂▁▂▂▁▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.04855 |
Loss/val | 0.04845 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_052640-ne93obuu/logs
wandb: Agent Starting Run: y5v8up57 with config:
wandb: batch_size: 32
wandb: epochs: 50
wandb: learning_rate: 1e-05
wandb: optimizer: rmsprop
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_052746-y5v8up57
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0089. Train Acc: 88.8375, Test loss: 0.0090. Test Acc: 88.7100. Time/epoch: 4.7166
EPOCH 10. Progress: 20.0%.
Train loss: 0.0046. Train Acc: 94.0175, Test loss: 0.0049. Test Acc: 93.9500. Time/epoch: 4.6910
EPOCH 20. Progress: 40.0%.
Train loss: 0.0039. Train Acc: 95.2975, Test loss: 0.0042. Test Acc: 95.0700. Time/epoch: 4.6789
EPOCH 30. Progress: 60.0%.
Train loss: 0.0033. Train Acc: 96.0875, Test loss: 0.0037. Test Acc: 95.6800. Time/epoch: 4.8283
EPOCH 40. Progress: 80.0%.
Train loss: 0.0031. Train Acc: 96.1325, Test loss: 0.0036. Test Acc: 95.7300. Time/epoch: 4.8624
EPOCH 50. Progress: 100.0%.
Train loss: 0.0030. Train Acc: 96.2850, Test loss: 0.0034. Test Acc: 95.9300. Time/epoch: 4.7943
Run history:
Accuracy/train | ▁▃▄▄▅▅▆▅▆▆▆▇▇▆▇▇▇▇▇▇▇▇▇██▇▇▇▇█████▇█████ |
Accuracy/val | ▁▃▄▅▅▆▆▆▆▆▆▇▇▇▇▇▇▇▇▇▇▇████▇▇▇█████▇█████ |
Loss/train | █▆▅▄▄▃▃▃▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▁▁▂▂▁▂▁▁▁▁▁▂▁▁▁▁▁ |
Loss/val | █▆▅▄▄▃▃▃▃▃▃▂▂▂▂▂▂▂▂▂▂▂▁▁▁▁▂▁▂▁▁▁▁▁▂▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 96.285 |
Accuracy/val | 95.93 |
Loss/train | 0.00299 |
Loss/val | 0.00341 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_052746-y5v8up57/logs
wandb: Agent Starting Run: vg8m4yn1 with config:
wandb: batch_size: 128
wandb: epochs: 50
wandb: learning_rate: 0.0003
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_053205-vg8m4yn1
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0014. Train Acc: 92.4675, Test loss: 0.0015. Test Acc: 92.3100. Time/epoch: 2.2125
EPOCH 10. Progress: 20.0%.
Train loss: 0.0008. Train Acc: 95.9925, Test loss: 0.0008. Test Acc: 95.8100. Time/epoch: 2.3310
EPOCH 20. Progress: 40.0%.
Train loss: 0.0005. Train Acc: 97.6750, Test loss: 0.0006. Test Acc: 97.1600. Time/epoch: 2.3246
EPOCH 30. Progress: 60.0%.
Train loss: 0.0009. Train Acc: 94.9925, Test loss: 0.0011. Test Acc: 94.3800. Time/epoch: 2.3237
EPOCH 40. Progress: 80.0%.
Train loss: 0.0003. Train Acc: 98.5775, Test loss: 0.0005. Test Acc: 97.5500. Time/epoch: 2.3323
EPOCH 50. Progress: 100.0%.
Train loss: 0.0003. Train Acc: 98.4100, Test loss: 0.0006. Test Acc: 97.1000. Time/epoch: 2.1881
Run history:
Accuracy/train | ▁▂▃▃▄▃▆▂▅▄▆▁▄▂▆▆▇▆▄▆▇▇▃▇▄▆▇█▅▅▆▇█▇█▇▇▇██ |
Accuracy/val | ▂▂▄▄▅▃▇▂▆▅▇▁▄▁▇▇█▇▅▇▇▇▂▇▄▇██▆▆▆▇█▇██████ |
Loss/train | ▇▇▆▅▅▆▃▇▄▅▃█▅▆▃▃▂▃▅▃▂▂▆▂▄▃▂▁▃▄▃▂▁▂▂▂▂▁▁▁ |
Loss/val | ▇▆▅▅▄▆▂▇▃▄▂█▄▇▂▂▁▂▄▂▂▁▆▂▄▂▁▁▄▄▃▂▁▂▂▂▂▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.41 |
Accuracy/val | 97.1 |
Loss/train | 0.00035 |
Loss/val | 0.00064 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_053205-vg8m4yn1/logs
wandb: Agent Starting Run: de5trgo5 with config:
wandb: batch_size: 64
wandb: epochs: 20
wandb: learning_rate: 0.0001
wandb: optimizer: sgd
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_053413-de5trgo5
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0029. Train Acc: 92.6575, Test loss: 0.0031. Test Acc: 92.4200. Time/epoch: 3.1186
EPOCH 10. Progress: 50.0%.
Train loss: 0.0019. Train Acc: 95.2225, Test loss: 0.0020. Test Acc: 95.1000. Time/epoch: 3.0661
EPOCH 20. Progress: 100.0%.
Train loss: 0.0021. Train Acc: 95.0450, Test loss: 0.0021. Test Acc: 94.9100. Time/epoch: 2.9048
Run history:
Accuracy/train | ▁▂▄▄▄▆▆▅▇▆▇▅▅▆▇▆█▇█▅▆ |
Accuracy/val | ▁▂▄▅▄▆▆▅▇▆▇▅▅▆▇▇█▇█▆▆ |
Loss/train | █▇▄▃▄▂▃▄▂▂▂▃▃▃▂▂▁▁▁▃▃ |
Loss/val | █▇▄▃▄▂▃▄▂▂▂▃▃▃▂▂▁▁▁▂▃ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 95.045 |
Accuracy/val | 94.91 |
Loss/train | 0.00205 |
Loss/val | 0.00214 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_053413-de5trgo5/logs
wandb: Agent Starting Run: g3gifqn2 with config:
wandb: batch_size: 64
wandb: epochs: 20
wandb: learning_rate: 0.0001
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_053528-g3gifqn2
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0030. Train Acc: 92.4275, Test loss: 0.0031. Test Acc: 92.4600. Time/epoch: 3.1681
EPOCH 10. Progress: 50.0%.
Train loss: 0.0024. Train Acc: 93.8675, Test loss: 0.0024. Test Acc: 93.7700. Time/epoch: 3.1402
EPOCH 20. Progress: 100.0%.
Train loss: 0.0025. Train Acc: 93.5575, Test loss: 0.0025. Test Acc: 93.3100. Time/epoch: 3.1162
Run history:
Accuracy/train | ▂▂▄▁▄▄▆▆▆▆▅▅▅▆▇▄██▆▇▄ |
Accuracy/val | ▂▃▄▁▅▅▇▆▇▅▅▅▅▆▇▄▇█▇▇▄ |
Loss/train | █▆▅█▄▄▃▃▃▄▄▃▄▄▂▄▂▁▂▁▅ |
Loss/val | █▆▅█▄▄▃▃▂▄▄▃▄▃▂▄▂▁▂▁▄ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 93.5575 |
Accuracy/val | 93.31 |
Loss/train | 0.00248 |
Loss/val | 0.00254 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_053528-g3gifqn2/logs
wandb: Agent Starting Run: gmswq9kf with config:
wandb: batch_size: 128
wandb: epochs: 20
wandb: learning_rate: 1e-05
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_053648-gmswq9kf
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0051. Train Acc: 76.9100, Test loss: 0.0051. Test Acc: 77.2800. Time/epoch: 2.3900
EPOCH 10. Progress: 50.0%.
Train loss: 0.0013. Train Acc: 93.1200, Test loss: 0.0014. Test Acc: 93.0600. Time/epoch: 2.3309
EPOCH 20. Progress: 100.0%.
Train loss: 0.0012. Train Acc: 93.5450, Test loss: 0.0013. Test Acc: 93.5600. Time/epoch: 2.3350
Run history:
Accuracy/train | ▁▆▇▇▇▇███████████████ |
Accuracy/val | ▁▆▇▇▇▇▇██████████████ |
Loss/train | █▃▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▃▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 93.545 |
Accuracy/val | 93.56 |
Loss/train | 0.00124 |
Loss/val | 0.00127 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_053648-gmswq9kf/logs
wandb: Agent Starting Run: jb2q9yd4 with config:
wandb: batch_size: 128
wandb: epochs: 10
wandb: learning_rate: 0.01
wandb: optimizer: adam
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_053750-jb2q9yd4
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0052. Train Acc: 73.2100, Test loss: 0.0053. Test Acc: 73.5900. Time/epoch: 2.4537
EPOCH 10. Progress: 100.0%.
Train loss: 0.0072. Train Acc: 70.5600, Test loss: 0.0073. Test Acc: 71.1400. Time/epoch: 2.3998
Run history:
Accuracy/train | ▇▆█▇█▇█▁▇▄▇ |
Accuracy/val | ▇▆███▇█▁▇▄▇ |
Loss/train | ▂▂▁▃▂▃▂█▂▇▅ |
Loss/val | ▂▂▁▃▂▃▂█▂▆▅ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 70.56 |
Accuracy/val | 71.14 |
Loss/train | 0.00724 |
Loss/val | 0.00728 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_053750-jb2q9yd4/logs
wandb: Agent Starting Run: 3jylhr2x with config:
wandb: batch_size: 32
wandb: epochs: 20
wandb: learning_rate: 0.01
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_053830-3jylhr2x
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0481. Train Acc: 36.8250, Test loss: 0.0480. Test Acc: 37.5400. Time/epoch: 4.6760
EPOCH 10. Progress: 50.0%.
Train loss: 0.0480. Train Acc: 36.8250, Test loss: 0.0479. Test Acc: 37.5400. Time/epoch: 4.6448
EPOCH 20. Progress: 100.0%.
Train loss: 0.0481. Train Acc: 36.8250, Test loss: 0.0480. Test Acc: 37.5400. Time/epoch: 4.8188
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | ▄█▃▅▂▁▃▃▃▂▁▁▂▁▃▁▃▁▅▄▂ |
Loss/val | ▄█▄▅▂▁▆▄▂▂▂▂▃▂▃▁▂▂▆▂▂ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.04805 |
Loss/val | 0.04795 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_053830-3jylhr2x/logs
wandb: Agent Starting Run: i6x2c5j4 with config:
wandb: batch_size: 32
wandb: epochs: 10
wandb: learning_rate: 3e-05
wandb: optimizer: sgd
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_054022-i6x2c5j4
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0265. Train Acc: 74.0550, Test loss: 0.0264. Test Acc: 74.5100. Time/epoch: 4.5972
EPOCH 10. Progress: 100.0%.
Train loss: 0.0039. Train Acc: 95.0675, Test loss: 0.0041. Test Acc: 94.7700. Time/epoch: 4.5556
Run history:
Accuracy/train | ▁▅▆▇▇▇▇████ |
Accuracy/val | ▁▄▇▆▇▇▇████ |
Loss/train | █▃▂▂▂▁▁▁▁▁▁ |
Loss/val | █▃▂▂▂▁▁▁▁▁▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 95.0675 |
Accuracy/val | 94.77 |
Loss/train | 0.00392 |
Loss/val | 0.00405 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_054022-i6x2c5j4/logs
wandb: Agent Starting Run: zdfc2kwu with config:
wandb: batch_size: 64
wandb: epochs: 10
wandb: learning_rate: 0.0001
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_054128-zdfc2kwu
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0032. Train Acc: 91.2025, Test loss: 0.0034. Test Acc: 90.8300. Time/epoch: 3.1622
EPOCH 10. Progress: 100.0%.
Train loss: 0.0012. Train Acc: 97.3625, Test loss: 0.0013. Test Acc: 97.1700. Time/epoch: 3.0038
Run history:
Accuracy/train | ▁▃▅▅▆▆▆▆▅▆█ |
Accuracy/val | ▁▄▅▅▆▆▆▆▅▆█ |
Loss/train | █▆▄▄▃▃▃▃▄▃▁ |
Loss/val | █▆▄▄▃▂▃▃▄▂▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 97.3625 |
Accuracy/val | 97.17 |
Loss/train | 0.00117 |
Loss/val | 0.00129 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_054128-zdfc2kwu/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: isecmdyz with config:
wandb: batch_size: 128
wandb: epochs: 50
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_054225-isecmdyz
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0014. Train Acc: 92.6600, Test loss: 0.0015. Test Acc: 92.6600. Time/epoch: 2.4375
EPOCH 10. Progress: 20.0%.
Train loss: 0.0007. Train Acc: 96.9500, Test loss: 0.0007. Test Acc: 96.7800. Time/epoch: 2.4299
EPOCH 20. Progress: 40.0%.
Train loss: 0.0005. Train Acc: 97.4725, Test loss: 0.0006. Test Acc: 96.8700. Time/epoch: 2.2712
EPOCH 30. Progress: 60.0%.
Train loss: 0.0004. Train Acc: 98.1950, Test loss: 0.0006. Test Acc: 97.3600. Time/epoch: 2.2906
EPOCH 40. Progress: 80.0%.
Train loss: 0.0004. Train Acc: 97.8750, Test loss: 0.0007. Test Acc: 96.9300. Time/epoch: 2.4031
EPOCH 50. Progress: 100.0%.
Train loss: 0.0003. Train Acc: 98.4775, Test loss: 0.0007. Test Acc: 97.1900. Time/epoch: 2.4000
Run history:
Accuracy/train | ▁▂▃▄▄▅▅▄▆▅▆▆▅▆▅▆▆▇▇▇▇▇▇▇▇█▆▆▇▇█▆▇▇▇▇███▇ |
Accuracy/val | ▁▂▃▄▄▅▅▄▆▆▆▆▆▇▅▇▇▇▇▇▇▇▇█▇█▆▆▇▇█▆▇▇▇▇███▇ |
Loss/train | █▇▆▅▅▄▅▅▄▄▃▃▄▃▄▃▃▂▂▂▃▂▂▂▂▁▃▃▂▂▂▃▂▂▂▁▁▁▁▂ |
Loss/val | █▇▆▅▅▃▄▄▃▃▂▃▃▂▄▂▂▂▂▂▂▂▂▁▂▁▃▃▂▁▁▃▂▃▂▂▁▁▁▃ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.4775 |
Accuracy/val | 97.19 |
Loss/train | 0.00033 |
Loss/val | 0.00071 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_054225-isecmdyz/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: z8gmtpb5 with config:
wandb: batch_size: 128
wandb: epochs: 10
wandb: learning_rate: 3e-05
wandb: optimizer: sgd
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_054447-z8gmtpb5
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0047. Train Acc: 75.2350, Test loss: 0.0047. Test Acc: 75.3900. Time/epoch: 2.1857
EPOCH 10. Progress: 100.0%.
Train loss: 0.0019. Train Acc: 89.2050, Test loss: 0.0020. Test Acc: 89.4500. Time/epoch: 2.2985
Run history:
Accuracy/train | ▁▄▅▆▆▇▇█▇██ |
Accuracy/val | ▁▄▅▆▆▇▇█▇██ |
Loss/train | █▅▄▄▃▂▂▂▂▁▁ |
Loss/val | █▅▄▄▃▂▂▂▂▁▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 89.205 |
Accuracy/val | 89.45 |
Loss/train | 0.00194 |
Loss/val | 0.002 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_054447-z8gmtpb5/logs
wandb: Agent Starting Run: rrka9xc6 with config:
wandb: batch_size: 128
wandb: epochs: 50
wandb: learning_rate: 0.001
wandb: optimizer: adam
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_054528-rrka9xc6
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0016. Train Acc: 90.9850, Test loss: 0.0017. Test Acc: 90.8500. Time/epoch: 2.2980
EPOCH 10. Progress: 20.0%.
Train loss: 0.0008. Train Acc: 95.9450, Test loss: 0.0009. Test Acc: 95.8100. Time/epoch: 2.4216
EPOCH 20. Progress: 40.0%.
Train loss: 0.0005. Train Acc: 97.3225, Test loss: 0.0007. Test Acc: 96.8300. Time/epoch: 2.4150
EPOCH 30. Progress: 60.0%.
Train loss: 0.0009. Train Acc: 95.5575, Test loss: 0.0012. Test Acc: 95.2200. Time/epoch: 2.3986
EPOCH 40. Progress: 80.0%.
Train loss: 0.0005. Train Acc: 97.7025, Test loss: 0.0007. Test Acc: 96.8500. Time/epoch: 2.2496
EPOCH 50. Progress: 100.0%.
Train loss: 0.0010. Train Acc: 94.8900, Test loss: 0.0014. Test Acc: 94.0500. Time/epoch: 2.2725
Run history:
Accuracy/train | ▁▄▁▄▃▄▆▅▆▄▆▇▆▇▂▇▇▇▆▇▇▇▆▇▅▇▅▇▆██▇▇▇█▇██▇▅ |
Accuracy/val | ▁▄▁▄▄▅▇▅▆▄▆▇▇▇▂▇▇▇▇▇█▇▇▇▆▇▅▇▆██▇▇▇█▇██▇▄ |
Loss/train | █▅█▅▆▅▃▄▄▇▃▂▃▂█▂▂▃▃▃▂▂▃▂▄▂▄▂▃▁▁▂▂▂▁▂▁▁▁▄ |
Loss/val | ▇▅▇▅▆▄▂▄▃▆▃▂▂▂█▂▁▂▂▂▁▂▃▁▄▃▄▂▄▁▁▂▂▂▁▃▁▂▂▆ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 94.89 |
Accuracy/val | 94.05 |
Loss/train | 0.00099 |
Loss/val | 0.00142 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_054528-rrka9xc6/logs
wandb: Agent Starting Run: c90l9ve2 with config:
wandb: batch_size: 64
wandb: epochs: 50
wandb: learning_rate: 1e-05
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_054741-c90l9ve2
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0055. Train Acc: 86.3700, Test loss: 0.0055. Test Acc: 86.4100. Time/epoch: 3.1368
EPOCH 10. Progress: 20.0%.
Train loss: 0.0025. Train Acc: 93.6250, Test loss: 0.0026. Test Acc: 93.4500. Time/epoch: 3.0174
EPOCH 20. Progress: 40.0%.
Train loss: 0.0023. Train Acc: 94.3850, Test loss: 0.0024. Test Acc: 94.2100. Time/epoch: 2.9791
EPOCH 30. Progress: 60.0%.
Train loss: 0.0021. Train Acc: 94.6550, Test loss: 0.0022. Test Acc: 94.7100. Time/epoch: 3.1562
EPOCH 40. Progress: 80.0%.
Train loss: 0.0019. Train Acc: 95.2050, Test loss: 0.0021. Test Acc: 95.1700. Time/epoch: 3.1645
EPOCH 50. Progress: 100.0%.
Train loss: 0.0019. Train Acc: 95.3175, Test loss: 0.0020. Test Acc: 95.1600. Time/epoch: 3.1532
Run history:
Accuracy/train | ▁▃▄▅▆▆▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇█▇██▇▇█████████ |
Accuracy/val | ▁▃▄▅▆▆▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇█▇▇█▇██▇▇█████████ |
Loss/train | █▅▄▄▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▁▂▁▁▁▁▁▂▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▅▅▄▃▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▂▂▁▂▁▁▁▁▁▂▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 95.3175 |
Accuracy/val | 95.16 |
Loss/train | 0.00193 |
Loss/val | 0.00204 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_054741-c90l9ve2/logs
wandb: Agent Starting Run: zad7mg7r with config:
wandb: batch_size: 64
wandb: epochs: 20
wandb: learning_rate: 0.0001
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_055034-zad7mg7r
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0031. Train Acc: 91.4550, Test loss: 0.0032. Test Acc: 91.5800. Time/epoch: 3.1675
EPOCH 10. Progress: 50.0%.
Train loss: 0.0014. Train Acc: 96.3650, Test loss: 0.0016. Test Acc: 95.9700. Time/epoch: 3.1474
EPOCH 20. Progress: 100.0%.
Train loss: 0.0010. Train Acc: 97.5000, Test loss: 0.0012. Test Acc: 97.0200. Time/epoch: 3.1174
Run history:
Accuracy/train | ▁▄▁▅▄▄▅▆▆▆▇▇█▇▄█▆▆███ |
Accuracy/val | ▁▄▁▅▄▄▅▆▆▆▇▇▇▇▃█▆▆███ |
Loss/train | █▆█▄▅▅▄▃▃▃▂▂▂▂▆▂▃▃▁▁▁ |
Loss/val | █▆█▄▅▅▃▃▃▃▂▂▂▂▆▂▃▃▁▁▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 97.5 |
Accuracy/val | 97.02 |
Loss/train | 0.00104 |
Loss/val | 0.00122 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_055034-zad7mg7r/logs
wandb: Agent Starting Run: rg05su6p with config:
wandb: batch_size: 32
wandb: epochs: 20
wandb: learning_rate: 0.001
wandb: optimizer: rmsprop
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_055153-rg05su6p
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0146. Train Acc: 78.8775, Test loss: 0.0147. Test Acc: 79.2400. Time/epoch: 4.8435
EPOCH 10. Progress: 50.0%.
Train loss: 0.0060. Train Acc: 93.6275, Test loss: 0.0063. Test Acc: 93.2900. Time/epoch: 4.8304
EPOCH 20. Progress: 100.0%.
Train loss: 0.0093. Train Acc: 91.3300, Test loss: 0.0099. Test Acc: 91.2600. Time/epoch: 4.7901
Run history:
Accuracy/train | ▁▄▆▇▆▇████▇███▇█▇▇██▆ |
Accuracy/val | ▁▄▆▇▆▇████▇███▇██▇██▆ |
Loss/train | █▅▃▂▂▂▁▁▁▁▂▁▁▁▂▁▁▂▁▁▄ |
Loss/val | █▅▃▂▂▂▁▁▁▁▂▁▁▂▂▁▁▂▁▁▅ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 91.33 |
Accuracy/val | 91.26 |
Loss/train | 0.00934 |
Loss/val | 0.00989 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_055153-rg05su6p/logs
wandb: Agent Starting Run: shvybvl5 with config:
wandb: batch_size: 32
wandb: epochs: 20
wandb: learning_rate: 1e-05
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_055350-shvybvl5
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0117. Train Acc: 87.0625, Test loss: 0.0120. Test Acc: 86.7000. Time/epoch: 4.8438
EPOCH 10. Progress: 50.0%.
Train loss: 0.0044. Train Acc: 94.2725, Test loss: 0.0045. Test Acc: 93.9900. Time/epoch: 4.8448
EPOCH 20. Progress: 100.0%.
Train loss: 0.0037. Train Acc: 95.1750, Test loss: 0.0038. Test Acc: 95.1000. Time/epoch: 4.8356
Run history:
Accuracy/train | ▁▃▄▅▆▆▇▇▇▆▇▇▇▇██▇█▇██ |
Accuracy/val | ▁▃▅▅▆▆▇▇▇▇▇▇▇████████ |
Loss/train | █▅▄▄▃▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁ |
Loss/val | █▅▄▃▃▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 95.175 |
Accuracy/val | 95.1 |
Loss/train | 0.00365 |
Loss/val | 0.00384 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_055350-shvybvl5/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: mdyofjir with config:
wandb: batch_size: 32
wandb: epochs: 20
wandb: learning_rate: 1e-05
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_055553-mdyofjir
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0146. Train Acc: 79.2575, Test loss: 0.0144. Test Acc: 79.6700. Time/epoch: 4.6721
EPOCH 10. Progress: 50.0%.
Train loss: 0.0060. Train Acc: 91.8325, Test loss: 0.0061. Test Acc: 92.0000. Time/epoch: 4.8439
EPOCH 20. Progress: 100.0%.
Train loss: 0.0046. Train Acc: 93.8375, Test loss: 0.0047. Test Acc: 94.1400. Time/epoch: 4.8424
Run history:
Accuracy/train | ▁▅▅▆▅▆▆▆▇▇▇▇▇▇▇██████ |
Accuracy/val | ▁▅▅▅▅▆▆▆▇▇▇▇▇█▇██████ |
Loss/train | █▅▄▄▃▃▃▂▂▂▂▂▂▁▂▁▁▁▁▁▁ |
Loss/val | █▅▄▄▃▃▃▃▂▂▂▂▂▁▂▁▁▁▁▁▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 93.8375 |
Accuracy/val | 94.14 |
Loss/train | 0.00459 |
Loss/val | 0.0047 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_055553-mdyofjir/logs
wandb: Agent Starting Run: h09ask4v with config:
wandb: batch_size: 32
wandb: epochs: 10
wandb: learning_rate: 0.0001
wandb: optimizer: adam
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_055749-h09ask4v
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0051. Train Acc: 93.2375, Test loss: 0.0052. Test Acc: 93.3900. Time/epoch: 4.9953
EPOCH 10. Progress: 100.0%.
Train loss: 0.0024. Train Acc: 97.1550, Test loss: 0.0027. Test Acc: 96.7500. Time/epoch: 5.1233
Run history:
Accuracy/train | ▁▄▄▆▅▆▇▇▆▇█ |
Accuracy/val | ▁▅▄▆▅▇▇▇▆██ |
Loss/train | █▅▅▃▄▃▂▂▃▁▁ |
Loss/val | █▅▅▃▄▃▂▂▃▂▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 97.155 |
Accuracy/val | 96.75 |
Loss/train | 0.00243 |
Loss/val | 0.00274 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_055749-h09ask4v/logs
wandb: Agent Starting Run: nj199acm with config:
wandb: batch_size: 32
wandb: epochs: 50
wandb: learning_rate: 0.0001
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_055901-nj199acm
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0049. Train Acc: 93.6950, Test loss: 0.0051. Test Acc: 93.5200. Time/epoch: 4.6779
EPOCH 10. Progress: 20.0%.
Train loss: 0.0026. Train Acc: 96.6575, Test loss: 0.0031. Test Acc: 96.4600. Time/epoch: 4.6789
EPOCH 20. Progress: 40.0%.
Train loss: 0.0015. Train Acc: 98.2975, Test loss: 0.0025. Test Acc: 97.4100. Time/epoch: 4.7833
EPOCH 30. Progress: 60.0%.
Train loss: 0.0016. Train Acc: 98.0500, Test loss: 0.0030. Test Acc: 96.9400. Time/epoch: 4.8049
EPOCH 40. Progress: 80.0%.
Train loss: 0.0018. Train Acc: 97.8700, Test loss: 0.0036. Test Acc: 96.6100. Time/epoch: 4.7920
EPOCH 50. Progress: 100.0%.
Train loss: 0.0008. Train Acc: 99.0750, Test loss: 0.0028. Test Acc: 97.3200. Time/epoch: 4.6852
Run history:
Accuracy/train | ▂▁▂▅▄▅▆▆▅▆▆▅▆▆▆▇▇▇▆▇▇▇▆▇▇▆▆▇▇▇▇█████████ |
Accuracy/val | ▃▁▂▆▅▆▇▇▇▇▇▆▇▇▇▇██▇▇██▇█▇▇▇▇█▇▇█████████ |
Loss/train | ▆█▇▄▅▄▃▃▃▃▃▄▃▃▃▂▂▂▂▂▂▂▂▁▂▃▃▂▂▂▂▁▁▁▁▁▁▁▁▁ |
Loss/val | ▆█▇▃▄▃▂▂▂▂▂▃▂▂▂▁▁▂▂▁▁▁▂▁▂▃▃▂▂▃▂▁▁▂▂▂▂▂▁▂ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 99.075 |
Accuracy/val | 97.32 |
Loss/train | 0.0008 |
Loss/val | 0.0028 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_055901-nj199acm/logs
wandb: Agent Starting Run: yxfiee1z with config:
wandb: batch_size: 64
wandb: epochs: 20
wandb: learning_rate: 0.0001
wandb: optimizer: adam
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_060319-yxfiee1z
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0027. Train Acc: 92.7600, Test loss: 0.0027. Test Acc: 92.4900. Time/epoch: 3.3177
EPOCH 10. Progress: 50.0%.
Train loss: 0.0015. Train Acc: 96.2775, Test loss: 0.0016. Test Acc: 95.8700. Time/epoch: 3.3097
EPOCH 20. Progress: 100.0%.
Train loss: 0.0009. Train Acc: 97.9275, Test loss: 0.0012. Test Acc: 97.2500. Time/epoch: 3.1353
Run history:
Accuracy/train | ▁▃▃▄▃▄▅▅▆▆▆▆▇▇▇▇▇▇▆██ |
Accuracy/val | ▁▃▄▅▃▅▅▅▆▇▆▇▇▇▇▇▇▇▇██ |
Loss/train | █▆▆▅▆▄▅▄▃▃▃▃▂▂▂▂▂▂▂▁▁ |
Loss/val | █▆▅▄▅▄▄▄▂▂▃▂▂▂▂▂▂▁▂▁▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 97.9275 |
Accuracy/val | 97.25 |
Loss/train | 0.0009 |
Loss/val | 0.00121 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_060319-yxfiee1z/logs
wandb: Agent Starting Run: kyg2yqo0 with config:
wandb: batch_size: 32
wandb: epochs: 10
wandb: learning_rate: 3e-05
wandb: optimizer: sgd
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_060441-kyg2yqo0
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0073. Train Acc: 91.1650, Test loss: 0.0074. Test Acc: 91.1900. Time/epoch: 4.7153
EPOCH 10. Progress: 100.0%.
Train loss: 0.0038. Train Acc: 95.3275, Test loss: 0.0040. Test Acc: 95.2200. Time/epoch: 4.5452
Run history:
Accuracy/train | ▂▄▁▄▆▆▇████ |
Accuracy/val | ▂▃▁▄▆▆▇████ |
Loss/train | █▅▇▅▃▃▂▁▁▁▁ |
Loss/val | █▅▇▅▃▃▂▁▁▁▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 95.3275 |
Accuracy/val | 95.22 |
Loss/train | 0.00382 |
Loss/val | 0.00399 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_060441-kyg2yqo0/logs
wandb: Agent Starting Run: 9ek9v3id with config:
wandb: batch_size: 64
wandb: epochs: 50
wandb: learning_rate: 0.01
wandb: optimizer: adam
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_060547-9ek9v3id
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0240. Test Acc: 37.5400. Time/epoch: 3.3223
EPOCH 10. Progress: 20.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 3.1278
EPOCH 20. Progress: 40.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 3.1250
EPOCH 30. Progress: 60.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 3.2855
EPOCH 40. Progress: 80.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 3.2736
EPOCH 50. Progress: 100.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0240. Test Acc: 37.5400. Time/epoch: 3.2960
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | ▂▄▄▆▄▂▁█▂▂▁▂▂▂▁▃▂▂▂▂▄▄▂▁▄▄▃▂▂▂▂▂▄▃▂▂▁▃▂▂ |
Loss/val | ▃▄▄▂▆▄▁█▃▃▁▄▅▄▃▅▄▃▄▂▃▄▄▂█▄▃▄▁▂▃▁▂▄▂▄▁▅▃▂ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.02402 |
Loss/val | 0.02404 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_060547-9ek9v3id/logs
wandb: Agent Starting Run: 02r18sv0 with config:
wandb: batch_size: 64
wandb: epochs: 10
wandb: learning_rate: 3e-05
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_060845-02r18sv0
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0042. Train Acc: 86.3800, Test loss: 0.0042. Test Acc: 86.6200. Time/epoch: 3.1642
EPOCH 10. Progress: 100.0%.
Train loss: 0.0018. Train Acc: 95.2325, Test loss: 0.0018. Test Acc: 95.3300. Time/epoch: 3.1758
Run history:
Accuracy/train | ▁▅▅▆▇▇▇▇▇██ |
Accuracy/val | ▁▅▅▇▇▇▇▇▇██ |
Loss/train | █▅▅▃▂▂▂▂▁▁▁ |
Loss/val | █▅▅▃▂▂▂▂▁▁▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 95.2325 |
Accuracy/val | 95.33 |
Loss/train | 0.00178 |
Loss/val | 0.00183 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_060845-02r18sv0/logs
wandb: Agent Starting Run: 1a72zmpf with config:
wandb: batch_size: 64
wandb: epochs: 10
wandb: learning_rate: 0.0001
wandb: optimizer: adam
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_060930-1a72zmpf
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0027. Train Acc: 92.8100, Test loss: 0.0028. Test Acc: 93.1900. Time/epoch: 3.1751
EPOCH 10. Progress: 100.0%.
Train loss: 0.0013. Train Acc: 96.8000, Test loss: 0.0015. Test Acc: 96.3400. Time/epoch: 3.3046
Run history:
Accuracy/train | ▁▃▄▄▅▆▇▆▇▇█ |
Accuracy/val | ▁▂▄▅▆▆▇▆▇██ |
Loss/train | █▆▅▄▄▃▂▂▂▁▁ |
Loss/val | █▆▅▄▄▃▂▂▂▂▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 96.8 |
Accuracy/val | 96.34 |
Loss/train | 0.00133 |
Loss/val | 0.00152 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_060930-1a72zmpf/logs
wandb: Agent Starting Run: z882e1y9 with config:
wandb: batch_size: 32
wandb: epochs: 20
wandb: learning_rate: 0.01
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_061018-z882e1y9
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0485. Train Acc: 36.8250, Test loss: 0.0484. Test Acc: 37.5400. Time/epoch: 4.6977
EPOCH 10. Progress: 50.0%.
Train loss: 0.0487. Train Acc: 36.8250, Test loss: 0.0486. Test Acc: 37.5400. Time/epoch: 4.6564
EPOCH 20. Progress: 100.0%.
Train loss: 0.0487. Train Acc: 36.8250, Test loss: 0.0486. Test Acc: 37.5400. Time/epoch: 4.7864
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | ▂▄▁▅▅▅▅▅█▆▅▇▇▆▂▂▆▆▄▆▅ |
Loss/val | ▃▅▁▆▅▅▆▅█▇▆▇▇▆▂▂▇▆▄▆▆ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.04867 |
Loss/val | 0.04863 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_061018-z882e1y9/logs
wandb: Agent Starting Run: csip2xoo with config:
wandb: batch_size: 64
wandb: epochs: 10
wandb: learning_rate: 0.0003
wandb: optimizer: sgd
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_061213-csip2xoo
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0032. Train Acc: 90.6875, Test loss: 0.0033. Test Acc: 90.7100. Time/epoch: 2.9392
EPOCH 10. Progress: 100.0%.
Train loss: 0.0014. Train Acc: 96.7025, Test loss: 0.0015. Test Acc: 96.3700. Time/epoch: 2.9506
Run history:
Accuracy/train | ▁▆▅▅▇▇▇▇███ |
Accuracy/val | ▁▆▅▅▇▇▆▆███ |
Loss/train | █▄▅▄▂▂▃▂▁▁▁ |
Loss/val | █▄▅▄▂▂▂▂▁▁▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 96.7025 |
Accuracy/val | 96.37 |
Loss/train | 0.00139 |
Loss/val | 0.0015 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_061213-csip2xoo/logs
wandb: Agent Starting Run: 8l0v5gap with config:
wandb: batch_size: 128
wandb: epochs: 20
wandb: learning_rate: 3e-05
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_061300-8l0v5gap
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0020. Train Acc: 89.7825, Test loss: 0.0021. Test Acc: 89.6000. Time/epoch: 2.3561
EPOCH 10. Progress: 50.0%.
Train loss: 0.0013. Train Acc: 93.0475, Test loss: 0.0014. Test Acc: 92.9100. Time/epoch: 2.1859
EPOCH 20. Progress: 100.0%.
Train loss: 0.0012. Train Acc: 93.8225, Test loss: 0.0012. Test Acc: 93.7300. Time/epoch: 2.1930
Run history:
Accuracy/train | ▁▃▁▄▄▅▄▆▄▂▅▇▇▇▆▆▇▆▅█▆ |
Accuracy/val | ▁▂▁▃▃▄▄▅▄▃▅▇▇▇▆▆▇▆▅█▆ |
Loss/train | █▆▇▄▄▄▃▃▄▆▃▂▂▂▂▂▁▂▃▁▂ |
Loss/val | █▆▇▄▅▄▄▃▄▅▃▂▂▂▂▂▁▂▃▁▂ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 93.8225 |
Accuracy/val | 93.73 |
Loss/train | 0.00116 |
Loss/val | 0.00121 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_061300-8l0v5gap/logs
wandb: Agent Starting Run: y27npk0v with config:
wandb: batch_size: 128
wandb: epochs: 50
wandb: learning_rate: 1e-05
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_061400-y27npk0v
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0046. Train Acc: 78.8800, Test loss: 0.0046. Test Acc: 78.6800. Time/epoch: 2.3478
EPOCH 10. Progress: 20.0%.
Train loss: 0.0014. Train Acc: 93.1050, Test loss: 0.0014. Test Acc: 93.1500. Time/epoch: 2.1986
EPOCH 20. Progress: 40.0%.
Train loss: 0.0012. Train Acc: 93.8950, Test loss: 0.0012. Test Acc: 93.8100. Time/epoch: 2.1873
EPOCH 30. Progress: 60.0%.
Train loss: 0.0011. Train Acc: 94.6275, Test loss: 0.0011. Test Acc: 94.8700. Time/epoch: 2.3376
EPOCH 40. Progress: 80.0%.
Train loss: 0.0010. Train Acc: 94.8450, Test loss: 0.0011. Test Acc: 95.0900. Time/epoch: 2.3416
EPOCH 50. Progress: 100.0%.
Train loss: 0.0011. Train Acc: 94.4350, Test loss: 0.0011. Test Acc: 94.5800. Time/epoch: 2.2144
Run history:
Accuracy/train | ▁▃▄▅▆▇▇▇▇▇▇▇▇█▇█▇███████████████████████ |
Accuracy/val | ▁▃▄▅▆▇▇▇▇▇▇▇▇█▇█▇███████████████████████ |
Loss/train | █▅▄▃▂▂▂▂▂▂▂▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▅▄▃▂▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 94.435 |
Accuracy/val | 94.58 |
Loss/train | 0.00107 |
Loss/val | 0.00112 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_061400-y27npk0v/logs
wandb: Agent Starting Run: t5gq6iyz with config:
wandb: batch_size: 32
wandb: epochs: 10
wandb: learning_rate: 0.001
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_061612-t5gq6iyz
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0175. Train Acc: 71.7025, Test loss: 0.0174. Test Acc: 72.2000. Time/epoch: 4.8500
EPOCH 10. Progress: 100.0%.
Train loss: 0.0085. Train Acc: 90.8825, Test loss: 0.0086. Test Acc: 90.6900. Time/epoch: 4.8059
Run history:
Accuracy/train | ▁▄▆▇▅▆▇████ |
Accuracy/val | ▁▃▆▇▅▆▇████ |
Loss/train | █▄▂▃▂▂▁▂▂▁▁ |
Loss/val | █▄▂▃▂▂▁▂▂▁▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 90.8825 |
Accuracy/val | 90.69 |
Loss/train | 0.00855 |
Loss/val | 0.00864 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_061612-t5gq6iyz/logs
wandb: Agent Starting Run: 04lbmtm5 with config:
wandb: batch_size: 32
wandb: epochs: 50
wandb: learning_rate: 0.0001
wandb: optimizer: sgd
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_061718-04lbmtm5
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0058. Train Acc: 92.4725, Test loss: 0.0062. Test Acc: 92.3100. Time/epoch: 4.7041
EPOCH 10. Progress: 20.0%.
Train loss: 0.0039. Train Acc: 94.6325, Test loss: 0.0043. Test Acc: 94.3700. Time/epoch: 4.6776
EPOCH 20. Progress: 40.0%.
Train loss: 0.0031. Train Acc: 95.7775, Test loss: 0.0034. Test Acc: 95.6400. Time/epoch: 4.7065
EPOCH 30. Progress: 60.0%.
Train loss: 0.0025. Train Acc: 96.8075, Test loss: 0.0029. Test Acc: 96.3600. Time/epoch: 4.5418
EPOCH 40. Progress: 80.0%.
Train loss: 0.0026. Train Acc: 96.7625, Test loss: 0.0030. Test Acc: 96.2800. Time/epoch: 4.6772
EPOCH 50. Progress: 100.0%.
Train loss: 0.0021. Train Acc: 97.2800, Test loss: 0.0026. Test Acc: 96.7600. Time/epoch: 4.6874
Run history:
Accuracy/train | ▂▂▃▃▄▁▅▅▄▅▆▆▆▇▇▆▆▇▇▇▇▆▇▇▇▇▆▇▇█▇▇▇▇█▆▆▆▆█ |
Accuracy/val | ▂▂▃▃▅▁▅▅▄▅▆▆▆▇▇▆▆▇▇▇▇▆▇█▇▇▆▇██▇▇▇▇█▆▆▆▆▇ |
Loss/train | ▇▇▆▆▅█▃▄▄▄▃▃▃▂▂▃▃▂▂▂▂▃▂▂▂▂▃▂▂▁▂▂▂▂▁▃▃▂▃▁ |
Loss/val | ▇▇▆▆▅█▃▄▄▄▃▃▃▂▂▃▃▂▂▂▂▃▂▁▂▂▃▁▂▁▂▂▂▂▁▃▃▃▃▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 97.28 |
Accuracy/val | 96.76 |
Loss/train | 0.0021 |
Loss/val | 0.00255 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_061718-04lbmtm5/logs
wandb: Agent Starting Run: hgv4yplr with config:
wandb: batch_size: 32
wandb: epochs: 20
wandb: learning_rate: 0.001
wandb: optimizer: sgd
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_062128-hgv4yplr
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0208. Train Acc: 75.5100, Test loss: 0.0206. Test Acc: 76.1200. Time/epoch: 4.5618
EPOCH 10. Progress: 50.0%.
Train loss: 0.0072. Train Acc: 91.9125, Test loss: 0.0080. Test Acc: 91.0600. Time/epoch: 4.5647
EPOCH 20. Progress: 100.0%.
Train loss: 0.0067. Train Acc: 92.4275, Test loss: 0.0081. Test Acc: 91.1600. Time/epoch: 4.6899
Run history:
Accuracy/train | ▁▃▄▅▆▆▆▇▇▆▇▇█▇█▇▇▇█▆█ |
Accuracy/val | ▁▃▅▅▇▇▇▇█▇█▇███▇▇▇█▇█ |
Loss/train | █▄▄▃▃▂▂▂▂▂▁▂▁▁▁▂▂▁▁▂▁ |
Loss/val | █▄▃▂▂▂▂▂▁▂▁▂▁▁▁▁▂▁▁▂▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 92.4275 |
Accuracy/val | 91.16 |
Loss/train | 0.00669 |
Loss/val | 0.00812 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_062128-hgv4yplr/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: 1557bxks with config:
wandb: batch_size: 64
wandb: epochs: 10
wandb: learning_rate: 0.001
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_062327-1557bxks
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0055. Train Acc: 83.4050, Test loss: 0.0056. Test Acc: 83.7600. Time/epoch: 3.0134
EPOCH 10. Progress: 100.0%.
Train loss: 0.0032. Train Acc: 91.2975, Test loss: 0.0035. Test Acc: 90.7600. Time/epoch: 2.9857
Run history:
Accuracy/train | ▁▂▂▁▅▅▇▇█▄▆ |
Accuracy/val | ▁▂▂▁▅▅▇▇█▅▆ |
Loss/train | ▅▆▅█▃▃▂▂▁▃▂ |
Loss/val | ▅▆▅█▃▃▂▂▁▃▂ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 91.2975 |
Accuracy/val | 90.76 |
Loss/train | 0.00322 |
Loss/val | 0.00353 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_062327-1557bxks/logs
wandb: Agent Starting Run: itxvvi4e with config:
wandb: batch_size: 32
wandb: epochs: 50
wandb: learning_rate: 3e-05
wandb: optimizer: sgd
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_062412-itxvvi4e
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0074. Train Acc: 90.0900, Test loss: 0.0076. Test Acc: 90.0700. Time/epoch: 4.7231
EPOCH 10. Progress: 20.0%.
Train loss: 0.0041. Train Acc: 94.9225, Test loss: 0.0041. Test Acc: 94.8500. Time/epoch: 4.5452
EPOCH 20. Progress: 40.0%.
Train loss: 0.0037. Train Acc: 95.1475, Test loss: 0.0038. Test Acc: 95.2200. Time/epoch: 4.5440
EPOCH 30. Progress: 60.0%.
Train loss: 0.0036. Train Acc: 95.5275, Test loss: 0.0037. Test Acc: 95.4800. Time/epoch: 4.5302
EPOCH 40. Progress: 80.0%.
Train loss: 0.0033. Train Acc: 96.1000, Test loss: 0.0034. Test Acc: 95.9400. Time/epoch: 4.6989
EPOCH 50. Progress: 100.0%.
Train loss: 0.0034. Train Acc: 95.6400, Test loss: 0.0034. Test Acc: 95.7700. Time/epoch: 4.6846
Run history:
Accuracy/train | ▁▃▄▅▅▆▅▆▆▅▇▇▇▇▇▇▇▇▇▇▇▆▇▇▇▇███▇▇▇▇▆████▇▇ |
Accuracy/val | ▁▃▄▅▅▆▅▆▆▅▇▇▇▇▇▇▇▇▇▇█▇▇▇▇▇██▇█▇▇▇▆████▇▇ |
Loss/train | █▆▅▄▄▃▄▂▂▃▂▂▂▂▂▂▂▂▂▂▁▂▂▁▂▁▁▁▁▁▂▁▂▂▁▁▁▁▂▁ |
Loss/val | █▆▅▄▄▃▃▂▂▃▂▂▂▂▂▂▂▂▂▂▁▂▂▁▂▁▁▁▁▁▂▁▂▂▁▁▁▁▂▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 95.64 |
Accuracy/val | 95.77 |
Loss/train | 0.00336 |
Loss/val | 0.00342 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_062412-itxvvi4e/logs
wandb: Agent Starting Run: 42wuc4gz with config:
wandb: batch_size: 64
wandb: epochs: 10
wandb: learning_rate: 3e-05
wandb: optimizer: sgd
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_062822-42wuc4gz
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0070. Train Acc: 81.2950, Test loss: 0.0070. Test Acc: 81.5400. Time/epoch: 2.9554
EPOCH 10. Progress: 100.0%.
Train loss: 0.0028. Train Acc: 92.7550, Test loss: 0.0030. Test Acc: 92.4100. Time/epoch: 3.0633
Run history:
Accuracy/train | ▁▆▇▇▇██▇██▇ |
Accuracy/val | ▁▆▇▇▇█████▇ |
Loss/train | █▄▂▂▂▁▁▁▁▁▂ |
Loss/val | █▄▂▂▂▁▁▁▁▁▂ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 92.755 |
Accuracy/val | 92.41 |
Loss/train | 0.00276 |
Loss/val | 0.00297 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_062822-42wuc4gz/logs
wandb: Agent Starting Run: 35gvosc0 with config:
wandb: batch_size: 32
wandb: epochs: 50
wandb: learning_rate: 1e-05
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_062908-35gvosc0
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0095. Train Acc: 89.5150, Test loss: 0.0096. Test Acc: 89.3100. Time/epoch: 4.6815
EPOCH 10. Progress: 20.0%.
Train loss: 0.0047. Train Acc: 93.7550, Test loss: 0.0048. Test Acc: 93.8200. Time/epoch: 4.6938
EPOCH 20. Progress: 40.0%.
Train loss: 0.0037. Train Acc: 95.4425, Test loss: 0.0038. Test Acc: 95.3800. Time/epoch: 4.8364
EPOCH 30. Progress: 60.0%.
Train loss: 0.0032. Train Acc: 96.0800, Test loss: 0.0033. Test Acc: 96.0400. Time/epoch: 4.7876
EPOCH 40. Progress: 80.0%.
Train loss: 0.0028. Train Acc: 96.6900, Test loss: 0.0029. Test Acc: 96.5800. Time/epoch: 4.8059
EPOCH 50. Progress: 100.0%.
Train loss: 0.0025. Train Acc: 97.0225, Test loss: 0.0027. Test Acc: 96.8900. Time/epoch: 4.7964
Run history:
Accuracy/train | ▁▃▃▄▄▄▅▅▅▅▅▆▆▆▆▆▇▆▇▇▆▇▇▇▇▇▇▇▇███████████ |
Accuracy/val | ▁▃▃▄▄▄▅▅▅▅▅▆▆▆▆▆▇▆▇▇▆▇▇▇▇▇▇█████████████ |
Loss/train | █▅▅▄▄▄▃▃▃▃▃▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▅▅▄▄▄▄▃▃▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 97.0225 |
Accuracy/val | 96.89 |
Loss/train | 0.00247 |
Loss/val | 0.00266 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_062908-35gvosc0/logs
wandb: Agent Starting Run: j4pup8og with config:
wandb: batch_size: 128
wandb: epochs: 50
wandb: learning_rate: 0.0001
wandb: optimizer: adam
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_063327-j4pup8og
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0014. Train Acc: 93.0450, Test loss: 0.0015. Test Acc: 93.0200. Time/epoch: 2.4545
EPOCH 10. Progress: 20.0%.
Train loss: 0.0008. Train Acc: 95.6450, Test loss: 0.0009. Test Acc: 95.6600. Time/epoch: 2.2921
EPOCH 20. Progress: 40.0%.
Train loss: 0.0006. Train Acc: 97.1450, Test loss: 0.0007. Test Acc: 96.8900. Time/epoch: 2.2876
EPOCH 30. Progress: 60.0%.
Train loss: 0.0006. Train Acc: 97.1675, Test loss: 0.0007. Test Acc: 96.8500. Time/epoch: 2.3911
EPOCH 40. Progress: 80.0%.
Train loss: 0.0005. Train Acc: 97.6325, Test loss: 0.0006. Test Acc: 97.1200. Time/epoch: 2.3969
EPOCH 50. Progress: 100.0%.
Train loss: 0.0004. Train Acc: 98.0375, Test loss: 0.0006. Test Acc: 97.5100. Time/epoch: 2.2635
Run history:
Accuracy/train | ▁▁▃▃▅▄▆▄▅▆▅▄▅▆▆▇▇▇▅▇▆▆▇▆▇▇▅▇█▇▇▇████▇▇▇█ |
Accuracy/val | ▁▂▄▄▅▄▆▅▅▆▅▄▅▆▆▇▇▇▄▇▆▆▇▇▇▇▅█▇▇▇▇███▇▇▇▇█ |
Loss/train | █▇▅▅▄▅▃▄▄▃▄▅▄▃▃▂▂▂▄▂▃▂▂▂▂▂▄▁▁▂▂▁▁▁▁▁▂▂▂▁ |
Loss/val | █▆▅▅▄▅▃▄▄▃▃▄▄▃▃▂▂▂▄▂▃▂▂▂▂▂▄▁▁▂▂▁▁▁▁▁▂▂▂▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.0375 |
Accuracy/val | 97.51 |
Loss/train | 0.00042 |
Loss/val | 0.0006 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_063327-j4pup8og/logs
wandb: Agent Starting Run: prgzf0iw with config:
wandb: batch_size: 128
wandb: epochs: 20
wandb: learning_rate: 0.001
wandb: optimizer: adam
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_063540-prgzf0iw
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0014. Train Acc: 92.9000, Test loss: 0.0015. Test Acc: 92.5000. Time/epoch: 2.4407
EPOCH 10. Progress: 50.0%.
Train loss: 0.0008. Train Acc: 96.0350, Test loss: 0.0009. Test Acc: 95.4600. Time/epoch: 2.4164
EPOCH 20. Progress: 100.0%.
Train loss: 0.0005. Train Acc: 97.7550, Test loss: 0.0007. Test Acc: 97.1800. Time/epoch: 2.2680
Run history:
Accuracy/train | ▃▁▆▂▅▄▅▆▇▆▆▆▆▇▇▇▇▆▆▆█ |
Accuracy/val | ▃▁▆▂▅▄▅▆▇▆▆▆▆▇█▇▇▆▆▆█ |
Loss/train | ▅█▃▆▄█▄▃▂▃▂▃▃▂▁▂▂▄▃▃▁ |
Loss/val | ▅█▃▆▃█▄▂▂▃▂▃▂▂▁▂▂▄▃▃▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 97.755 |
Accuracy/val | 97.18 |
Loss/train | 0.00048 |
Loss/val | 0.00067 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_063540-prgzf0iw/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: r82ztge9 with config:
wandb: batch_size: 128
wandb: epochs: 10
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_063651-r82ztge9
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0020. Train Acc: 88.4900, Test loss: 0.0021. Test Acc: 88.7800. Time/epoch: 2.4492
EPOCH 10. Progress: 100.0%.
Train loss: 0.0009. Train Acc: 95.1850, Test loss: 0.0010. Test Acc: 94.9800. Time/epoch: 2.4040
Run history:
Accuracy/train | ▁▄▅▆▇▆█▇██▇ |
Accuracy/val | ▁▄▅▆▇▆▇▆██▇ |
Loss/train | █▅▃▃▃▃▂▃▂▁▂ |
Loss/val | █▅▃▃▂▂▁▂▁▁▂ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 95.185 |
Accuracy/val | 94.98 |
Loss/train | 0.00091 |
Loss/val | 0.00095 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_063651-r82ztge9/logs
wandb: Agent Starting Run: annf7jys with config:
wandb: batch_size: 128
wandb: epochs: 10
wandb: learning_rate: 0.001
wandb: optimizer: rmsprop
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_063731-annf7jys
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0048. Train Acc: 75.6050, Test loss: 0.0048. Test Acc: 76.0700. Time/epoch: 2.3776
EPOCH 10. Progress: 100.0%.
Train loss: 0.0026. Train Acc: 85.0350, Test loss: 0.0026. Test Acc: 85.0000. Time/epoch: 2.3433
Run history:
Accuracy/train | ▄▃▅▅▁▄▅▇██▆ |
Accuracy/val | ▅▃▅▅▁▄▅▇██▇ |
Loss/train | ▅▄▃▄█▆▃▂▁▁▂ |
Loss/val | ▅▄▃▄█▆▃▂▁▁▂ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 85.035 |
Accuracy/val | 85.0 |
Loss/train | 0.00256 |
Loss/val | 0.0026 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_063731-annf7jys/logs
wandb: Agent Starting Run: l0odnl1k with config:
wandb: batch_size: 128
wandb: epochs: 10
wandb: learning_rate: 3e-05
wandb: optimizer: rmsprop
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_063812-l0odnl1k
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0020. Train Acc: 90.2750, Test loss: 0.0020. Test Acc: 90.1600. Time/epoch: 2.2118
EPOCH 10. Progress: 100.0%.
Train loss: 0.0010. Train Acc: 95.1850, Test loss: 0.0010. Test Acc: 95.0600. Time/epoch: 2.1960
Run history:
Accuracy/train | ▁▂▄▆▆▅▆▇▆██ |
Accuracy/val | ▁▃▅▆▆▅▇▇▆██ |
Loss/train | █▆▄▃▃▄▂▂▂▁▁ |
Loss/val | █▆▄▃▃▄▂▂▃▁▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 95.185 |
Accuracy/val | 95.06 |
Loss/train | 0.00097 |
Loss/val | 0.00104 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_063812-l0odnl1k/logs
wandb: Agent Starting Run: 7bnazyxw with config:
wandb: batch_size: 64
wandb: epochs: 50
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_063852-7bnazyxw
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0028. Train Acc: 92.1675, Test loss: 0.0030. Test Acc: 91.8700. Time/epoch: 3.3159
EPOCH 10. Progress: 20.0%.
Train loss: 0.0013. Train Acc: 96.8300, Test loss: 0.0015. Test Acc: 96.3700. Time/epoch: 3.1416
EPOCH 20. Progress: 40.0%.
Train loss: 0.0011. Train Acc: 97.0825, Test loss: 0.0016. Test Acc: 96.1800. Time/epoch: 3.2810
EPOCH 30. Progress: 60.0%.
Train loss: 0.0007. Train Acc: 98.3550, Test loss: 0.0013. Test Acc: 97.4600. Time/epoch: 3.3041
EPOCH 40. Progress: 80.0%.
Train loss: 0.0006. Train Acc: 98.6100, Test loss: 0.0013. Test Acc: 97.5200. Time/epoch: 3.3066
EPOCH 50. Progress: 100.0%.
Train loss: 0.0005. Train Acc: 98.7850, Test loss: 0.0014. Test Acc: 97.2500. Time/epoch: 3.3019
Run history:
Accuracy/train | ▁▄▅▄▅▅▅▆▆▆▅▆▇▆▆▆▆▇▆▇▇▆▇▆▇██▇▇▇▆███▇▇████ |
Accuracy/val | ▁▄▅▅▆▆▅▆▆▇▆▆▇▆▇▆▆▇▇█▇▆█▆████▇▇▆███▇████▇ |
Loss/train | █▆▅▅▄▄▄▄▃▃▄▃▃▃▃▃▃▂▃▂▂▄▂▃▂▂▁▂▃▂▃▁▁▁▂▂▁▁▁▁ |
Loss/val | █▅▄▄▃▃▄▃▂▂▃▃▁▃▂▃▃▁▃▁▂▄▁▃▂▁▁▂▃▃▄▂▁▂▂▂▂▂▂▂ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.785 |
Accuracy/val | 97.25 |
Loss/train | 0.00048 |
Loss/val | 0.00144 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_063852-7bnazyxw/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: cqfn8ipr with config:
wandb: batch_size: 64
wandb: epochs: 50
wandb: learning_rate: 0.01
wandb: optimizer: sgd
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_064201-cqfn8ipr
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0241. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 3.0963
EPOCH 10. Progress: 20.0%.
Train loss: 0.0241. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 3.0808
EPOCH 20. Progress: 40.0%.
Train loss: 0.0241. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 3.0637
EPOCH 30. Progress: 60.0%.
Train loss: 0.0241. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 2.9467
EPOCH 40. Progress: 80.0%.
Train loss: 0.0241. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 3.0561
EPOCH 50. Progress: 100.0%.
Train loss: 0.0241. Train Acc: 36.8250, Test loss: 0.0242. Test Acc: 37.5400. Time/epoch: 3.0647
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | ▅▁▄▂▅▃▂▁▅▅▄▂▄▇▁▆▃▂▄▄▂▃▁▃▁▃▄▄▆▁▃▇▃▄▂▇▃▁█▅ |
Loss/val | ▄▃▄▂▆▄▃▁▅▄▃▂▄▇▁▆▂▃▄▄▄▅▂▃▁▄▄▄▇▂▄▇▃▄▂▆▄▁█▇ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.02412 |
Loss/val | 0.02417 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_064201-cqfn8ipr/logs
wandb: Agent Starting Run: x90fff0g with config:
wandb: batch_size: 32
wandb: epochs: 10
wandb: learning_rate: 0.01
wandb: optimizer: adam
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_064449-x90fff0g
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0481. Train Acc: 36.8250, Test loss: 0.0480. Test Acc: 37.5400. Time/epoch: 4.9988
EPOCH 10. Progress: 100.0%.
Train loss: 0.0481. Train Acc: 36.8250, Test loss: 0.0480. Test Acc: 37.5400. Time/epoch: 5.1742
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | ▇▄█▃▅▃▃▂▁▂▅ |
Loss/val | █▂▇▂▂▄▂▁▂▂▃ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.04807 |
Loss/val | 0.04796 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_064449-x90fff0g/logs
wandb: Agent Starting Run: awxs0f2q with config:
wandb: batch_size: 128
wandb: epochs: 10
wandb: learning_rate: 1e-05
wandb: optimizer: sgd
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_064600-awxs0f2q
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0058. Train Acc: 73.0175, Test loss: 0.0058. Test Acc: 73.4500. Time/epoch: 2.2151
EPOCH 10. Progress: 100.0%.
Train loss: 0.0021. Train Acc: 89.6050, Test loss: 0.0022. Test Acc: 89.4400. Time/epoch: 2.1574
Run history:
Accuracy/train | ▁▄▅▆▆▇▇▇███ |
Accuracy/val | ▁▄▅▆▆▇▇▇███ |
Loss/train | █▅▄▃▃▂▂▂▁▁▁ |
Loss/val | █▅▄▃▃▃▂▂▁▁▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 89.605 |
Accuracy/val | 89.44 |
Loss/train | 0.00213 |
Loss/val | 0.00218 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_064600-awxs0f2q/logs
wandb: Agent Starting Run: i8lgbjvl with config:
wandb: batch_size: 32
wandb: epochs: 50
wandb: learning_rate: 3e-05
wandb: optimizer: sgd
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_064641-i8lgbjvl
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0112. Train Acc: 87.1725, Test loss: 0.0114. Test Acc: 87.3900. Time/epoch: 4.7143
EPOCH 10. Progress: 20.0%.
Train loss: 0.0060. Train Acc: 91.7525, Test loss: 0.0062. Test Acc: 91.9000. Time/epoch: 4.5731
EPOCH 20. Progress: 40.0%.
Train loss: 0.0050. Train Acc: 93.5525, Test loss: 0.0052. Test Acc: 93.4300. Time/epoch: 4.5421
EPOCH 30. Progress: 60.0%.
Train loss: 0.0048. Train Acc: 93.5650, Test loss: 0.0050. Test Acc: 93.5300. Time/epoch: 4.7165
EPOCH 40. Progress: 80.0%.
Train loss: 0.0042. Train Acc: 94.9375, Test loss: 0.0045. Test Acc: 94.6100. Time/epoch: 4.6815
EPOCH 50. Progress: 100.0%.
Train loss: 0.0040. Train Acc: 95.0375, Test loss: 0.0043. Test Acc: 94.8200. Time/epoch: 4.6573
Run history:
Accuracy/train | ▁▁▃▄▄▅▅▅▅▆▆▆▆▆▆▇▇▆▇▇▆▇▅▇▇▇▇▇█▇▇▇▇▇█▇▇███ |
Accuracy/val | ▁▁▃▄▄▅▅▅▅▆▆▆▆▆▆▇▇▆▇▇▆▇▅▇▇▇▇▇▇▇▇▇▇▇█▇▇███ |
Loss/train | █▆▅▄▄▃▃▃▃▂▃▂▂▂▂▂▂▃▂▂▂▂▃▂▂▂▁▂▁▁▁▂▁▁▁▂▁▁▁▁ |
Loss/val | █▆▅▄▄▃▃▃▃▂▂▂▂▂▂▂▂▃▂▂▂▂▃▂▂▂▁▁▁▁▁▂▁▁▁▂▂▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 95.0375 |
Accuracy/val | 94.82 |
Loss/train | 0.00404 |
Loss/val | 0.00426 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_064641-i8lgbjvl/logs
wandb: Agent Starting Run: 2x20kvei with config:
wandb: batch_size: 32
wandb: epochs: 50
wandb: learning_rate: 0.0001
wandb: optimizer: adam
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_065050-2x20kvei
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0045. Train Acc: 94.4125, Test loss: 0.0047. Test Acc: 94.2500. Time/epoch: 5.1401
EPOCH 10. Progress: 20.0%.
Train loss: 0.0026. Train Acc: 96.5200, Test loss: 0.0030. Test Acc: 96.1000. Time/epoch: 5.1145
EPOCH 20. Progress: 40.0%.
Train loss: 0.0016. Train Acc: 98.0475, Test loss: 0.0022. Test Acc: 97.4800. Time/epoch: 5.1726
EPOCH 30. Progress: 60.0%.
Train loss: 0.0013. Train Acc: 98.2825, Test loss: 0.0022. Test Acc: 97.3500. Time/epoch: 5.1462
EPOCH 40. Progress: 80.0%.
Train loss: 0.0014. Train Acc: 98.3350, Test loss: 0.0027. Test Acc: 97.1400. Time/epoch: 4.9997
EPOCH 50. Progress: 100.0%.
Train loss: 0.0008. Train Acc: 98.9700, Test loss: 0.0022. Test Acc: 97.5800. Time/epoch: 4.9964
Run history:
Accuracy/train | ▁▁▂▄▂▃▅▂▄▆▅▅▆▆▆▃▆▇▆▆▇▇▇▇▇██▆▆▇▇▇██▇▇████ |
Accuracy/val | ▁▁▂▅▂▄▅▃▄▆▆▆▇▇▇▃▇█▆▇██▇█▇██▆▅▇▇█▇█▇▇▇██▇ |
Loss/train | ▇▇▆▄▆▅▄▅▄▃▃▃▂▃▃█▂▂▂▂▂▂▂▂▂▁▁▃▂▂▂▂▁▁▂▁▁▁▁▁ |
Loss/val | ▆▅▅▃▅▃▃▄▃▂▂▂▂▂▂█▂▁▂▂▁▁▂▁▂▁▁▃▂▂▂▁▁▁▂▂▂▁▁▂ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.97 |
Accuracy/val | 97.58 |
Loss/train | 0.00082 |
Loss/val | 0.0022 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_065050-2x20kvei/logs
wandb: Agent Starting Run: 59l6xn7o with config:
wandb: batch_size: 128
wandb: epochs: 20
wandb: learning_rate: 0.0001
wandb: optimizer: sgd
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_065525-59l6xn7o
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0042. Train Acc: 80.7750, Test loss: 0.0043. Test Acc: 80.6300. Time/epoch: 2.3286
EPOCH 10. Progress: 50.0%.
Train loss: 0.0011. Train Acc: 94.6550, Test loss: 0.0011. Test Acc: 94.9500. Time/epoch: 2.1682
EPOCH 20. Progress: 100.0%.
Train loss: 0.0010. Train Acc: 95.3900, Test loss: 0.0010. Test Acc: 95.5600. Time/epoch: 2.3293
Run history:
Accuracy/train | ▁▅▆▇▇▇▇█▇▇██▇█▇████▇█ |
Accuracy/val | ▁▅▆▇▇▇▇█▇▇██▇██████▇█ |
Loss/train | █▄▃▂▂▂▂▁▂▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▄▃▂▂▂▂▁▂▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 95.39 |
Accuracy/val | 95.56 |
Loss/train | 0.00095 |
Loss/val | 0.00099 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_065525-59l6xn7o/logs
wandb: Agent Starting Run: w1h9wxrm with config:
wandb: batch_size: 32
wandb: epochs: 20
wandb: learning_rate: 3e-05
wandb: optimizer: rmsprop
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_065627-w1h9wxrm
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0072. Train Acc: 89.5425, Test loss: 0.0073. Test Acc: 89.6000. Time/epoch: 4.6712
EPOCH 10. Progress: 50.0%.
Train loss: 0.0031. Train Acc: 96.0950, Test loss: 0.0033. Test Acc: 96.1100. Time/epoch: 4.6559
EPOCH 20. Progress: 100.0%.
Train loss: 0.0027. Train Acc: 96.7000, Test loss: 0.0029. Test Acc: 96.5800. Time/epoch: 4.8368
Run history:
Accuracy/train | ▁▃▅▅▅▆▇▆▇▇▇▇▇█▇█▇▇█▇█ |
Accuracy/val | ▁▃▆▅▅▆▇▇▇▇█▇▇█▇█▇▇█▇█ |
Loss/train | █▆▄▄▄▃▂▃▂▂▂▂▂▁▂▁▂▂▁▂▁ |
Loss/val | █▇▄▄▄▄▂▃▂▂▂▂▂▁▂▁▂▂▁▂▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 96.7 |
Accuracy/val | 96.58 |
Loss/train | 0.00267 |
Loss/val | 0.0029 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_065627-w1h9wxrm/logs
wandb: Agent Starting Run: jab9p12o with config:
wandb: batch_size: 64
wandb: epochs: 20
wandb: learning_rate: 3e-05
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_065818-jab9p12o
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0045. Train Acc: 88.4400, Test loss: 0.0046. Test Acc: 88.3700. Time/epoch: 3.0000
EPOCH 10. Progress: 50.0%.
Train loss: 0.0020. Train Acc: 94.6150, Test loss: 0.0021. Test Acc: 94.6100. Time/epoch: 3.0053
EPOCH 20. Progress: 100.0%.
Train loss: 0.0015. Train Acc: 96.0950, Test loss: 0.0017. Test Acc: 95.8100. Time/epoch: 3.0189
Run history:
Accuracy/train | ▁▄▄▅▅▂▆▆▅▆▇▇▇▇▆▇▇████ |
Accuracy/val | ▁▄▄▅▆▂▆▆▆▆▇▇▇▇▆▇▇████ |
Loss/train | █▅▅▄▃▇▃▃▃▃▂▂▂▂▂▂▂▁▁▁▁ |
Loss/val | █▅▅▄▃▇▃▃▃▃▂▂▂▂▂▂▂▁▁▁▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 96.095 |
Accuracy/val | 95.81 |
Loss/train | 0.00152 |
Loss/val | 0.00169 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_065818-jab9p12o/logs
wandb: Agent Starting Run: 9arbpp4s with config:
wandb: batch_size: 32
wandb: epochs: 50
wandb: learning_rate: 0.0003
wandb: optimizer: rmsprop
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_065939-9arbpp4s
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0082. Train Acc: 88.3625, Test loss: 0.0084. Test Acc: 88.3400. Time/epoch: 4.8145
EPOCH 10. Progress: 20.0%.
Train loss: 0.0029. Train Acc: 96.4425, Test loss: 0.0031. Test Acc: 96.2300. Time/epoch: 4.7270
EPOCH 20. Progress: 40.0%.
Train loss: 0.0036. Train Acc: 95.4050, Test loss: 0.0038. Test Acc: 95.5000. Time/epoch: 4.7034
EPOCH 30. Progress: 60.0%.
Train loss: 0.0023. Train Acc: 97.1925, Test loss: 0.0025. Test Acc: 96.8300. Time/epoch: 4.6798
EPOCH 40. Progress: 80.0%.
Train loss: 0.0034. Train Acc: 95.7200, Test loss: 0.0037. Test Acc: 95.6300. Time/epoch: 4.7823
EPOCH 50. Progress: 100.0%.
Train loss: 0.0019. Train Acc: 97.6125, Test loss: 0.0024. Test Acc: 97.1800. Time/epoch: 4.8360
Run history:
Accuracy/train | ▁▄▃▅▃▆▇▇▇▇▆▇▇▇▇▆▆█▇▆▆▇▇███▇▇████▇▇██▇███ |
Accuracy/val | ▁▄▃▅▃▆▇▇▇▇▆▇▇▇▇▆▇█▇▇▆▇▇███▇▇████▇▇██▇███ |
Loss/train | █▅▅▄▆▃▂▂▂▂▄▂▂▂▂▃▃▂▂▃▃▂▂▂▂▁▂▂▁▁▁▁▂▂▁▁▂▁▁▁ |
Loss/val | █▄▅▄▆▃▂▂▂▂▄▂▂▂▂▃▃▁▂▃▃▂▂▂▁▁▂▂▁▁▁▁▂▂▁▁▂▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 97.6125 |
Accuracy/val | 97.18 |
Loss/train | 0.00193 |
Loss/val | 0.00237 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_065939-9arbpp4s/logs
wandb: Agent Starting Run: oefv01yj with config:
wandb: batch_size: 64
wandb: epochs: 50
wandb: learning_rate: 0.0001
wandb: optimizer: rmsprop
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_070357-oefv01yj
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0028. Train Acc: 92.7950, Test loss: 0.0028. Test Acc: 92.9400. Time/epoch: 3.0069
EPOCH 10. Progress: 20.0%.
Train loss: 0.0015. Train Acc: 96.1900, Test loss: 0.0016. Test Acc: 96.1400. Time/epoch: 2.9758
EPOCH 20. Progress: 40.0%.
Train loss: 0.0014. Train Acc: 96.6225, Test loss: 0.0016. Test Acc: 96.4300. Time/epoch: 3.1506
EPOCH 30. Progress: 60.0%.
Train loss: 0.0012. Train Acc: 96.9750, Test loss: 0.0014. Test Acc: 96.7400. Time/epoch: 3.1406
EPOCH 40. Progress: 80.0%.
Train loss: 0.0013. Train Acc: 96.8525, Test loss: 0.0014. Test Acc: 96.5500. Time/epoch: 3.1281
EPOCH 50. Progress: 100.0%.
Train loss: 0.0011. Train Acc: 97.3725, Test loss: 0.0012. Test Acc: 97.2000. Time/epoch: 3.1423
Run history:
Accuracy/train | ▂▃▃▄▅▅▁▆▆▆▃▆▅▇▇▃▇▇▅▆▇▇▇▇▇▇▇█▇█▇█▆██▆████ |
Accuracy/val | ▂▄▃▅▅▅▁▆▆▆▃▆▅▇▇▄▇▆▅▆▇▇▇▇▇▇▇█▇█▇█▆██▆█▇██ |
Loss/train | █▆▆▅▄▄█▃▃▃▅▃▄▃▃▆▃▃▃▃▂▂▂▂▂▂▂▁▂▁▂▁▃▁▁▃▁▁▁▁ |
Loss/val | ▇▆▅▅▄▄█▃▃▃▅▃▃▂▃▆▃▃▃▃▂▂▂▂▂▂▂▁▂▁▂▁▃▁▁▃▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 97.3725 |
Accuracy/val | 97.2 |
Loss/train | 0.00107 |
Loss/val | 0.00117 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_070357-oefv01yj/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: 96qs6je8 with config:
wandb: batch_size: 64
wandb: epochs: 50
wandb: learning_rate: 0.0003
wandb: optimizer: rmsprop
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_070655-96qs6je8
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0028. Train Acc: 92.7200, Test loss: 0.0028. Test Acc: 92.6500. Time/epoch: 3.1800
EPOCH 10. Progress: 20.0%.
Train loss: 0.0013. Train Acc: 96.9675, Test loss: 0.0014. Test Acc: 96.5200. Time/epoch: 3.1467
EPOCH 20. Progress: 40.0%.
Train loss: 0.0010. Train Acc: 97.5800, Test loss: 0.0012. Test Acc: 97.1100. Time/epoch: 3.1478
EPOCH 30. Progress: 60.0%.
Train loss: 0.0012. Train Acc: 97.2175, Test loss: 0.0014. Test Acc: 96.7800. Time/epoch: 3.1445
EPOCH 40. Progress: 80.0%.
Train loss: 0.0009. Train Acc: 97.9575, Test loss: 0.0011. Test Acc: 97.3900. Time/epoch: 2.9880
EPOCH 50. Progress: 100.0%.
Train loss: 0.0012. Train Acc: 97.2075, Test loss: 0.0015. Test Acc: 96.7100. Time/epoch: 2.9671
Run history:
Accuracy/train | ▁▂▄▅▂▅▆▃▆▆▇▂▆▆▇▁▇▆▇▇▆▆▇▇▇▅█▇▇▇█▅▇██████▇ |
Accuracy/val | ▁▂▄▅▂▅▆▃▇▆▇▂▆▇▇▁▇▇█▇▆▆██▇▅█▇▇▇█▅▇███▇██▇ |
Loss/train | ▇▆▆▄▇▄▃▆▃▃▂▇▃▃▂█▂▂▂▂▃▃▁▂▂▄▁▂▂▂▁▄▂▁▁▁▁▁▁▂ |
Loss/val | ▇▆▆▄▆▃▃▆▂▃▂▇▃▂▂█▁▂▁▂▂▃▁▁▂▄▁▂▂▂▁▄▂▁▁▂▁▁▁▂ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 97.2075 |
Accuracy/val | 96.71 |
Loss/train | 0.00119 |
Loss/val | 0.0015 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_070655-96qs6je8/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: if36gw6q with config:
wandb: batch_size: 32
wandb: epochs: 50
wandb: learning_rate: 1e-05
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_070954-if36gw6q
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0117. Train Acc: 84.8025, Test loss: 0.0116. Test Acc: 84.9500. Time/epoch: 4.8100
EPOCH 10. Progress: 20.0%.
Train loss: 0.0051. Train Acc: 93.5625, Test loss: 0.0052. Test Acc: 93.7500. Time/epoch: 4.8047
EPOCH 20. Progress: 40.0%.
Train loss: 0.0044. Train Acc: 94.6175, Test loss: 0.0045. Test Acc: 94.6100. Time/epoch: 4.6649
EPOCH 30. Progress: 60.0%.
Train loss: 0.0040. Train Acc: 94.8675, Test loss: 0.0041. Test Acc: 94.9600. Time/epoch: 4.6971
EPOCH 40. Progress: 80.0%.
Train loss: 0.0040. Train Acc: 94.8900, Test loss: 0.0041. Test Acc: 95.0300. Time/epoch: 4.6646
EPOCH 50. Progress: 100.0%.
Train loss: 0.0039. Train Acc: 95.4925, Test loss: 0.0040. Test Acc: 95.3700. Time/epoch: 4.8321
Run history:
Accuracy/train | ▁▃▄▄▅▅▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇██▇███████████▇██▇█ |
Accuracy/val | ▁▃▄▄▅▅▆▆▇▇▇▇▇▇██▇▇▇▇███▇███████████▇████ |
Loss/train | █▅▄▄▃▃▃▃▂▂▂▂▂▂▂▁▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▅▄▄▃▃▃▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 95.4925 |
Accuracy/val | 95.37 |
Loss/train | 0.00385 |
Loss/val | 0.00399 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_070954-if36gw6q/logs
wandb: Agent Starting Run: lny4oi1s with config:
wandb: batch_size: 32
wandb: epochs: 20
wandb: learning_rate: 0.01
wandb: optimizer: sgd
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_071411-lny4oi1s
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0481. Train Acc: 36.8250, Test loss: 0.0480. Test Acc: 37.5400. Time/epoch: 4.5595
EPOCH 10. Progress: 50.0%.
Train loss: 0.0481. Train Acc: 36.8250, Test loss: 0.0480. Test Acc: 37.5400. Time/epoch: 4.6839
EPOCH 20. Progress: 100.0%.
Train loss: 0.0481. Train Acc: 36.8250, Test loss: 0.0480. Test Acc: 37.5400. Time/epoch: 4.6789
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | ▂▃▃▁▃▁█▁▃▃▂▁▂▃▂▁▁▃▅▄▂ |
Loss/val | ▃▃▃▂▃▁█▁▃▃▂▂▂▄▂▂▁▂▄▃▃ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.04809 |
Loss/val | 0.04802 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_071411-lny4oi1s/logs
wandb: Agent Starting Run: csvwyhyp with config:
wandb: batch_size: 32
wandb: epochs: 50
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_071602-csvwyhyp
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0061. Train Acc: 91.8000, Test loss: 0.0062. Test Acc: 91.6500. Time/epoch: 4.9858
EPOCH 10. Progress: 20.0%.
Train loss: 0.0024. Train Acc: 96.8900, Test loss: 0.0030. Test Acc: 96.6200. Time/epoch: 5.1420
EPOCH 20. Progress: 40.0%.
Train loss: 0.0021. Train Acc: 97.5225, Test loss: 0.0034. Test Acc: 96.3500. Time/epoch: 5.1794
EPOCH 30. Progress: 60.0%.
Train loss: 0.0014. Train Acc: 98.2825, Test loss: 0.0033. Test Acc: 96.9800. Time/epoch: 5.1754
EPOCH 40. Progress: 80.0%.
Train loss: 0.0008. Train Acc: 99.0850, Test loss: 0.0030. Test Acc: 97.6100. Time/epoch: 5.1110
EPOCH 50. Progress: 100.0%.
Train loss: 0.0006. Train Acc: 99.3250, Test loss: 0.0037. Test Acc: 97.3500. Time/epoch: 4.9807
Run history:
Accuracy/train | ▁▃▃▅▅▅▂▆▆▆▆▆▆▆▅▇▆▆▆▇█▇█▇▇▇▇▇▇▇███▇████▇█ |
Accuracy/val | ▁▃▄▆▆▆▃▇▇▆▇▇▇▇▅█▆▆▆██▇▇▇▇▇▇▇▇▇▇█▇▇█▇▇▇▆█ |
Loss/train | █▆▅▄▄▄▆▄▃▄▃▃▃▃▄▂▃▃▃▂▂▂▁▂▂▂▃▂▂▂▁▁▁▂▁▂▁▁▂▁ |
Loss/val | █▅▄▃▃▂▅▂▂▂▁▁▂▂▄▁▃▃▄▁▁▃▂▂▃▂▄▃▂▃▃▃▃▃▂▃▃▃▅▃ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 99.325 |
Accuracy/val | 97.35 |
Loss/train | 0.00063 |
Loss/val | 0.00372 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_071602-csvwyhyp/logs
wandb: Agent Starting Run: yge6t1ea with config:
wandb: batch_size: 128
wandb: epochs: 50
wandb: learning_rate: 0.001
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_072034-yge6t1ea
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0029. Train Acc: 81.7425, Test loss: 0.0030. Test Acc: 82.0300. Time/epoch: 2.3699
EPOCH 10. Progress: 20.0%.
Train loss: 0.0027. Train Acc: 89.3325, Test loss: 0.0029. Test Acc: 89.0700. Time/epoch: 2.3301
EPOCH 20. Progress: 40.0%.
Train loss: 0.0030. Train Acc: 89.0175, Test loss: 0.0032. Test Acc: 88.2100. Time/epoch: 2.3258
EPOCH 30. Progress: 60.0%.
Train loss: 0.0006. Train Acc: 97.4625, Test loss: 0.0011. Test Acc: 95.1700. Time/epoch: 2.1939
EPOCH 40. Progress: 80.0%.
Train loss: 0.0006. Train Acc: 97.5300, Test loss: 0.0012. Test Acc: 94.5700. Time/epoch: 2.2067
EPOCH 50. Progress: 100.0%.
Train loss: 0.0007. Train Acc: 96.6775, Test loss: 0.0014. Test Acc: 94.0000. Time/epoch: 2.3487
Run history:
Accuracy/train | ▂▁▃▃▅▆▆▅▅▇▄▇▇▇▇▇▅▅▇▇▅▇▆▇██▇▇▇██▇▇████▇▇▇ |
Accuracy/val | ▂▁▃▃▆▆▇▆▅▇▅█▇███▅▆██▅▇▇▇███▇▇██▇▇████▇▇▇ |
Loss/train | ▆█▇▆▄▃▃▄▆▂▆▂▂▂▂▂▇▄▂▂▆▂▃▂▁▁▂▂▂▁▁▂▂▁▁▁▁▂▂▂ |
Loss/val | ▆█▆▆▃▃▂▄▆▂▆▂▂▁▁▁▇▄▁▁▆▂▃▂▁▁▂▂▂▁▁▃▂▁▂▁▁▃▃▂ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 96.6775 |
Accuracy/val | 94.0 |
Loss/train | 0.00071 |
Loss/val | 0.00143 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_072034-yge6t1ea/logs
wandb: Agent Starting Run: ec2v9ubl with config:
wandb: batch_size: 64
wandb: epochs: 20
wandb: learning_rate: 0.0001
wandb: optimizer: adam
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_072245-ec2v9ubl
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0036. Train Acc: 89.8275, Test loss: 0.0036. Test Acc: 89.9400. Time/epoch: 3.1595
EPOCH 10. Progress: 50.0%.
Train loss: 0.0013. Train Acc: 96.6900, Test loss: 0.0015. Test Acc: 96.2600. Time/epoch: 3.1593
EPOCH 20. Progress: 100.0%.
Train loss: 0.0011. Train Acc: 97.1875, Test loss: 0.0014. Test Acc: 96.6100. Time/epoch: 3.1437
Run history:
Accuracy/train | ▂▁▅▁▆▆▇▇▇▇██▇▆██▇▇███ |
Accuracy/val | ▂▁▅▁▆▇▇▇▇▇██▇▅██▇▇███ |
Loss/train | ▇▇▄█▃▃▂▃▂▂▂▁▂▃▁▂▂▂▁▁▁ |
Loss/val | ▇▇▄█▃▂▂▂▂▂▁▁▂▃▁▁▂▂▁▁▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 97.1875 |
Accuracy/val | 96.61 |
Loss/train | 0.00112 |
Loss/val | 0.00142 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_072245-ec2v9ubl/logs
wandb: Agent Starting Run: mqjrnn89 with config:
wandb: batch_size: 64
wandb: epochs: 20
wandb: learning_rate: 0.01
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_072406-mqjrnn89
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 3.1553
EPOCH 10. Progress: 50.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 2.9821
EPOCH 20. Progress: 100.0%.
Train loss: 0.0240. Train Acc: 36.8250, Test loss: 0.0241. Test Acc: 37.5400. Time/epoch: 2.9804
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | ▃▇█▇▄▂▃▄▂▂▂▁▃▄▁▁▄▄▁▅▁ |
Loss/val | ▅▆█▆▃▃▄▄▅▃▄▁▄▅▇▃▆▆▃▇▆ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.02402 |
Loss/val | 0.02408 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_072406-mqjrnn89/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: ca726hgm with config:
wandb: batch_size: 128
wandb: epochs: 10
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_072533-ca726hgm
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0015. Train Acc: 91.7075, Test loss: 0.0016. Test Acc: 91.9400. Time/epoch: 2.4440
EPOCH 10. Progress: 100.0%.
Train loss: 0.0007. Train Acc: 96.3700, Test loss: 0.0008. Test Acc: 96.0600. Time/epoch: 2.3954
Run history:
Accuracy/train | ▁▅▇▅▇▇██▆█▇ |
Accuracy/val | ▁▅▆▅▇▇█▇▆█▇ |
Loss/train | █▄▃▄▂▂▁▂▃▁▂ |
Loss/val | █▄▂▄▂▂▁▂▃▁▂ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 96.37 |
Accuracy/val | 96.06 |
Loss/train | 0.0007 |
Loss/val | 0.00084 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_072533-ca726hgm/logs
wandb: Agent Starting Run: qzkda9ho with config:
wandb: batch_size: 64
wandb: epochs: 50
wandb: learning_rate: 3e-05
wandb: optimizer: sgd
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_072614-qzkda9ho
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0180. Train Acc: 36.8300, Test loss: 0.0179. Test Acc: 37.5400. Time/epoch: 3.1094
EPOCH 10. Progress: 20.0%.
Train loss: 0.0151. Train Acc: 63.6725, Test loss: 0.0150. Test Acc: 64.2200. Time/epoch: 3.0681
EPOCH 20. Progress: 40.0%.
Train loss: 0.0098. Train Acc: 76.4450, Test loss: 0.0098. Test Acc: 76.3900. Time/epoch: 3.0830
EPOCH 30. Progress: 60.0%.
Train loss: 0.0027. Train Acc: 93.2175, Test loss: 0.0028. Test Acc: 93.1000. Time/epoch: 2.9288
EPOCH 40. Progress: 80.0%.
Train loss: 0.0020. Train Acc: 94.9225, Test loss: 0.0021. Test Acc: 94.9100. Time/epoch: 2.9379
EPOCH 50. Progress: 100.0%.
Train loss: 0.0018. Train Acc: 95.4750, Test loss: 0.0019. Test Acc: 95.5300. Time/epoch: 3.1026
Run history:
Accuracy/train | ▁▁▄▄▄▄▄▄▄▄▄▄▄▄▄▅▆▆▆▇▇▇██████████████████ |
Accuracy/val | ▁▁▄▄▄▄▄▄▄▄▄▄▄▄▄▅▆▆▆▇▇▇██████████████████ |
Loss/train | █████▇▇▇▇▇▇▆▆▆▆▅▄▄▄▃▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █████▇▇▇▇▇▇▆▆▆▆▅▄▄▄▃▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 95.475 |
Accuracy/val | 95.53 |
Loss/train | 0.00178 |
Loss/val | 0.0019 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_072614-qzkda9ho/logs
wandb: Agent Starting Run: o8kgc485 with config:
wandb: batch_size: 32
wandb: epochs: 50
wandb: learning_rate: 1e-05
wandb: optimizer: sgd
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_072901-o8kgc485
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0107. Train Acc: 88.2925, Test loss: 0.0107. Test Acc: 88.2500. Time/epoch: 4.5831
EPOCH 10. Progress: 20.0%.
Train loss: 0.0049. Train Acc: 93.7575, Test loss: 0.0051. Test Acc: 93.4600. Time/epoch: 4.7178
EPOCH 20. Progress: 40.0%.
Train loss: 0.0039. Train Acc: 95.0025, Test loss: 0.0041. Test Acc: 94.8500. Time/epoch: 4.6745
EPOCH 30. Progress: 60.0%.
Train loss: 0.0035. Train Acc: 95.5725, Test loss: 0.0037. Test Acc: 95.4400. Time/epoch: 4.7075
EPOCH 40. Progress: 80.0%.
Train loss: 0.0032. Train Acc: 96.0400, Test loss: 0.0034. Test Acc: 95.7500. Time/epoch: 4.5206
EPOCH 50. Progress: 100.0%.
Train loss: 0.0031. Train Acc: 96.1600, Test loss: 0.0034. Test Acc: 95.9800. Time/epoch: 4.5911
Run history:
Accuracy/train | ▁▃▄▅▆▅▆▆▆▆▇▇▆▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇██████████ |
Accuracy/val | ▁▃▄▅▆▆▆▆▆▇▇▇▇▇▇▆▇▇▇▇▇▇▇▇█▇█▇▇▇██████████ |
Loss/train | █▅▄▄▃▃▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▁▁▁▂▂▂▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▅▄▄▃▃▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▁▁▁▂▂▂▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 96.16 |
Accuracy/val | 95.98 |
Loss/train | 0.00308 |
Loss/val | 0.00336 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_072901-o8kgc485/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: 65kk9gew with config:
wandb: batch_size: 64
wandb: epochs: 50
wandb: learning_rate: 1e-05
wandb: optimizer: sgd
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_073320-65kk9gew
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0081. Train Acc: 80.4525, Test loss: 0.0081. Test Acc: 80.4400. Time/epoch: 3.1321
EPOCH 10. Progress: 20.0%.
Train loss: 0.0028. Train Acc: 93.0775, Test loss: 0.0030. Test Acc: 92.9500. Time/epoch: 2.9711
EPOCH 20. Progress: 40.0%.
Train loss: 0.0025. Train Acc: 93.5775, Test loss: 0.0026. Test Acc: 93.5400. Time/epoch: 2.9327
EPOCH 30. Progress: 60.0%.
Train loss: 0.0022. Train Acc: 94.4950, Test loss: 0.0023. Test Acc: 94.5300. Time/epoch: 2.9275
EPOCH 40. Progress: 80.0%.
Train loss: 0.0020. Train Acc: 95.2375, Test loss: 0.0021. Test Acc: 95.0200. Time/epoch: 3.0979
EPOCH 50. Progress: 100.0%.
Train loss: 0.0018. Train Acc: 95.4875, Test loss: 0.0019. Test Acc: 95.4800. Time/epoch: 3.0886
Run history:
Accuracy/train | ▁▃▄▅▆▆▆▆▇▇▇▇▇▇▇▇▇▇▇█▇█▇███▇██▇██████████ |
Accuracy/val | ▁▃▄▅▆▆▆▆▇▇▇▇▇▇▇▇▇▇██▇█████▇██▇██████████ |
Loss/train | █▆▅▄▃▃▃▃▂▂▂▂▂▂▂▂▂▂▂▁▂▁▂▁▁▁▁▁▁▂▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▆▅▄▃▃▃▃▂▂▂▂▂▂▂▂▂▂▂▁▂▁▂▁▁▁▁▁▁▂▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 95.4875 |
Accuracy/val | 95.48 |
Loss/train | 0.00184 |
Loss/val | 0.00192 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_073320-65kk9gew/logs
wandb: Agent Starting Run: havnxul7 with config:
wandb: batch_size: 32
wandb: epochs: 10
wandb: learning_rate: 0.001
wandb: optimizer: sgd
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_073608-havnxul7
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0206. Train Acc: 76.8350, Test loss: 0.0208. Test Acc: 77.0900. Time/epoch: 4.5854
EPOCH 10. Progress: 100.0%.
Train loss: 0.0245. Train Acc: 60.5525, Test loss: 0.0244. Test Acc: 61.1900. Time/epoch: 4.5407
Run history:
Accuracy/train | ▅▆▆▇▇█▁▁▁▁▁ |
Accuracy/val | ▅▆▆█▇█▁▁▁▁▁ |
Loss/train | ▅▃▃▁▃▁█▆▆▆▆ |
Loss/val | ▅▃▃▁▃▁█▆▆▆▆ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 60.5525 |
Accuracy/val | 61.19 |
Loss/train | 0.02449 |
Loss/val | 0.02439 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_073608-havnxul7/logs
wandb: Agent Starting Run: 1xwptrqw with config:
wandb: batch_size: 64
wandb: epochs: 50
wandb: learning_rate: 3e-05
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_073714-1xwptrqw
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0033. Train Acc: 91.8650, Test loss: 0.0034. Test Acc: 91.6500. Time/epoch: 3.1650
EPOCH 10. Progress: 20.0%.
Train loss: 0.0021. Train Acc: 94.7550, Test loss: 0.0022. Test Acc: 94.7100. Time/epoch: 2.9932
EPOCH 20. Progress: 40.0%.
Train loss: 0.0019. Train Acc: 95.2250, Test loss: 0.0020. Test Acc: 95.3900. Time/epoch: 3.0052
EPOCH 30. Progress: 60.0%.
Train loss: 0.0018. Train Acc: 95.3650, Test loss: 0.0019. Test Acc: 95.5800. Time/epoch: 3.1262
EPOCH 40. Progress: 80.0%.
Train loss: 0.0017. Train Acc: 95.7625, Test loss: 0.0018. Test Acc: 95.9000. Time/epoch: 3.1511
EPOCH 50. Progress: 100.0%.
Train loss: 0.0017. Train Acc: 95.7825, Test loss: 0.0018. Test Acc: 95.8400. Time/epoch: 3.1237
Run history:
Accuracy/train | ▁▃▄▄▄▅▄▆▆▆▆▅▆▆▇▇▇▆▇▆▆▇▇▇▇▇▇▆▆▇▇█▇██▆████ |
Accuracy/val | ▁▃▄▄▅▅▄▆▆▆▆▅▆▆▇▇▇▆▇▆▆▇▇▇▇▇█▆▆▇▇▇▇██▇██▇█ |
Loss/train | █▆▅▄▄▄▄▃▃▃▃▃▃▂▂▂▂▃▂▂▃▂▂▂▂▂▁▂▃▁▂▁▂▁▁▂▁▁▁▁ |
Loss/val | █▆▅▄▄▄▄▃▃▃▃▃▃▂▂▂▂▃▂▂▃▂▂▂▁▂▁▂▃▁▂▁▂▁▁▂▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 95.7825 |
Accuracy/val | 95.84 |
Loss/train | 0.00173 |
Loss/val | 0.00178 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_073714-1xwptrqw/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: mgnsl2hp with config:
wandb: batch_size: 64
wandb: epochs: 10
wandb: learning_rate: 3e-05
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_074012-mgnsl2hp
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0038. Train Acc: 89.9425, Test loss: 0.0038. Test Acc: 90.0700. Time/epoch: 3.1821
EPOCH 10. Progress: 100.0%.
Train loss: 0.0021. Train Acc: 94.4625, Test loss: 0.0021. Test Acc: 94.4500. Time/epoch: 3.1261
Run history:
Accuracy/train | ▁▃▅▅▆▆▇▇██▇ |
Accuracy/val | ▁▃▅▅▆▆▇▇▇█▇ |
Loss/train | █▆▅▄▃▃▂▂▁▁▂ |
Loss/val | █▆▄▄▃▃▂▂▂▁▂ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 94.4625 |
Accuracy/val | 94.45 |
Loss/train | 0.00207 |
Loss/val | 0.00215 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_074012-mgnsl2hp/logs
wandb: Agent Starting Run: c5uxcduw with config:
wandb: batch_size: 32
wandb: epochs: 20
wandb: learning_rate: 0.01
wandb: optimizer: sgd
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_074058-c5uxcduw
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0481. Train Acc: 36.8250, Test loss: 0.0480. Test Acc: 37.5400. Time/epoch: 4.5902
EPOCH 10. Progress: 50.0%.
Train loss: 0.0480. Train Acc: 36.8250, Test loss: 0.0479. Test Acc: 37.5400. Time/epoch: 4.7131
EPOCH 20. Progress: 100.0%.
Train loss: 0.0480. Train Acc: 36.8250, Test loss: 0.0480. Test Acc: 37.5400. Time/epoch: 4.7224
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | ▄▃▅▂▄▂▅▅▂▁▂▅▂▅█▃▃▇▁▁▂ |
Loss/val | █▄▃▃▇▄▄▅▄▅▃▄▄▅▇▃▆▄▂▁▅ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.04805 |
Loss/val | 0.04796 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_074058-c5uxcduw/logs
wandb: Agent Starting Run: xuisv8ry with config:
wandb: batch_size: 64
wandb: epochs: 10
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_074246-xuisv8ry
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0030. Train Acc: 91.0575, Test loss: 0.0032. Test Acc: 91.1900. Time/epoch: 3.1646
EPOCH 10. Progress: 100.0%.
Train loss: 0.0013. Train Acc: 96.5650, Test loss: 0.0015. Test Acc: 96.3400. Time/epoch: 3.2859
Run history:
Accuracy/train | ▁▁▁▅▅▆▇▆▇▇█ |
Accuracy/val | ▂▁▂▆▅▇▇▆▇▇█ |
Loss/train | ▇█▇▄▄▃▂▃▂▂▁ |
Loss/val | ▇█▆▃▄▃▂▃▂▂▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 96.565 |
Accuracy/val | 96.34 |
Loss/train | 0.00134 |
Loss/val | 0.00153 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_074246-xuisv8ry/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: 46pg2e94 with config:
wandb: batch_size: 32
wandb: epochs: 50
wandb: learning_rate: 1e-05
wandb: optimizer: sgd
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_074344-46pg2e94
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0089. Train Acc: 90.5625, Test loss: 0.0089. Test Acc: 90.7700. Time/epoch: 4.5626
EPOCH 10. Progress: 20.0%.
Train loss: 0.0043. Train Acc: 94.3400, Test loss: 0.0045. Test Acc: 94.4700. Time/epoch: 4.5405
EPOCH 20. Progress: 40.0%.
Train loss: 0.0038. Train Acc: 95.2925, Test loss: 0.0040. Test Acc: 95.2900. Time/epoch: 4.6378
EPOCH 30. Progress: 60.0%.
Train loss: 0.0035. Train Acc: 95.5525, Test loss: 0.0038. Test Acc: 95.5200. Time/epoch: 4.7263
EPOCH 40. Progress: 80.0%.
Train loss: 0.0033. Train Acc: 95.8100, Test loss: 0.0036. Test Acc: 95.6200. Time/epoch: 4.6638
EPOCH 50. Progress: 100.0%.
Train loss: 0.0031. Train Acc: 96.2025, Test loss: 0.0034. Test Acc: 96.0900. Time/epoch: 4.5067
Run history:
Accuracy/train | ▁▁▃▄▅▅▅▆▆▆▆▆▆▆▆▆▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇███▇▇▇██ |
Accuracy/val | ▁▂▃▄▅▅▅▆▆▆▆▇▆▆▆▆▇▇▇▇▇▆▇▇▇▇▆▇▇▇▇▇███▆▇▇▇█ |
Loss/train | █▆▅▄▃▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▂▂▁▁▁▂▂▁▁▁▁▁▁▁▁▂▁▁▁▁ |
Loss/val | █▆▅▄▃▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▂▂▁▁▂▂▂▁▁▂▁▁▁▁▁▂▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 96.2025 |
Accuracy/val | 96.09 |
Loss/train | 0.00306 |
Loss/val | 0.0034 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_074344-46pg2e94/logs
wandb: Agent Starting Run: zs7y16lw with config:
wandb: batch_size: 128
wandb: epochs: 50
wandb: learning_rate: 3e-05
wandb: optimizer: rmsprop
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_074752-zs7y16lw
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0018. Train Acc: 91.1075, Test loss: 0.0019. Test Acc: 91.1800. Time/epoch: 2.3901
EPOCH 10. Progress: 20.0%.
Train loss: 0.0009. Train Acc: 95.4950, Test loss: 0.0010. Test Acc: 95.2600. Time/epoch: 2.3338
EPOCH 20. Progress: 40.0%.
Train loss: 0.0012. Train Acc: 93.6225, Test loss: 0.0012. Test Acc: 93.3800. Time/epoch: 2.3350
EPOCH 30. Progress: 60.0%.
Train loss: 0.0009. Train Acc: 95.1950, Test loss: 0.0010. Test Acc: 94.8400. Time/epoch: 2.1745
EPOCH 40. Progress: 80.0%.
Train loss: 0.0007. Train Acc: 96.6200, Test loss: 0.0008. Test Acc: 96.4200. Time/epoch: 2.1733
EPOCH 50. Progress: 100.0%.
Train loss: 0.0006. Train Acc: 96.9625, Test loss: 0.0007. Test Acc: 96.6100. Time/epoch: 2.3403
Run history:
Accuracy/train | ▁▁▃▅▂▅▅▆▆▆▆▄▆▅▇▅▄▇▇▇▇▇▇▇▆▇▇▅████▇▇██▇███ |
Accuracy/val | ▁▁▃▅▂▅▅▆▆▆▆▄▆▅▇▅▄▇▇▇▇▇▇▇▅▇▇▅▇▇▇█▇▇██▇▇█▇ |
Loss/train | █▇▅▄▆▄▄▃▃▃▃▄▃▃▂▃▄▂▂▂▂▂▂▂▃▂▂▃▁▁▁▁▂▂▁▁▂▁▁▁ |
Loss/val | █▇▆▄▆▄▄▃▃▃▃▅▃▃▂▃▄▂▂▂▂▂▂▂▃▂▂▃▁▂▂▁▂▂▁▁▂▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 96.9625 |
Accuracy/val | 96.61 |
Loss/train | 0.0006 |
Loss/val | 0.0007 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_074752-zs7y16lw/logs
wandb: Agent Starting Run: kwgjwpfh with config:
wandb: batch_size: 128
wandb: epochs: 20
wandb: learning_rate: 1e-05
wandb: optimizer: sgd
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_075005-kwgjwpfh
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0055. Train Acc: 74.1500, Test loss: 0.0055. Test Acc: 74.1300. Time/epoch: 2.1878
EPOCH 10. Progress: 50.0%.
Train loss: 0.0016. Train Acc: 92.2425, Test loss: 0.0016. Test Acc: 92.3200. Time/epoch: 2.1617
EPOCH 20. Progress: 100.0%.
Train loss: 0.0013. Train Acc: 93.5700, Test loss: 0.0014. Test Acc: 93.5200. Time/epoch: 2.3063
Run history:
Accuracy/train | ▁▄▆▆▆▇▇▇▇▇███████████ |
Accuracy/val | ▁▄▅▆▆▇▇▇▇████████████ |
Loss/train | █▅▄▃▃▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▅▄▃▃▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 93.57 |
Accuracy/val | 93.52 |
Loss/train | 0.00132 |
Loss/val | 0.00137 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_075005-kwgjwpfh/logs
wandb: Agent Starting Run: iqjhniw2 with config:
wandb: batch_size: 32
wandb: epochs: 20
wandb: learning_rate: 1e-05
wandb: optimizer: rmsprop
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_075106-iqjhniw2
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0094. Train Acc: 89.3450, Test loss: 0.0094. Test Acc: 89.3800. Time/epoch: 4.7114
EPOCH 10. Progress: 50.0%.
Train loss: 0.0044. Train Acc: 94.7650, Test loss: 0.0045. Test Acc: 94.8600. Time/epoch: 4.6636
EPOCH 20. Progress: 100.0%.
Train loss: 0.0040. Train Acc: 95.4100, Test loss: 0.0041. Test Acc: 95.5200. Time/epoch: 4.6925
Run history:
Accuracy/train | ▁▄▅▆▆▇▇▆▇▇▇▆▇▇▇██▇▇██ |
Accuracy/val | ▁▄▅▆▅▆▇▆▇▇▇▆▇█▇██▇███ |
Loss/train | █▅▄▃▃▂▂▂▂▂▂▂▁▁▁▁▁▂▁▁▁ |
Loss/val | █▅▄▃▃▂▂▂▂▂▂▂▁▁▁▁▁▂▁▁▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 95.41 |
Accuracy/val | 95.52 |
Loss/train | 0.00396 |
Loss/val | 0.00408 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_075106-iqjhniw2/logs
wandb: Agent Starting Run: y33bnpyd with config:
wandb: batch_size: 128
wandb: epochs: 50
wandb: learning_rate: 3e-05
wandb: optimizer: adam
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_075258-y33bnpyd
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0024. Train Acc: 86.4350, Test loss: 0.0024. Test Acc: 86.7200. Time/epoch: 2.4388
EPOCH 10. Progress: 20.0%.
Train loss: 0.0009. Train Acc: 95.3050, Test loss: 0.0010. Test Acc: 95.1700. Time/epoch: 2.2733
EPOCH 20. Progress: 40.0%.
Train loss: 0.0008. Train Acc: 95.9575, Test loss: 0.0009. Test Acc: 95.8600. Time/epoch: 2.4097
EPOCH 30. Progress: 60.0%.
Train loss: 0.0007. Train Acc: 96.5525, Test loss: 0.0008. Test Acc: 96.4200. Time/epoch: 2.4182
EPOCH 40. Progress: 80.0%.
Train loss: 0.0007. Train Acc: 96.6775, Test loss: 0.0007. Test Acc: 96.4200. Time/epoch: 2.4077
EPOCH 50. Progress: 100.0%.
Train loss: 0.0006. Train Acc: 97.0450, Test loss: 0.0007. Test Acc: 96.5900. Time/epoch: 2.2643
Run history:
Accuracy/train | ▁▄▅▆▆▆▆▆▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇███▇▇▇▇██████████ |
Accuracy/val | ▁▄▅▆▆▆▇▆▇▇▆▇▇▇▇▇▇▇▇▇█▇▇███▇▇▇▇██████████ |
Loss/train | █▅▄▄▃▃▃▃▂▂▃▂▂▂▂▂▂▂▂▂▂▂▂▁▁▁▂▂▂▂▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▅▄▄▃▃▃▃▂▂▃▂▂▂▂▂▂▂▂▂▂▂▂▁▁▁▂▂▂▂▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 97.045 |
Accuracy/val | 96.59 |
Loss/train | 0.00062 |
Loss/val | 0.0007 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_075258-y33bnpyd/logs
wandb: Agent Starting Run: i9579k9i with config:
wandb: batch_size: 32
wandb: epochs: 20
wandb: learning_rate: 1e-05
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_075514-i9579k9i
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0102. Train Acc: 85.2700, Test loss: 0.0103. Test Acc: 85.2000. Time/epoch: 4.8704
EPOCH 10. Progress: 50.0%.
Train loss: 0.0054. Train Acc: 93.0500, Test loss: 0.0056. Test Acc: 92.8800. Time/epoch: 4.6998
EPOCH 20. Progress: 100.0%.
Train loss: 0.0039. Train Acc: 95.1175, Test loss: 0.0042. Test Acc: 94.9600. Time/epoch: 4.6657
Run history:
Accuracy/train | ▁▂▃▂▄▄▅▅▆▆▇▇▇▇▇█▇▇███ |
Accuracy/val | ▁▂▃▂▄▄▅▅▆▆▇▇▇▇▇▇▇▇███ |
Loss/train | █▆▅▅▅▄▄▄▃▃▃▂▂▂▂▂▂▂▁▁▁ |
Loss/val | █▆▅▅▅▄▄▄▃▃▃▂▂▂▂▂▂▂▁▁▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 95.1175 |
Accuracy/val | 94.96 |
Loss/train | 0.00387 |
Loss/val | 0.00416 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_075514-i9579k9i/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: fzkj3z7r with config:
wandb: batch_size: 32
wandb: epochs: 10
wandb: learning_rate: 0.01
wandb: optimizer: rmsprop
wandb: weight_decay: 0.0005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_075717-fzkj3z7r
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: rmsprop
EPOCH 0. Progress: 0.0%.
Train loss: 0.0481. Train Acc: 36.8250, Test loss: 0.0481. Test Acc: 37.5400. Time/epoch: 4.8334
EPOCH 10. Progress: 100.0%.
Train loss: 0.0481. Train Acc: 36.8250, Test loss: 0.0480. Test Acc: 37.5400. Time/epoch: 4.8037
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | █▄▅▁▄▃▃▁▃▄▃ |
Loss/val | █▅▅▁▃▅▂▂▃▄▂ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.04807 |
Loss/val | 0.04796 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_075717-fzkj3z7r/logs
wandb: Agent Starting Run: t97rlspn with config:
wandb: batch_size: 128
wandb: epochs: 50
wandb: learning_rate: 1e-05
wandb: optimizer: sgd
wandb: weight_decay: 0.005
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_075825-t97rlspn
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: sgd
EPOCH 0. Progress: 0.0%.
Train loss: 0.0079. Train Acc: 78.0575, Test loss: 0.0079. Test Acc: 78.7000. Time/epoch: 2.3503
EPOCH 10. Progress: 20.0%.
Train loss: 0.0019. Train Acc: 89.7800, Test loss: 0.0020. Test Acc: 89.9900. Time/epoch: 2.2950
EPOCH 20. Progress: 40.0%.
Train loss: 0.0014. Train Acc: 92.7375, Test loss: 0.0015. Test Acc: 92.6600. Time/epoch: 2.1827
EPOCH 30. Progress: 60.0%.
Train loss: 0.0013. Train Acc: 93.2475, Test loss: 0.0014. Test Acc: 93.3500. Time/epoch: 2.1846
EPOCH 40. Progress: 80.0%.
Train loss: 0.0012. Train Acc: 93.8700, Test loss: 0.0013. Test Acc: 93.9200. Time/epoch: 2.1709
EPOCH 50. Progress: 100.0%.
Train loss: 0.0012. Train Acc: 93.9200, Test loss: 0.0013. Test Acc: 94.0400. Time/epoch: 2.3071
Run history:
Accuracy/train | ▁▂▃▄▅▅▅▆▆▆▆▇▇▇▇▇▇▇▇▇██▇▇████████████████ |
Accuracy/val | ▁▂▃▄▅▅▆▆▆▆▆▇▇▇▇▇▇▇▇▇███▇████████████████ |
Loss/train | █▅▄▃▃▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▅▄▃▃▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 93.92 |
Accuracy/val | 94.04 |
Loss/train | 0.00119 |
Loss/val | 0.00126 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_075825-t97rlspn/logs
wandb: Agent Starting Run: ruzwy4t8 with config:
wandb: batch_size: 32
wandb: epochs: 10
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.05
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_080034-ruzwy4t8
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/4bmop0um
optimizer: adam
EPOCH 0. Progress: 0.0%.
Train loss: 0.0057. Train Acc: 92.0350, Test loss: 0.0057. Test Acc: 91.7600. Time/epoch: 4.9613
EPOCH 10. Progress: 100.0%.
Train loss: 0.0026. Train Acc: 96.9525, Test loss: 0.0030. Test Acc: 96.6400. Time/epoch: 5.1348
Run history:
Accuracy/train | ▁▄▅▄▆▆██▇█▇ |
Accuracy/val | ▁▄▆▄▆▆██▇█▇ |
Loss/train | █▄▄▅▃▃▁▁▁▁▂ |
Loss/val | █▄▄▅▃▃▁▂▂▂▂ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 96.9525 |
Accuracy/val | 96.64 |
Loss/train | 0.00257 |
Loss/val | 0.00295 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
./wandb/run-20230518_080034-ruzwy4t8/logs
wandb: Agent Starting Run: aca9t601 with config:
wandb: batch_size: 32
wandb: epochs: 50
wandb: learning_rate: 0.0003
wandb: optimizer: sgd
wandb: weight_decay: 0.0005
wandb: Ctrl + C detected. Stopping sweep.
Problem at: /tmp/ipykernel_682325/368360005.py 26 train
Traceback (most recent call last):
File "/gpfs/gibbs/project/dijk/ahf38/conda_envs/geo_comp2/lib/python3.8/site-packages/wandb/sdk/wandb_init.py", line 1150, in init
run = wi.init()
File "/gpfs/gibbs/project/dijk/ahf38/conda_envs/geo_comp2/lib/python3.8/site-packages/wandb/sdk/wandb_init.py", line 799, in init
run_start_result = run_start_handle.wait(timeout=30)
File "/gpfs/gibbs/project/dijk/ahf38/conda_envs/geo_comp2/lib/python3.8/site-packages/wandb/sdk/lib/mailbox.py", line 283, in wait
found, abandoned = self._slot._get_and_clear(timeout=wait_timeout)
File "/gpfs/gibbs/project/dijk/ahf38/conda_envs/geo_comp2/lib/python3.8/site-packages/wandb/sdk/lib/mailbox.py", line 130, in _get_and_clear
if self._wait(timeout=timeout):
File "/gpfs/gibbs/project/dijk/ahf38/conda_envs/geo_comp2/lib/python3.8/site-packages/wandb/sdk/lib/mailbox.py", line 126, in _wait
return self._event.wait(timeout=timeout)
File "/gpfs/gibbs/project/dijk/ahf38/conda_envs/geo_comp2/lib/python3.8/threading.py", line 558, in wait
signaled = self._cond.wait(timeout)
File "/gpfs/gibbs/project/dijk/ahf38/conda_envs/geo_comp2/lib/python3.8/threading.py", line 306, in wait
gotit = waiter.acquire(True, timeout)
Exception
Using a smarter search
[ ]:
# Make a smarter search
# Configure the sweep – specify the parameters to search through, the search strategy, the optimization metric et all.
sweep_config = {
'method': 'bayes', #grid, random
'metric': {
'name': 'Accuracy/val',
'goal': 'maximize'
},
'parameters': {
'epochs': {
'values': [10, 20, 50, 100]
},
'batch_size': {
'values': [32,64,128, 512]
},
'weight_decay': {
'values': [0.0005, 0.005, 0.05]
},
'learning_rate': {
'values': [1e-2,1e-3, 1e-4, 3e-4, 3e-5, 1e-5]
},
'optimizer': {
'values': ['adam']
}
}
}
[ ]:
class CNNet(nn.Module):
def __init__(self):
super().__init__()
self.conv1 = nn.Conv2d(4, 6, 5)
self.pool = nn.MaxPool2d(2, 2)
self.conv2 = nn.Conv2d(6, 16, 5)
self.fc1 = nn.Linear(16 * 4 * 4, 120)
self.fc2 = nn.Linear(120, 84)
self.fc3 = nn.Linear(84, 6)
def forward(self, x):
x = self.pool(F.relu(self.conv1(x)))
x = self.pool(F.relu(self.conv2(x)))
x = torch.flatten(x, 1) # flatten all dimensions except batch
x = F.relu(self.fc1(x))
x = F.relu(self.fc2(x))
x = self.fc3(x)
return x
model = CNNet()
[ ]:
# Initialize a new sweep
# Arguments:
# – sweep_config: the sweep config dictionary defined above
# – entity: Set the username for the sweep
# – project: Set the project name for the sweep
sweep_id = wandb.sweep(sweep_config, entity="ahof1704", project="CNN_Sat_sweep")
Create sweep with ID: tyzcsl8s
Sweep URL: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
[ ]:
# Training and Evaluation routines for Sweeping
import time
loss_fn = nn.CrossEntropyLoss().to(device)
def train(config=None):
"""
This is a standard training loop, which leaves some parts to be filled in.
INPUT:
:param model: an untrained pytorch model
:param loss_fn: e.g. Cross Entropy loss of Mean Squared Error.
:param optimizer: the model optimizer, initialized with a learning rate.
:param training_set: The training data, in a dataloader for easy iteration.
:param test_loader: The testing data, in a dataloader for easy iteration.
"""
# config_defaults = {
# 'epochs': 2,
# 'batch_size': 128,
# 'weight_decay': 0.0005,
# 'learning_rate': 1e-3,
# 'activation': 'relu',
# 'optimizer': 'nadam',
# 'seed': 42
# }
with wandb.init(config=config):
verbose=False
model = CNNet().to(device)
wandb.watch(model, log="all")
model.train()
# Config is a variable that holds and saves hyperparameters and inputs
config = wandb.config
# Define the optimizer
if config.optimizer=='sgd':
optimizer = torch.optim.SGD(model.parameters(), lr=config.learning_rate, weight_decay=config.weight_decay, momentum=0.9, nesterov=True)
elif config.optimizer=='rmsprop':
optimizer = torch.optim.RMSprop(model.parameters(), lr=config.learning_rate, weight_decay=config.weight_decay)
elif config.optimizer=='adam':
optimizer = torch.optim.Adam(model.parameters(), lr=config.learning_rate, betas=(0.9, 0.999))
elif config.optimizer=='nadam':
optimizer = torch.optim.Nadam(model.parameters(), lr=config.learning_rate, betas=(0.9, 0.999))
# -- create dataloaders
train_sampler = SubsetRandomSampler(train_indices)
valid_sampler = SubsetRandomSampler(val_indices)
dataloaders = {
'train': torch.utils.data.DataLoader(dataset, batch_size=config.batch_size, sampler=train_sampler),
'test': torch.utils.data.DataLoader(dataset, batch_size=config.batch_size, sampler=valid_sampler),
'all': torch.utils.data.DataLoader(dataset, batch_size=5000, shuffle=False),
}
train_loader = dataloaders['train']
test_loader = dataloaders['test']
# if num_epochs is None:
# num_epochs = 100
# print('n. of epochs: {}'.format(num_epochs))
best_acc=-1
for epoch in range(config.epochs+1):
start = time.time()
# loop through each data point in the training set
for data, targets in train_loader:
# run the model on the data
model_input = data.permute(0, 3, 2, 1).to(device)
if verbose: print('model_input.shape: {}'.format(model_input.shape))
# Clear gradients w.r.t. parameters
optimizer.zero_grad()
out = model(model_input) # The second output is the latent representation
if verbose:
print('targets.shape: {}'.format(targets.shape))
print('targets: {}'.format(targets))
print('out.shape: {}'.format(out.shape))
print('out: {}'.format(out))
# Calculate the loss
targets = targets.type(torch.LongTensor).to(device) # add an extra dimension to keep CrossEntropy happy.
if verbose: print('targets.shape: {}'.format(targets.shape))
loss = loss_fn(out,targets)
if verbose: print('loss: {}'.format(loss))
# Find the gradients of our loss via backpropogation
loss.backward()
# Adjust accordingly with the optimizer
optimizer.step()
loss_train, acc_train = evaluate(model,train_loader,verbose)
loss_test, acc_test = evaluate(model,test_loader,verbose)
# Give status reports every 100 epochs
if epoch % 10==0:
print(f" EPOCH {epoch}. Progress: {epoch/config.epochs*100}%. ")
print(" Train loss: {:.4f}. Train Acc: {:.4f}, Test loss: {:.4f}. Test Acc: {:.4f}. Time/epoch: {:.4f}".format(loss_train, acc_train, loss_test, acc_test, (time.time() - start))) #TODO: implement the evaluate function to provide performance statistics during training.
wandb.log({
"Loss/train": loss_train,
"Loss/val": loss_test,
"Accuracy/train": acc_train,
"Accuracy/val": acc_test,
"epoch": epoch
}, step=epoch)
if acc_test>best_acc:
print('saving best checkpoint at epoch: {}, Acc: {}'.format(epoch,acc_test))
best_acc = acc_test
torch.save(model.state_dict(), os.path.join(wandb.run.dir,'model.pt'))
def evaluate(model, evaluation_set, verbose=False):
"""
Evaluates the given model on the given dataset.
Returns the percentage of correct classifications out of total classifications.
"""
model.eval()
with torch.no_grad(): # this disables backpropogation, which makes the model run much more quickly.
correct = 0
total = 0
loss_all=0
for data, targets in evaluation_set:
# run the model on the data
model_input = data.permute(0, 3, 2, 1).to(device)
if verbose:
print('model_input.shape: {}'.format(model_input.shape))
print('targets.shape: {}'.format(targets.shape))
out = model(model_input)
targets = targets.type(torch.LongTensor).to(device)
loss = loss_fn(out,targets)
if verbose: print('out[:5]: {}'.format(out[:5]))
loss_all+=loss.item()
# the class with the highest energy is what we choose as prediction
_, predicted = torch.max(out.data, 1)
total += targets.size(0)
correct += (predicted == targets).sum().item()
acc = 100 * correct / total
loss = loss_all/total
return loss, acc
[ ]:
wandb.agent(sweep_id, train)
wandb: Agent Starting Run: eaergb9w with config:
wandb: batch_size: 512
wandb: epochs: 50
wandb: learning_rate: 0.001
wandb: optimizer: adam
wandb: weight_decay: 0.005
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_084935-eaergb9w
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0004. Train Acc: 92.3950, Test loss: 0.0004. Test Acc: 92.1800. Time/epoch: 1.5736
saving best checkpoint at epoch: 0, Acc: 92.18
saving best checkpoint at epoch: 1, Acc: 94.77
saving best checkpoint at epoch: 3, Acc: 95.09
saving best checkpoint at epoch: 4, Acc: 95.15
saving best checkpoint at epoch: 6, Acc: 95.75
saving best checkpoint at epoch: 8, Acc: 95.89
EPOCH 10. Progress: 20.0%.
Train loss: 0.0002. Train Acc: 96.2850, Test loss: 0.0002. Test Acc: 96.1300. Time/epoch: 1.6753
saving best checkpoint at epoch: 10, Acc: 96.13
saving best checkpoint at epoch: 11, Acc: 96.24
saving best checkpoint at epoch: 12, Acc: 96.29
saving best checkpoint at epoch: 13, Acc: 96.31
saving best checkpoint at epoch: 16, Acc: 96.85
EPOCH 20. Progress: 40.0%.
Train loss: 0.0001. Train Acc: 97.5450, Test loss: 0.0002. Test Acc: 97.2100. Time/epoch: 1.5347
saving best checkpoint at epoch: 20, Acc: 97.21
EPOCH 30. Progress: 60.0%.
Train loss: 0.0002. Train Acc: 96.6350, Test loss: 0.0002. Test Acc: 96.0200. Time/epoch: 1.5355
saving best checkpoint at epoch: 35, Acc: 97.35
EPOCH 40. Progress: 80.0%.
Train loss: 0.0001. Train Acc: 97.9400, Test loss: 0.0002. Test Acc: 97.0300. Time/epoch: 1.6826
saving best checkpoint at epoch: 46, Acc: 97.37
EPOCH 50. Progress: 100.0%.
Train loss: 0.0001. Train Acc: 98.4200, Test loss: 0.0001. Test Acc: 97.5800. Time/epoch: 1.5738
saving best checkpoint at epoch: 50, Acc: 97.58
Run history:
Accuracy/train | ▂▄▄▅▁▅▃▅▆▆▆▆▄▆▆▃▇▆▇▅▄▅▇▄▆▇▇▆▇▇▇▅▇▆▆▇█▆▇█ |
Accuracy/val | ▁▅▄▅▁▆▄▆▆▆▆▆▄▇▆▃█▇▇▆▄▆▇▄▆▇▇▇█▇▇▆▇▆▆▇█▆▇█ |
Loss/train | █▅▅▅█▄▆▄▄▄▃▄▅▃▃▆▂▃▂▄▆▄▂▅▃▂▂▂▂▂▂▄▂▃▃▂▁▃▂▁ |
Loss/val | █▅▅▄█▃▅▃▃▃▃▃▅▂▃▆▁▂▁▄▆▄▂▅▃▂▂▂▂▂▂▄▂▃▄▂▁▄▂▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.42 |
Accuracy/val | 97.58 |
Loss/train | 8e-05 |
Loss/val | 0.00015 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_084935-eaergb9w/logs
wandb: Agent Starting Run: imhc2czd with config:
wandb: batch_size: 128
wandb: epochs: 20
wandb: learning_rate: 3e-05
wandb: optimizer: adam
wandb: weight_decay: 0.005
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_085111-imhc2czd
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0024. Train Acc: 89.1650, Test loss: 0.0024. Test Acc: 89.2400. Time/epoch: 2.2423
saving best checkpoint at epoch: 0, Acc: 89.24
saving best checkpoint at epoch: 1, Acc: 90.78
saving best checkpoint at epoch: 2, Acc: 92.33
saving best checkpoint at epoch: 3, Acc: 92.54
saving best checkpoint at epoch: 4, Acc: 93.38
saving best checkpoint at epoch: 5, Acc: 93.91
saving best checkpoint at epoch: 6, Acc: 93.98
saving best checkpoint at epoch: 8, Acc: 94.29
saving best checkpoint at epoch: 9, Acc: 94.53
EPOCH 10. Progress: 50.0%.
Train loss: 0.0012. Train Acc: 93.6325, Test loss: 0.0012. Test Acc: 93.4200. Time/epoch: 2.1841
saving best checkpoint at epoch: 11, Acc: 94.66
saving best checkpoint at epoch: 12, Acc: 94.94
saving best checkpoint at epoch: 16, Acc: 95.02
saving best checkpoint at epoch: 18, Acc: 95.11
saving best checkpoint at epoch: 19, Acc: 95.26
EPOCH 20. Progress: 100.0%.
Train loss: 0.0009. Train Acc: 95.8200, Test loss: 0.0009. Test Acc: 95.6600. Time/epoch: 2.1753
saving best checkpoint at epoch: 20, Acc: 95.66
Run history:
Accuracy/train | ▁▃▄▄▅▆▆▆▆▇▆▇▇▇▇▇▇▇▇██ |
Accuracy/val | ▁▃▄▅▆▆▆▆▇▇▆▇▇▇▇▇▇▇▇██ |
Loss/train | █▅▄▄▃▃▂▂▂▂▂▂▂▁▂▁▁▂▁▁▁ |
Loss/val | █▅▄▄▃▃▂▂▂▂▂▂▂▂▂▂▂▂▁▁▁ |
epoch | ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇██ |
Run summary:
Accuracy/train | 95.82 |
Accuracy/val | 95.66 |
Loss/train | 0.00087 |
Loss/val | 0.00092 |
epoch | 20 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_085111-imhc2czd/logs
wandb: Agent Starting Run: ts1a9t68 with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 0.0001
wandb: optimizer: adam
wandb: weight_decay: 0.005
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_085212-ts1a9t68
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0006. Train Acc: 88.8700, Test loss: 0.0006. Test Acc: 88.9000. Time/epoch: 1.7003
saving best checkpoint at epoch: 0, Acc: 88.9
saving best checkpoint at epoch: 1, Acc: 91.84
saving best checkpoint at epoch: 2, Acc: 92.76
saving best checkpoint at epoch: 3, Acc: 93.44
saving best checkpoint at epoch: 4, Acc: 93.47
saving best checkpoint at epoch: 6, Acc: 94.24
saving best checkpoint at epoch: 8, Acc: 94.68
saving best checkpoint at epoch: 9, Acc: 94.9
EPOCH 10. Progress: 10.0%.
Train loss: 0.0003. Train Acc: 93.0725, Test loss: 0.0003. Test Acc: 93.1100. Time/epoch: 1.6812
saving best checkpoint at epoch: 12, Acc: 95.02
saving best checkpoint at epoch: 14, Acc: 95.07
saving best checkpoint at epoch: 15, Acc: 95.68
EPOCH 20. Progress: 20.0%.
Train loss: 0.0002. Train Acc: 95.9475, Test loss: 0.0002. Test Acc: 95.7700. Time/epoch: 1.5469
saving best checkpoint at epoch: 20, Acc: 95.77
saving best checkpoint at epoch: 21, Acc: 96.0
saving best checkpoint at epoch: 23, Acc: 96.22
saving best checkpoint at epoch: 24, Acc: 96.25
saving best checkpoint at epoch: 26, Acc: 96.26
saving best checkpoint at epoch: 27, Acc: 96.32
saving best checkpoint at epoch: 28, Acc: 96.52
EPOCH 30. Progress: 30.0%.
Train loss: 0.0002. Train Acc: 96.6025, Test loss: 0.0002. Test Acc: 96.2700. Time/epoch: 1.7239
saving best checkpoint at epoch: 32, Acc: 96.6
saving best checkpoint at epoch: 34, Acc: 96.78
saving best checkpoint at epoch: 39, Acc: 96.92
EPOCH 40. Progress: 40.0%.
Train loss: 0.0002. Train Acc: 97.1050, Test loss: 0.0002. Test Acc: 96.7100. Time/epoch: 1.7287
saving best checkpoint at epoch: 46, Acc: 96.96
EPOCH 50. Progress: 50.0%.
Train loss: 0.0001. Train Acc: 97.3550, Test loss: 0.0002. Test Acc: 96.9100. Time/epoch: 1.5700
saving best checkpoint at epoch: 51, Acc: 97.04
saving best checkpoint at epoch: 54, Acc: 97.17
EPOCH 60. Progress: 60.0%.
Train loss: 0.0001. Train Acc: 97.4800, Test loss: 0.0002. Test Acc: 97.0700. Time/epoch: 1.5663
saving best checkpoint at epoch: 62, Acc: 97.49
EPOCH 70. Progress: 70.0%.
Train loss: 0.0001. Train Acc: 97.8925, Test loss: 0.0002. Test Acc: 97.3400. Time/epoch: 1.6849
saving best checkpoint at epoch: 72, Acc: 97.52
saving best checkpoint at epoch: 76, Acc: 97.6
EPOCH 80. Progress: 80.0%.
Train loss: 0.0001. Train Acc: 98.0125, Test loss: 0.0001. Test Acc: 97.5100. Time/epoch: 1.5435
saving best checkpoint at epoch: 85, Acc: 97.77
EPOCH 90. Progress: 90.0%.
Train loss: 0.0001. Train Acc: 98.0675, Test loss: 0.0001. Test Acc: 97.4300. Time/epoch: 1.5394
saving best checkpoint at epoch: 92, Acc: 97.79
EPOCH 100. Progress: 100.0%.
Train loss: 0.0001. Train Acc: 98.5125, Test loss: 0.0001. Test Acc: 97.8000. Time/epoch: 1.6845
saving best checkpoint at epoch: 100, Acc: 97.8
Run history:
Accuracy/train | ▁▄▄▄▄▅▆▆▆▆▆▇▇▆▇▇▇▇▇▇▇▇▇▇▇█▇▇▇███▇███████ |
Accuracy/val | ▁▄▄▄▄▆▆▆▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇█▇▇████▇███████ |
Loss/train | █▄▄▄▄▃▃▃▃▂▃▂▂▂▂▂▂▂▂▂▂▂▂▂▂▁▂▂▂▁▁▁▂▁▁▁▁▁▁▁ |
Loss/val | █▄▄▄▄▃▂▃▂▂▂▂▂▂▂▂▂▁▂▂▁▂▂▂▂▁▂▁▁▁▁▁▂▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.5125 |
Accuracy/val | 97.8 |
Loss/train | 8e-05 |
Loss/val | 0.00013 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_085212-ts1a9t68/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: 5imxc6l6 with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 0.001
wandb: optimizer: adam
wandb: weight_decay: 0.005
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_085517-5imxc6l6
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0005. Train Acc: 90.0775, Test loss: 0.0005. Test Acc: 90.2300. Time/epoch: 1.5671
saving best checkpoint at epoch: 0, Acc: 90.23
saving best checkpoint at epoch: 1, Acc: 93.06
saving best checkpoint at epoch: 3, Acc: 94.35
saving best checkpoint at epoch: 6, Acc: 94.75
saving best checkpoint at epoch: 8, Acc: 95.84
saving best checkpoint at epoch: 9, Acc: 96.75
EPOCH 10. Progress: 10.0%.
Train loss: 0.0002. Train Acc: 96.2875, Test loss: 0.0002. Test Acc: 96.2400. Time/epoch: 1.6812
saving best checkpoint at epoch: 15, Acc: 96.89
saving best checkpoint at epoch: 17, Acc: 97.11
saving best checkpoint at epoch: 18, Acc: 97.19
EPOCH 20. Progress: 20.0%.
Train loss: 0.0001. Train Acc: 97.5500, Test loss: 0.0002. Test Acc: 97.2300. Time/epoch: 1.5478
saving best checkpoint at epoch: 20, Acc: 97.23
saving best checkpoint at epoch: 26, Acc: 97.4
saving best checkpoint at epoch: 29, Acc: 97.66
EPOCH 30. Progress: 30.0%.
Train loss: 0.0001. Train Acc: 98.2575, Test loss: 0.0001. Test Acc: 97.6600. Time/epoch: 1.5383
EPOCH 40. Progress: 40.0%.
Train loss: 0.0001. Train Acc: 98.3550, Test loss: 0.0001. Test Acc: 97.3800. Time/epoch: 1.6888
saving best checkpoint at epoch: 41, Acc: 97.71
EPOCH 50. Progress: 50.0%.
Train loss: 0.0002. Train Acc: 96.8825, Test loss: 0.0002. Test Acc: 96.1500. Time/epoch: 1.5808
saving best checkpoint at epoch: 51, Acc: 98.03
EPOCH 60. Progress: 60.0%.
Train loss: 0.0001. Train Acc: 98.2350, Test loss: 0.0002. Test Acc: 97.0100. Time/epoch: 1.6859
EPOCH 70. Progress: 70.0%.
Train loss: 0.0001. Train Acc: 98.9475, Test loss: 0.0002. Test Acc: 97.5000. Time/epoch: 1.6416
EPOCH 80. Progress: 80.0%.
Train loss: 0.0001. Train Acc: 98.7400, Test loss: 0.0002. Test Acc: 97.2400. Time/epoch: 1.5532
EPOCH 90. Progress: 90.0%.
Train loss: 0.0001. Train Acc: 97.9650, Test loss: 0.0002. Test Acc: 96.6200. Time/epoch: 1.6915
EPOCH 100. Progress: 100.0%.
Train loss: 0.0001. Train Acc: 98.4825, Test loss: 0.0002. Test Acc: 96.5600. Time/epoch: 1.5437
Run history:
Accuracy/train | ▃▁▃▄▆▆▇▇▇▇▇▆▇▇▇▇▇▇▇▇█▇▇▇████▇██▇▇█▆█▇██▇ |
Accuracy/val | ▃▁▃▄▇▇▇▇▇▇▇▆█▇████▇██▇▇█████▇█▇▇▇█▆█▇██▇ |
Loss/train | ▇█▇▆▃▃▃▂▂▃▃▄▂▂▂▂▂▂▂▂▁▂▂▂▁▁▁▁▂▁▁▂▂▁▃▁▂▁▁▂ |
Loss/val | ▆█▇▅▂▂▂▁▁▂▂▃▁▂▁▁▁▁▂▁▁▂▂▁▁▁▁▁▂▁▂▂▃▂▅▂▃▂▂▃ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.4825 |
Accuracy/val | 96.56 |
Loss/train | 8e-05 |
Loss/val | 0.00025 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_085517-5imxc6l6/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: kqldb244 with config:
wandb: batch_size: 64
wandb: epochs: 10
wandb: learning_rate: 3e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_085822-kqldb244
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0038. Train Acc: 89.1650, Test loss: 0.0039. Test Acc: 89.0500. Time/epoch: 3.2586
saving best checkpoint at epoch: 0, Acc: 89.05
saving best checkpoint at epoch: 1, Acc: 92.16
saving best checkpoint at epoch: 2, Acc: 92.62
saving best checkpoint at epoch: 3, Acc: 92.98
saving best checkpoint at epoch: 4, Acc: 94.1
saving best checkpoint at epoch: 5, Acc: 94.15
saving best checkpoint at epoch: 6, Acc: 94.77
saving best checkpoint at epoch: 7, Acc: 94.8
saving best checkpoint at epoch: 9, Acc: 95.35
EPOCH 10. Progress: 100.0%.
Train loss: 0.0020. Train Acc: 95.0625, Test loss: 0.0021. Test Acc: 95.0700. Time/epoch: 3.2527
Run history:
Accuracy/train | ▁▄▅▅▇▇▇▇▆██ |
Accuracy/val | ▁▄▅▅▇▇▇▇▆██ |
Loss/train | █▅▄▃▃▂▂▁▃▁▁ |
Loss/val | █▅▄▃▃▂▂▁▃▁▁ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 95.0625 |
Accuracy/val | 95.07 |
Loss/train | 0.00197 |
Loss/val | 0.00206 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_085822-kqldb244/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: q66lh63h with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_085920-q66lh63h
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0004. Train Acc: 90.1525, Test loss: 0.0004. Test Acc: 90.4800. Time/epoch: 1.7523
saving best checkpoint at epoch: 0, Acc: 90.48
saving best checkpoint at epoch: 1, Acc: 92.32
saving best checkpoint at epoch: 3, Acc: 94.52
saving best checkpoint at epoch: 4, Acc: 95.1
saving best checkpoint at epoch: 5, Acc: 95.55
saving best checkpoint at epoch: 8, Acc: 96.04
EPOCH 10. Progress: 10.0%.
Train loss: 0.0002. Train Acc: 95.9600, Test loss: 0.0002. Test Acc: 95.8600. Time/epoch: 1.7021
saving best checkpoint at epoch: 11, Acc: 96.22
saving best checkpoint at epoch: 14, Acc: 96.61
saving best checkpoint at epoch: 17, Acc: 96.64
EPOCH 20. Progress: 20.0%.
Train loss: 0.0002. Train Acc: 96.4425, Test loss: 0.0002. Test Acc: 96.3300. Time/epoch: 1.5584
saving best checkpoint at epoch: 23, Acc: 96.86
saving best checkpoint at epoch: 27, Acc: 97.06
EPOCH 30. Progress: 30.0%.
Train loss: 0.0001. Train Acc: 97.6200, Test loss: 0.0002. Test Acc: 97.1400. Time/epoch: 1.7035
saving best checkpoint at epoch: 30, Acc: 97.14
saving best checkpoint at epoch: 35, Acc: 97.35
EPOCH 40. Progress: 40.0%.
Train loss: 0.0002. Train Acc: 96.1100, Test loss: 0.0002. Test Acc: 95.8000. Time/epoch: 1.5532
saving best checkpoint at epoch: 48, Acc: 97.39
EPOCH 50. Progress: 50.0%.
Train loss: 0.0001. Train Acc: 97.3150, Test loss: 0.0002. Test Acc: 96.7000. Time/epoch: 1.7284
saving best checkpoint at epoch: 52, Acc: 97.42
saving best checkpoint at epoch: 57, Acc: 97.52
saving best checkpoint at epoch: 58, Acc: 97.6
EPOCH 60. Progress: 60.0%.
Train loss: 0.0001. Train Acc: 97.9300, Test loss: 0.0002. Test Acc: 97.0400. Time/epoch: 1.5781
saving best checkpoint at epoch: 66, Acc: 97.66
EPOCH 70. Progress: 70.0%.
Train loss: 0.0002. Train Acc: 96.9750, Test loss: 0.0002. Test Acc: 96.4400. Time/epoch: 1.5612
saving best checkpoint at epoch: 74, Acc: 97.68
saving best checkpoint at epoch: 77, Acc: 97.69
EPOCH 80. Progress: 80.0%.
Train loss: 0.0001. Train Acc: 98.7125, Test loss: 0.0002. Test Acc: 97.4400. Time/epoch: 1.7046
saving best checkpoint at epoch: 83, Acc: 97.93
saving best checkpoint at epoch: 87, Acc: 97.96
saving best checkpoint at epoch: 89, Acc: 97.97
EPOCH 90. Progress: 90.0%.
Train loss: 0.0000. Train Acc: 99.2050, Test loss: 0.0001. Test Acc: 97.9800. Time/epoch: 1.5516
saving best checkpoint at epoch: 90, Acc: 97.98
EPOCH 100. Progress: 100.0%.
Train loss: 0.0001. Train Acc: 99.0625, Test loss: 0.0002. Test Acc: 97.6300. Time/epoch: 1.7018
Run history:
Accuracy/train | ▁▂▅▄▅▆▆▆▆▇▆▆▇▇▇▇▅▅▇▇▇▇▇▇▆▇█▇██▇▆████████ |
Accuracy/val | ▁▂▆▄▆▆▆▇▆▇▆▇▇▇▇▇▆▅▇▇▇▇▇█▇▇█▇██▇▆█████▇██ |
Loss/train | ██▄▅▄▄▃▃▃▃▃▃▂▂▂▂▄▄▂▂▂▂▂▂▃▂▂▂▁▁▂▃▁▁▁▁▁▁▁▁ |
Loss/val | ██▃▅▃▃▂▂▂▂▂▂▁▂▁▁▃▃▁▁▂▂▂▁▃▂▁▂▁▁▃▄▁▁▁▁▁▂▁▂ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 99.0625 |
Accuracy/val | 97.63 |
Loss/train | 5e-05 |
Loss/val | 0.00017 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_085920-q66lh63h/logs
wandb: Sweep Agent: Waiting for job.
500 response executing GraphQL.
{"errors":[{"message":"Post \"http://anaconda2.default.svc.cluster.local/search\": read tcp 10.52.6.4:46610-\u003e10.55.247.53:80: read: connection reset by peer","path":["agentHeartbeat"]}],"data":{"agentHeartbeat":null}}
wandb: ERROR Error while calling W&B API: Post "http://anaconda2.default.svc.cluster.local/search": read tcp 10.52.6.4:46610->10.55.247.53:80: read: connection reset by peer (<Response [500]>)
wandb: Job received.
wandb: Agent Starting Run: 459efn2e with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 3e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_090246-459efn2e
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0027. Train Acc: 61.6575, Test loss: 0.0027. Test Acc: 62.3500. Time/epoch: 1.5920
saving best checkpoint at epoch: 0, Acc: 62.35
saving best checkpoint at epoch: 1, Acc: 70.78
saving best checkpoint at epoch: 2, Acc: 76.68
saving best checkpoint at epoch: 3, Acc: 85.2
saving best checkpoint at epoch: 4, Acc: 88.49
saving best checkpoint at epoch: 5, Acc: 90.07
saving best checkpoint at epoch: 6, Acc: 90.91
saving best checkpoint at epoch: 7, Acc: 91.36
saving best checkpoint at epoch: 8, Acc: 92.11
saving best checkpoint at epoch: 9, Acc: 92.19
EPOCH 10. Progress: 10.0%.
Train loss: 0.0004. Train Acc: 92.6975, Test loss: 0.0004. Test Acc: 92.6700. Time/epoch: 1.5554
saving best checkpoint at epoch: 10, Acc: 92.67
saving best checkpoint at epoch: 11, Acc: 92.92
saving best checkpoint at epoch: 12, Acc: 93.29
saving best checkpoint at epoch: 13, Acc: 93.37
saving best checkpoint at epoch: 15, Acc: 93.63
saving best checkpoint at epoch: 16, Acc: 94.18
saving best checkpoint at epoch: 17, Acc: 94.32
saving best checkpoint at epoch: 18, Acc: 94.46
saving best checkpoint at epoch: 19, Acc: 94.54
EPOCH 20. Progress: 20.0%.
Train loss: 0.0003. Train Acc: 94.5350, Test loss: 0.0003. Test Acc: 94.4500. Time/epoch: 1.5664
saving best checkpoint at epoch: 21, Acc: 94.88
saving best checkpoint at epoch: 23, Acc: 94.98
saving best checkpoint at epoch: 25, Acc: 95.07
saving best checkpoint at epoch: 26, Acc: 95.12
saving best checkpoint at epoch: 28, Acc: 95.36
saving best checkpoint at epoch: 29, Acc: 95.49
EPOCH 30. Progress: 30.0%.
Train loss: 0.0002. Train Acc: 95.7675, Test loss: 0.0002. Test Acc: 95.5500. Time/epoch: 1.5633
saving best checkpoint at epoch: 30, Acc: 95.55
saving best checkpoint at epoch: 34, Acc: 95.78
saving best checkpoint at epoch: 37, Acc: 95.83
EPOCH 40. Progress: 40.0%.
Train loss: 0.0002. Train Acc: 96.2775, Test loss: 0.0002. Test Acc: 95.9100. Time/epoch: 1.6901
saving best checkpoint at epoch: 40, Acc: 95.91
saving best checkpoint at epoch: 44, Acc: 95.94
saving best checkpoint at epoch: 45, Acc: 95.95
saving best checkpoint at epoch: 47, Acc: 96.17
EPOCH 50. Progress: 50.0%.
Train loss: 0.0002. Train Acc: 96.4825, Test loss: 0.0002. Test Acc: 96.1100. Time/epoch: 1.5931
saving best checkpoint at epoch: 51, Acc: 96.28
saving best checkpoint at epoch: 55, Acc: 96.36
EPOCH 60. Progress: 60.0%.
Train loss: 0.0002. Train Acc: 96.6675, Test loss: 0.0002. Test Acc: 96.4200. Time/epoch: 1.5757
saving best checkpoint at epoch: 60, Acc: 96.42
saving best checkpoint at epoch: 61, Acc: 96.47
saving best checkpoint at epoch: 63, Acc: 96.49
EPOCH 70. Progress: 70.0%.
Train loss: 0.0002. Train Acc: 96.9775, Test loss: 0.0002. Test Acc: 96.4900. Time/epoch: 1.7017
saving best checkpoint at epoch: 72, Acc: 96.57
EPOCH 80. Progress: 80.0%.
Train loss: 0.0002. Train Acc: 97.0150, Test loss: 0.0002. Test Acc: 96.4700. Time/epoch: 1.5609
saving best checkpoint at epoch: 81, Acc: 96.72
saving best checkpoint at epoch: 86, Acc: 96.74
EPOCH 90. Progress: 90.0%.
Train loss: 0.0002. Train Acc: 97.1425, Test loss: 0.0002. Test Acc: 96.6200. Time/epoch: 1.7450
saving best checkpoint at epoch: 94, Acc: 96.79
saving best checkpoint at epoch: 96, Acc: 96.83
EPOCH 100. Progress: 100.0%.
Train loss: 0.0001. Train Acc: 97.1800, Test loss: 0.0002. Test Acc: 96.8100. Time/epoch: 1.6897
Run history:
Accuracy/train | ▁▄▇▇▇▇▇▇▇███████████████████████████████ |
Accuracy/val | ▁▄▇▇▇▇▇▇████████████████████████████████ |
Loss/train | █▄▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▄▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 97.18 |
Accuracy/val | 96.81 |
Loss/train | 0.00015 |
Loss/val | 0.00018 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_090246-459efn2e/logs
wandb: Agent Starting Run: krnzu5ta with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 0.0001
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_090544-krnzu5ta
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0009. Train Acc: 86.3925, Test loss: 0.0009. Test Acc: 86.5600. Time/epoch: 1.5978
saving best checkpoint at epoch: 0, Acc: 86.56
saving best checkpoint at epoch: 1, Acc: 90.27
saving best checkpoint at epoch: 2, Acc: 92.0
saving best checkpoint at epoch: 3, Acc: 92.55
saving best checkpoint at epoch: 4, Acc: 92.97
saving best checkpoint at epoch: 6, Acc: 93.28
saving best checkpoint at epoch: 8, Acc: 93.92
saving best checkpoint at epoch: 9, Acc: 94.22
EPOCH 10. Progress: 10.0%.
Train loss: 0.0003. Train Acc: 94.2675, Test loss: 0.0003. Test Acc: 94.1000. Time/epoch: 1.5429
saving best checkpoint at epoch: 11, Acc: 94.25
saving best checkpoint at epoch: 12, Acc: 94.52
saving best checkpoint at epoch: 13, Acc: 94.92
saving best checkpoint at epoch: 15, Acc: 95.2
saving best checkpoint at epoch: 16, Acc: 95.49
saving best checkpoint at epoch: 19, Acc: 95.63
EPOCH 20. Progress: 20.0%.
Train loss: 0.0002. Train Acc: 95.6400, Test loss: 0.0002. Test Acc: 95.5400. Time/epoch: 1.5730
saving best checkpoint at epoch: 22, Acc: 96.06
saving best checkpoint at epoch: 24, Acc: 96.16
saving best checkpoint at epoch: 29, Acc: 96.18
EPOCH 30. Progress: 30.0%.
Train loss: 0.0002. Train Acc: 95.9750, Test loss: 0.0002. Test Acc: 95.7100. Time/epoch: 1.5606
saving best checkpoint at epoch: 31, Acc: 96.59
saving best checkpoint at epoch: 32, Acc: 96.68
saving best checkpoint at epoch: 35, Acc: 96.75
saving best checkpoint at epoch: 38, Acc: 96.85
EPOCH 40. Progress: 40.0%.
Train loss: 0.0001. Train Acc: 97.3400, Test loss: 0.0002. Test Acc: 97.0200. Time/epoch: 1.6947
saving best checkpoint at epoch: 40, Acc: 97.02
saving best checkpoint at epoch: 47, Acc: 97.18
saving best checkpoint at epoch: 49, Acc: 97.3
EPOCH 50. Progress: 50.0%.
Train loss: 0.0002. Train Acc: 97.1250, Test loss: 0.0002. Test Acc: 96.7600. Time/epoch: 1.5569
EPOCH 60. Progress: 60.0%.
Train loss: 0.0001. Train Acc: 97.6850, Test loss: 0.0002. Test Acc: 97.3000. Time/epoch: 1.5390
saving best checkpoint at epoch: 64, Acc: 97.57
EPOCH 70. Progress: 70.0%.
Train loss: 0.0001. Train Acc: 97.8050, Test loss: 0.0001. Test Acc: 97.3200. Time/epoch: 1.6843
saving best checkpoint at epoch: 75, Acc: 97.68
EPOCH 80. Progress: 80.0%.
Train loss: 0.0001. Train Acc: 98.0475, Test loss: 0.0001. Test Acc: 97.3500. Time/epoch: 1.5452
saving best checkpoint at epoch: 88, Acc: 97.8
EPOCH 90. Progress: 90.0%.
Train loss: 0.0001. Train Acc: 97.4075, Test loss: 0.0002. Test Acc: 96.8800. Time/epoch: 1.5421
EPOCH 100. Progress: 100.0%.
Train loss: 0.0001. Train Acc: 98.4850, Test loss: 0.0001. Test Acc: 97.8100. Time/epoch: 1.6910
saving best checkpoint at epoch: 100, Acc: 97.81
Run history:
Accuracy/train | ▁▄▅▅▆▆▆▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇███▇█▇██▇██████ |
Accuracy/val | ▁▄▅▅▆▆▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇█▇▇███▇█▇██▇██████ |
Loss/train | █▄▃▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▁▁▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▄▃▃▃▂▂▂▂▂▂▂▂▂▁▁▁▁▂▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.485 |
Accuracy/val | 97.81 |
Loss/train | 8e-05 |
Loss/val | 0.00014 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_090544-krnzu5ta/logs
wandb: Agent Starting Run: ngrmf0wm with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.005
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_090843-ngrmf0wm
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0005. Train Acc: 89.7600, Test loss: 0.0005. Test Acc: 89.5100. Time/epoch: 1.5902
saving best checkpoint at epoch: 0, Acc: 89.51
saving best checkpoint at epoch: 1, Acc: 91.22
saving best checkpoint at epoch: 2, Acc: 93.15
saving best checkpoint at epoch: 4, Acc: 94.45
saving best checkpoint at epoch: 5, Acc: 94.67
saving best checkpoint at epoch: 6, Acc: 95.01
saving best checkpoint at epoch: 7, Acc: 95.14
saving best checkpoint at epoch: 9, Acc: 95.95
EPOCH 10. Progress: 10.0%.
Train loss: 0.0002. Train Acc: 96.2450, Test loss: 0.0002. Test Acc: 96.2300. Time/epoch: 1.6991
saving best checkpoint at epoch: 10, Acc: 96.23
saving best checkpoint at epoch: 12, Acc: 96.61
EPOCH 20. Progress: 20.0%.
Train loss: 0.0002. Train Acc: 96.8075, Test loss: 0.0002. Test Acc: 96.4200. Time/epoch: 1.5569
saving best checkpoint at epoch: 23, Acc: 96.74
saving best checkpoint at epoch: 28, Acc: 96.76
saving best checkpoint at epoch: 29, Acc: 96.87
EPOCH 30. Progress: 30.0%.
Train loss: 0.0003. Train Acc: 94.6725, Test loss: 0.0003. Test Acc: 94.3300. Time/epoch: 1.5484
saving best checkpoint at epoch: 36, Acc: 96.95
EPOCH 40. Progress: 40.0%.
Train loss: 0.0002. Train Acc: 96.6175, Test loss: 0.0002. Test Acc: 96.1000. Time/epoch: 1.6936
saving best checkpoint at epoch: 44, Acc: 97.14
saving best checkpoint at epoch: 48, Acc: 97.23
saving best checkpoint at epoch: 49, Acc: 97.32
EPOCH 50. Progress: 50.0%.
Train loss: 0.0001. Train Acc: 97.4550, Test loss: 0.0002. Test Acc: 96.5800. Time/epoch: 1.5732
saving best checkpoint at epoch: 55, Acc: 97.37
EPOCH 60. Progress: 60.0%.
Train loss: 0.0001. Train Acc: 97.6750, Test loss: 0.0002. Test Acc: 96.7000. Time/epoch: 1.5459
saving best checkpoint at epoch: 68, Acc: 97.45
EPOCH 70. Progress: 70.0%.
Train loss: 0.0001. Train Acc: 98.5400, Test loss: 0.0002. Test Acc: 97.2100. Time/epoch: 1.7067
saving best checkpoint at epoch: 77, Acc: 97.55
saving best checkpoint at epoch: 79, Acc: 97.56
EPOCH 80. Progress: 80.0%.
Train loss: 0.0001. Train Acc: 98.6975, Test loss: 0.0002. Test Acc: 97.2100. Time/epoch: 1.5635
saving best checkpoint at epoch: 81, Acc: 97.75
EPOCH 90. Progress: 90.0%.
Train loss: 0.0001. Train Acc: 98.4400, Test loss: 0.0002. Test Acc: 96.9900. Time/epoch: 1.5489
saving best checkpoint at epoch: 97, Acc: 97.82
EPOCH 100. Progress: 100.0%.
Train loss: 0.0001. Train Acc: 98.9525, Test loss: 0.0002. Test Acc: 97.4600. Time/epoch: 1.6900
Run history:
Accuracy/train | ▁▄▅▅▆▆▅▆▆▆▆▇▅▇▆▇▆▇▆▇▇▇▇▇▇▇▇▇█▇▇██▇▇██▇██ |
Accuracy/val | ▁▄▅▆▇▇▆▆▇▇▇▇▅▇▇▇▇▇▇██▇▇▇███▇█████▇▇██▇██ |
Loss/train | █▅▄▄▃▃▄▃▃▃▃▂▄▂▃▂▂▂▃▂▂▂▂▂▂▂▂▂▁▂▂▁▁▂▁▁▁▁▁▁ |
Loss/val | █▅▃▃▂▂▃▂▂▁▂▁▄▁▁▁▂▁▂▁▁▁▁▂▁▁▁▁▁▁▁▁▂▂▂▂▁▂▁▂ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.9525 |
Accuracy/val | 97.46 |
Loss/train | 6e-05 |
Loss/val | 0.00019 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_090843-ngrmf0wm/logs
wandb: Sweep Agent: Waiting for job.
500 response executing GraphQL.
{"errors":[{"message":"Post \"http://anaconda2.default.svc.cluster.local/search\": read tcp 10.52.40.3:37590-\u003e10.55.247.53:80: read: connection reset by peer","path":["agentHeartbeat"]}],"data":{"agentHeartbeat":null}}
wandb: ERROR Error while calling W&B API: Post "http://anaconda2.default.svc.cluster.local/search": read tcp 10.52.40.3:37590->10.55.247.53:80: read: connection reset by peer (<Response [500]>)
wandb: Job received.
wandb: Agent Starting Run: b2px33o8 with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 0.0001
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_091213-b2px33o8
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0008. Train Acc: 87.1950, Test loss: 0.0008. Test Acc: 86.6900. Time/epoch: 1.6896
saving best checkpoint at epoch: 0, Acc: 86.69
saving best checkpoint at epoch: 1, Acc: 89.34
saving best checkpoint at epoch: 2, Acc: 90.57
saving best checkpoint at epoch: 3, Acc: 91.56
saving best checkpoint at epoch: 4, Acc: 92.49
saving best checkpoint at epoch: 5, Acc: 92.64
saving best checkpoint at epoch: 6, Acc: 92.99
saving best checkpoint at epoch: 7, Acc: 93.3
EPOCH 10. Progress: 10.0%.
Train loss: 0.0003. Train Acc: 94.0175, Test loss: 0.0003. Test Acc: 93.7900. Time/epoch: 1.7866
saving best checkpoint at epoch: 10, Acc: 93.79
saving best checkpoint at epoch: 12, Acc: 93.92
saving best checkpoint at epoch: 14, Acc: 94.09
saving best checkpoint at epoch: 15, Acc: 94.36
saving best checkpoint at epoch: 17, Acc: 94.5
saving best checkpoint at epoch: 18, Acc: 94.6
saving best checkpoint at epoch: 19, Acc: 94.96
EPOCH 20. Progress: 20.0%.
Train loss: 0.0002. Train Acc: 95.5375, Test loss: 0.0002. Test Acc: 95.1900. Time/epoch: 1.6947
saving best checkpoint at epoch: 20, Acc: 95.19
saving best checkpoint at epoch: 21, Acc: 95.34
saving best checkpoint at epoch: 25, Acc: 95.45
saving best checkpoint at epoch: 26, Acc: 95.55
saving best checkpoint at epoch: 29, Acc: 95.58
EPOCH 30. Progress: 30.0%.
Train loss: 0.0002. Train Acc: 96.0200, Test loss: 0.0002. Test Acc: 95.7800. Time/epoch: 1.5499
saving best checkpoint at epoch: 30, Acc: 95.78
saving best checkpoint at epoch: 31, Acc: 95.91
saving best checkpoint at epoch: 35, Acc: 96.26
EPOCH 40. Progress: 40.0%.
Train loss: 0.0002. Train Acc: 96.3125, Test loss: 0.0002. Test Acc: 95.7600. Time/epoch: 1.5549
saving best checkpoint at epoch: 41, Acc: 96.33
EPOCH 50. Progress: 50.0%.
Train loss: 0.0002. Train Acc: 96.9525, Test loss: 0.0002. Test Acc: 96.3500. Time/epoch: 1.7089
saving best checkpoint at epoch: 50, Acc: 96.35
saving best checkpoint at epoch: 51, Acc: 96.41
saving best checkpoint at epoch: 52, Acc: 96.62
saving best checkpoint at epoch: 57, Acc: 96.67
EPOCH 60. Progress: 60.0%.
Train loss: 0.0001. Train Acc: 97.0525, Test loss: 0.0002. Test Acc: 96.5000. Time/epoch: 1.5527
saving best checkpoint at epoch: 64, Acc: 96.76
saving best checkpoint at epoch: 67, Acc: 96.79
saving best checkpoint at epoch: 68, Acc: 96.91
EPOCH 70. Progress: 70.0%.
Train loss: 0.0001. Train Acc: 97.2625, Test loss: 0.0002. Test Acc: 96.7700. Time/epoch: 1.5684
saving best checkpoint at epoch: 77, Acc: 96.98
EPOCH 80. Progress: 80.0%.
Train loss: 0.0001. Train Acc: 97.1000, Test loss: 0.0002. Test Acc: 96.6400. Time/epoch: 1.5479
saving best checkpoint at epoch: 84, Acc: 97.1
EPOCH 90. Progress: 90.0%.
Train loss: 0.0001. Train Acc: 97.7250, Test loss: 0.0002. Test Acc: 97.0200. Time/epoch: 1.5580
saving best checkpoint at epoch: 94, Acc: 97.12
saving best checkpoint at epoch: 96, Acc: 97.13
saving best checkpoint at epoch: 97, Acc: 97.19
saving best checkpoint at epoch: 99, Acc: 97.27
EPOCH 100. Progress: 100.0%.
Train loss: 0.0001. Train Acc: 97.9525, Test loss: 0.0002. Test Acc: 96.8400. Time/epoch: 1.6912
Run history:
Accuracy/train | ▁▃▅▅▅▅▆▆▆▆▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇█▇▇▇███████████ |
Accuracy/val | ▁▄▅▅▆▆▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇████▇▇███████████ |
Loss/train | █▅▃▃▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▁▁▁▁▂▂▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▄▃▃▃▂▂▂▂▂▂▂▂▂▁▂▁▁▂▂▁▁▁▁▁▁▁▂▂▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 97.9525 |
Accuracy/val | 96.84 |
Loss/train | 0.00011 |
Loss/val | 0.00017 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_091213-b2px33o8/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: 00ln6on5 with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.005
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_091518-00ln6on5
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0006. Train Acc: 87.6175, Test loss: 0.0006. Test Acc: 87.8600. Time/epoch: 1.5812
saving best checkpoint at epoch: 0, Acc: 87.86
saving best checkpoint at epoch: 1, Acc: 90.48
saving best checkpoint at epoch: 2, Acc: 93.51
saving best checkpoint at epoch: 3, Acc: 94.21
saving best checkpoint at epoch: 6, Acc: 94.82
saving best checkpoint at epoch: 7, Acc: 95.4
saving best checkpoint at epoch: 8, Acc: 95.5
saving best checkpoint at epoch: 9, Acc: 96.05
EPOCH 10. Progress: 10.0%.
Train loss: 0.0002. Train Acc: 95.4650, Test loss: 0.0002. Test Acc: 95.3600. Time/epoch: 1.5420
saving best checkpoint at epoch: 15, Acc: 96.18
saving best checkpoint at epoch: 17, Acc: 96.49
saving best checkpoint at epoch: 19, Acc: 96.67
EPOCH 20. Progress: 20.0%.
Train loss: 0.0002. Train Acc: 95.8375, Test loss: 0.0002. Test Acc: 95.7100. Time/epoch: 1.5545
saving best checkpoint at epoch: 22, Acc: 96.9
saving best checkpoint at epoch: 27, Acc: 96.99
EPOCH 30. Progress: 30.0%.
Train loss: 0.0001. Train Acc: 97.1250, Test loss: 0.0002. Test Acc: 96.9700. Time/epoch: 1.5461
saving best checkpoint at epoch: 34, Acc: 97.16
EPOCH 40. Progress: 40.0%.
Train loss: 0.0001. Train Acc: 97.8200, Test loss: 0.0002. Test Acc: 97.2800. Time/epoch: 1.6927
saving best checkpoint at epoch: 40, Acc: 97.28
saving best checkpoint at epoch: 44, Acc: 97.37
saving best checkpoint at epoch: 46, Acc: 97.47
EPOCH 50. Progress: 50.0%.
Train loss: 0.0001. Train Acc: 97.8575, Test loss: 0.0002. Test Acc: 97.1200. Time/epoch: 1.5630
EPOCH 60. Progress: 60.0%.
Train loss: 0.0001. Train Acc: 97.0925, Test loss: 0.0002. Test Acc: 96.1700. Time/epoch: 1.5466
saving best checkpoint at epoch: 63, Acc: 97.6
saving best checkpoint at epoch: 65, Acc: 97.77
EPOCH 70. Progress: 70.0%.
Train loss: 0.0001. Train Acc: 98.4900, Test loss: 0.0001. Test Acc: 97.5900. Time/epoch: 1.7045
EPOCH 80. Progress: 80.0%.
Train loss: 0.0001. Train Acc: 98.6075, Test loss: 0.0002. Test Acc: 97.6500. Time/epoch: 1.5509
saving best checkpoint at epoch: 88, Acc: 97.88
EPOCH 90. Progress: 90.0%.
Train loss: 0.0001. Train Acc: 98.7950, Test loss: 0.0002. Test Acc: 97.5600. Time/epoch: 1.5506
EPOCH 100. Progress: 100.0%.
Train loss: 0.0001. Train Acc: 98.5575, Test loss: 0.0002. Test Acc: 97.3500. Time/epoch: 1.6969
Run history:
Accuracy/train | ▁▅▅▆▆▆▇▇▆▅▇▇▇▇▇▇▇▇████▇▇███▆███▇████▇███ |
Accuracy/val | ▁▅▅▆▆▇▇▇▇▅▇▇█▇▇███████▇████▆███▇████▇███ |
Loss/train | █▅▅▃▃▃▃▂▃▄▂▂▂▂▂▂▂▂▂▁▁▁▂▂▁▂▁▃▁▁▁▂▁▁▁▁▂▁▁▁ |
Loss/val | █▄▄▃▃▂▂▂▂▄▂▂▂▂▂▁▁▂▁▁▁▁▂▁▁▁▁▃▁▁▁▂▁▂▁▂▂▂▂▂ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.5575 |
Accuracy/val | 97.35 |
Loss/train | 7e-05 |
Loss/val | 0.00019 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_091518-00ln6on5/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: 5furh1c1 with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_091823-5furh1c1
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0005. Train Acc: 89.3375, Test loss: 0.0005. Test Acc: 89.4500. Time/epoch: 1.5920
saving best checkpoint at epoch: 0, Acc: 89.45
saving best checkpoint at epoch: 1, Acc: 92.14
saving best checkpoint at epoch: 3, Acc: 93.8
saving best checkpoint at epoch: 5, Acc: 94.15
saving best checkpoint at epoch: 6, Acc: 95.47
saving best checkpoint at epoch: 7, Acc: 95.69
saving best checkpoint at epoch: 8, Acc: 95.77
saving best checkpoint at epoch: 9, Acc: 96.16
EPOCH 10. Progress: 10.0%.
Train loss: 0.0002. Train Acc: 96.0925, Test loss: 0.0002. Test Acc: 95.9100. Time/epoch: 1.7116
saving best checkpoint at epoch: 13, Acc: 96.38
saving best checkpoint at epoch: 14, Acc: 96.49
saving best checkpoint at epoch: 17, Acc: 96.56
EPOCH 20. Progress: 20.0%.
Train loss: 0.0002. Train Acc: 96.6575, Test loss: 0.0002. Test Acc: 96.2700. Time/epoch: 1.5641
saving best checkpoint at epoch: 22, Acc: 96.66
saving best checkpoint at epoch: 23, Acc: 96.75
saving best checkpoint at epoch: 24, Acc: 96.98
saving best checkpoint at epoch: 27, Acc: 97.09
EPOCH 30. Progress: 30.0%.
Train loss: 0.0001. Train Acc: 97.8000, Test loss: 0.0002. Test Acc: 97.1600. Time/epoch: 1.5668
saving best checkpoint at epoch: 30, Acc: 97.16
saving best checkpoint at epoch: 35, Acc: 97.2
EPOCH 40. Progress: 40.0%.
Train loss: 0.0001. Train Acc: 97.7275, Test loss: 0.0002. Test Acc: 96.9200. Time/epoch: 1.7048
saving best checkpoint at epoch: 41, Acc: 97.3
saving best checkpoint at epoch: 43, Acc: 97.34
saving best checkpoint at epoch: 45, Acc: 97.5
saving best checkpoint at epoch: 49, Acc: 97.51
EPOCH 50. Progress: 50.0%.
Train loss: 0.0001. Train Acc: 98.0625, Test loss: 0.0002. Test Acc: 97.2300. Time/epoch: 1.5850
saving best checkpoint at epoch: 58, Acc: 97.58
EPOCH 60. Progress: 60.0%.
Train loss: 0.0001. Train Acc: 98.4100, Test loss: 0.0002. Test Acc: 97.2400. Time/epoch: 1.5624
saving best checkpoint at epoch: 62, Acc: 97.64
saving best checkpoint at epoch: 68, Acc: 97.65
EPOCH 70. Progress: 70.0%.
Train loss: 0.0001. Train Acc: 98.5825, Test loss: 0.0002. Test Acc: 97.3700. Time/epoch: 1.7039
EPOCH 80. Progress: 80.0%.
Train loss: 0.0001. Train Acc: 98.4775, Test loss: 0.0002. Test Acc: 97.0500. Time/epoch: 1.6558
EPOCH 90. Progress: 90.0%.
Train loss: 0.0000. Train Acc: 99.1525, Test loss: 0.0002. Test Acc: 97.6800. Time/epoch: 1.5644
saving best checkpoint at epoch: 90, Acc: 97.68
EPOCH 100. Progress: 100.0%.
Train loss: 0.0001. Train Acc: 98.8000, Test loss: 0.0002. Test Acc: 97.2400. Time/epoch: 1.6939
Run history:
Accuracy/train | ▁▃▅▆▆▆▆▇▆▇▇▅▇▇▇▇▇█▇▇▇▇▇██▇█▇▇███████████ |
Accuracy/val | ▁▃▅▆▇▆▇▇▇▇▇▆█▇████▇▇█████▇██████████▇█▇█ |
Loss/train | █▆▅▄▃▄▃▃▃▂▂▄▂▂▂▂▂▂▂▂▂▂▂▁▁▂▁▁▂▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▆▄▃▃▃▂▂▂▂▂▃▁▂▁▁▁▁▂▂▁▂▁▁▁▂▂▂▂▁▂▁▂▁▂▁▃▂▂▂ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.8 |
Accuracy/val | 97.24 |
Loss/train | 6e-05 |
Loss/val | 0.0002 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_091823-5furh1c1/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: n788bo7t with config:
wandb: batch_size: 512
wandb: epochs: 50
wandb: learning_rate: 0.001
wandb: optimizer: adam
wandb: weight_decay: 0.005
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_092150-n788bo7t
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0005. Train Acc: 87.5075, Test loss: 0.0005. Test Acc: 87.7000. Time/epoch: 1.6022
saving best checkpoint at epoch: 0, Acc: 87.7
saving best checkpoint at epoch: 1, Acc: 90.88
saving best checkpoint at epoch: 2, Acc: 92.92
saving best checkpoint at epoch: 4, Acc: 94.1
saving best checkpoint at epoch: 5, Acc: 95.52
saving best checkpoint at epoch: 6, Acc: 96.17
EPOCH 10. Progress: 20.0%.
Train loss: 0.0002. Train Acc: 95.4100, Test loss: 0.0002. Test Acc: 95.2600. Time/epoch: 1.6911
saving best checkpoint at epoch: 15, Acc: 96.45
saving best checkpoint at epoch: 16, Acc: 96.54
EPOCH 20. Progress: 40.0%.
Train loss: 0.0002. Train Acc: 95.8550, Test loss: 0.0002. Test Acc: 95.6100. Time/epoch: 1.5528
saving best checkpoint at epoch: 22, Acc: 96.71
EPOCH 30. Progress: 60.0%.
Train loss: 0.0002. Train Acc: 95.4175, Test loss: 0.0003. Test Acc: 95.0800. Time/epoch: 1.5461
saving best checkpoint at epoch: 32, Acc: 97.09
EPOCH 40. Progress: 80.0%.
Train loss: 0.0001. Train Acc: 97.2700, Test loss: 0.0002. Test Acc: 96.6200. Time/epoch: 1.6937
EPOCH 50. Progress: 100.0%.
Train loss: 0.0002. Train Acc: 96.7125, Test loss: 0.0002. Test Acc: 95.8700. Time/epoch: 1.6149
Run history:
Accuracy/train | ▁▃▅▂▇▇▅▇▆▇▇▇▇▇▇▇▇▇▆▆▄▆▇▆▆█▇▆██▅▇▇█▇█▇▆▇▇ |
Accuracy/val | ▁▃▅▂▇▇▅▇▇▇▇▇██▇▇▇▇▆▆▄▆▇▆▇█▇▆██▅▇▇█▇█▇▆▇▇ |
Loss/train | █▇▅▇▃▂▄▃▃▂▃▃▂▂▃▂▃▂▃▃▆▄▂▃▃▁▂▄▁▂▄▃▂▁▂▁▂▃▂▂ |
Loss/val | █▆▄▇▂▂▄▂▃▂▂▂▂▁▂▂▂▂▃▃▇▄▂▃▃▁▂▄▁▂▄▃▂▁▂▁▂▃▂▂ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 96.7125 |
Accuracy/val | 95.87 |
Loss/train | 0.00016 |
Loss/val | 0.00023 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_092150-n788bo7t/logs
wandb: Agent Starting Run: fdsgzvl8 with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 0.0001
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_092328-fdsgzvl8
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0006. Train Acc: 86.6300, Test loss: 0.0007. Test Acc: 86.8200. Time/epoch: 1.7127
saving best checkpoint at epoch: 0, Acc: 86.82
saving best checkpoint at epoch: 1, Acc: 89.99
saving best checkpoint at epoch: 2, Acc: 90.95
saving best checkpoint at epoch: 3, Acc: 91.64
saving best checkpoint at epoch: 4, Acc: 91.7
saving best checkpoint at epoch: 5, Acc: 92.49
saving best checkpoint at epoch: 6, Acc: 93.35
saving best checkpoint at epoch: 7, Acc: 93.75
saving best checkpoint at epoch: 9, Acc: 94.04
EPOCH 10. Progress: 10.0%.
Train loss: 0.0003. Train Acc: 94.6025, Test loss: 0.0003. Test Acc: 94.3900. Time/epoch: 1.5597
saving best checkpoint at epoch: 10, Acc: 94.39
saving best checkpoint at epoch: 11, Acc: 94.58
saving best checkpoint at epoch: 12, Acc: 94.91
saving best checkpoint at epoch: 13, Acc: 95.27
saving best checkpoint at epoch: 15, Acc: 95.4
EPOCH 20. Progress: 20.0%.
Train loss: 0.0002. Train Acc: 95.4025, Test loss: 0.0002. Test Acc: 95.1000. Time/epoch: 1.5497
saving best checkpoint at epoch: 22, Acc: 95.41
saving best checkpoint at epoch: 23, Acc: 95.66
saving best checkpoint at epoch: 25, Acc: 95.89
saving best checkpoint at epoch: 26, Acc: 96.21
EPOCH 30. Progress: 30.0%.
Train loss: 0.0002. Train Acc: 96.1775, Test loss: 0.0002. Test Acc: 95.6800. Time/epoch: 1.6917
saving best checkpoint at epoch: 34, Acc: 96.43
saving best checkpoint at epoch: 39, Acc: 96.5
EPOCH 40. Progress: 40.0%.
Train loss: 0.0002. Train Acc: 95.9325, Test loss: 0.0002. Test Acc: 95.4300. Time/epoch: 1.5507
EPOCH 50. Progress: 50.0%.
Train loss: 0.0001. Train Acc: 97.3700, Test loss: 0.0002. Test Acc: 96.6800. Time/epoch: 1.7086
saving best checkpoint at epoch: 50, Acc: 96.68
saving best checkpoint at epoch: 52, Acc: 96.7
EPOCH 60. Progress: 60.0%.
Train loss: 0.0002. Train Acc: 96.6825, Test loss: 0.0002. Test Acc: 96.0100. Time/epoch: 1.5585
saving best checkpoint at epoch: 62, Acc: 96.84
saving best checkpoint at epoch: 65, Acc: 96.89
EPOCH 70. Progress: 70.0%.
Train loss: 0.0001. Train Acc: 97.5775, Test loss: 0.0002. Test Acc: 96.9800. Time/epoch: 1.5568
saving best checkpoint at epoch: 70, Acc: 96.98
saving best checkpoint at epoch: 79, Acc: 97.0
EPOCH 80. Progress: 80.0%.
Train loss: 0.0001. Train Acc: 97.9175, Test loss: 0.0002. Test Acc: 96.9300. Time/epoch: 1.6924
saving best checkpoint at epoch: 85, Acc: 97.28
EPOCH 90. Progress: 90.0%.
Train loss: 0.0001. Train Acc: 98.0975, Test loss: 0.0001. Test Acc: 97.3400. Time/epoch: 1.5694
saving best checkpoint at epoch: 90, Acc: 97.34
EPOCH 100. Progress: 100.0%.
Train loss: 0.0001. Train Acc: 97.9975, Test loss: 0.0002. Test Acc: 97.2300. Time/epoch: 1.5454
Run history:
Accuracy/train | ▁▄▅▅▆▆▆▇▆▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇█▇█████████████ |
Accuracy/val | ▁▄▅▆▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇████▇███████ |
Loss/train | █▅▄▃▃▃▃▂▂▂▂▃▂▂▂▂▂▂▂▂▂▂▂▂▂▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▅▄▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▂▁▂▂▂▂▁▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 97.9975 |
Accuracy/val | 97.23 |
Loss/train | 0.00011 |
Loss/val | 0.00016 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_092328-fdsgzvl8/logs
wandb: Agent Starting Run: ecs67yd1 with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_092624-ecs67yd1
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0005. Train Acc: 87.6525, Test loss: 0.0005. Test Acc: 88.0100. Time/epoch: 1.5929
saving best checkpoint at epoch: 0, Acc: 88.01
saving best checkpoint at epoch: 1, Acc: 92.54
saving best checkpoint at epoch: 4, Acc: 94.07
saving best checkpoint at epoch: 5, Acc: 95.03
EPOCH 10. Progress: 10.0%.
Train loss: 0.0002. Train Acc: 96.1950, Test loss: 0.0002. Test Acc: 95.8200. Time/epoch: 1.5677
saving best checkpoint at epoch: 10, Acc: 95.82
saving best checkpoint at epoch: 14, Acc: 96.33
saving best checkpoint at epoch: 15, Acc: 96.48
saving best checkpoint at epoch: 17, Acc: 96.73
saving best checkpoint at epoch: 18, Acc: 97.03
EPOCH 20. Progress: 20.0%.
Train loss: 0.0001. Train Acc: 97.1150, Test loss: 0.0002. Test Acc: 96.6800. Time/epoch: 1.5537
saving best checkpoint at epoch: 24, Acc: 97.06
saving best checkpoint at epoch: 27, Acc: 97.29
EPOCH 30. Progress: 30.0%.
Train loss: 0.0001. Train Acc: 97.8925, Test loss: 0.0002. Test Acc: 97.2900. Time/epoch: 1.5402
saving best checkpoint at epoch: 32, Acc: 97.54
EPOCH 40. Progress: 40.0%.
Train loss: 0.0001. Train Acc: 98.3425, Test loss: 0.0001. Test Acc: 97.4100. Time/epoch: 1.6852
saving best checkpoint at epoch: 45, Acc: 97.66
EPOCH 50. Progress: 50.0%.
Train loss: 0.0001. Train Acc: 97.2975, Test loss: 0.0002. Test Acc: 96.2800. Time/epoch: 1.5690
saving best checkpoint at epoch: 51, Acc: 97.78
EPOCH 60. Progress: 60.0%.
Train loss: 0.0001. Train Acc: 99.0375, Test loss: 0.0001. Test Acc: 97.7500. Time/epoch: 1.5477
saving best checkpoint at epoch: 61, Acc: 97.85
EPOCH 70. Progress: 70.0%.
Train loss: 0.0000. Train Acc: 99.2150, Test loss: 0.0002. Test Acc: 97.5700. Time/epoch: 1.6997
EPOCH 80. Progress: 80.0%.
Train loss: 0.0000. Train Acc: 99.0825, Test loss: 0.0002. Test Acc: 97.5000. Time/epoch: 1.5379
saving best checkpoint at epoch: 89, Acc: 97.88
EPOCH 90. Progress: 90.0%.
Train loss: 0.0000. Train Acc: 99.3100, Test loss: 0.0002. Test Acc: 97.5700. Time/epoch: 1.5444
saving best checkpoint at epoch: 98, Acc: 97.93
EPOCH 100. Progress: 100.0%.
Train loss: 0.0000. Train Acc: 99.4825, Test loss: 0.0002. Test Acc: 97.7900. Time/epoch: 1.6948
Run history:
Accuracy/train | ▁▄▅▅▆▅▆▇▇▇▆▇▇▇▇▇▇▇▇▇█▇█▇████▇████████▇██ |
Accuracy/val | ▁▄▆▆▇▆▇▇▇▇▆▇█▇▇▇██▇███████████▇██████▇██ |
Loss/train | █▆▄▄▃▄▃▃▃▂▃▂▂▂▂▂▂▂▂▂▂▂▁▂▁▁▁▁▂▁▂▁▁▂▁▁▁▂▁▁ |
Loss/val | █▆▃▃▂▃▂▂▂▂▃▁▁▁▁▁▁▂▂▁▁▂▁▁▁▁▁▁▂▁▂▂▂▂▁▁▂▃▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 99.4825 |
Accuracy/val | 97.79 |
Loss/train | 3e-05 |
Loss/val | 0.00016 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_092624-ecs67yd1/logs
wandb: Agent Starting Run: 4c9tchm1 with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.0005
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_092922-4c9tchm1
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0005. Train Acc: 89.6000, Test loss: 0.0005. Test Acc: 89.5500. Time/epoch: 1.5700
saving best checkpoint at epoch: 0, Acc: 89.55
saving best checkpoint at epoch: 1, Acc: 90.99
saving best checkpoint at epoch: 3, Acc: 93.52
saving best checkpoint at epoch: 4, Acc: 94.09
saving best checkpoint at epoch: 5, Acc: 94.9
EPOCH 10. Progress: 10.0%.
Train loss: 0.0002. Train Acc: 95.2525, Test loss: 0.0002. Test Acc: 95.1200. Time/epoch: 1.6870
saving best checkpoint at epoch: 10, Acc: 95.12
saving best checkpoint at epoch: 12, Acc: 95.69
saving best checkpoint at epoch: 13, Acc: 95.87
saving best checkpoint at epoch: 16, Acc: 96.02
saving best checkpoint at epoch: 17, Acc: 96.15
saving best checkpoint at epoch: 18, Acc: 96.47
saving best checkpoint at epoch: 19, Acc: 96.51
EPOCH 20. Progress: 20.0%.
Train loss: 0.0002. Train Acc: 96.8775, Test loss: 0.0002. Test Acc: 96.2600. Time/epoch: 1.5535
saving best checkpoint at epoch: 26, Acc: 96.7
EPOCH 30. Progress: 30.0%.
Train loss: 0.0001. Train Acc: 97.3550, Test loss: 0.0002. Test Acc: 96.6500. Time/epoch: 1.5500
saving best checkpoint at epoch: 33, Acc: 97.17
saving best checkpoint at epoch: 37, Acc: 97.24
EPOCH 40. Progress: 40.0%.
Train loss: 0.0001. Train Acc: 97.7200, Test loss: 0.0002. Test Acc: 96.7300. Time/epoch: 1.6755
saving best checkpoint at epoch: 44, Acc: 97.35
EPOCH 50. Progress: 50.0%.
Train loss: 0.0001. Train Acc: 98.5475, Test loss: 0.0002. Test Acc: 97.3200. Time/epoch: 1.5598
saving best checkpoint at epoch: 58, Acc: 97.38
EPOCH 60. Progress: 60.0%.
Train loss: 0.0001. Train Acc: 98.4050, Test loss: 0.0002. Test Acc: 97.1200. Time/epoch: 1.5449
saving best checkpoint at epoch: 68, Acc: 97.49
EPOCH 70. Progress: 70.0%.
Train loss: 0.0001. Train Acc: 98.8850, Test loss: 0.0002. Test Acc: 97.2900. Time/epoch: 1.6866
saving best checkpoint at epoch: 75, Acc: 97.6
EPOCH 80. Progress: 80.0%.
Train loss: 0.0001. Train Acc: 98.7425, Test loss: 0.0002. Test Acc: 97.1400. Time/epoch: 1.6972
EPOCH 90. Progress: 90.0%.
Train loss: 0.0000. Train Acc: 99.2600, Test loss: 0.0002. Test Acc: 97.5400. Time/epoch: 1.5439
saving best checkpoint at epoch: 91, Acc: 97.66
EPOCH 100. Progress: 100.0%.
Train loss: 0.0000. Train Acc: 99.3775, Test loss: 0.0002. Test Acc: 97.5500. Time/epoch: 1.5368
Run history:
Accuracy/train | ▁▂▅▅▅▆▅▆▆▆▆▇▇▇▇▇▇▇▇▇▇▇▇█▇█▇▇▇▇███▇███▇██ |
Accuracy/val | ▁▂▆▆▆▆▆▇▇▇▆▇▇█▇▇▇█▇▇██▇████▇▇▇███████▇██ |
Loss/train | ██▄▄▄▄▄▃▃▃▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▁▁▁▂▁▁▁▂▁▁ |
Loss/val | ██▃▃▃▂▃▂▂▂▂▂▁▁▁▁▁▁▁▂▁▁▁▁▁▁▂▂▂▂▁▁▂▂▂▂▂▂▂▂ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 99.3775 |
Accuracy/val | 97.55 |
Loss/train | 4e-05 |
Loss/val | 0.00019 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_092922-4c9tchm1/logs
wandb: Agent Starting Run: stp1cco3 with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 3e-05
wandb: optimizer: adam
wandb: weight_decay: 0.0005
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_093221-stp1cco3
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0015. Train Acc: 72.5425, Test loss: 0.0015. Test Acc: 72.6800. Time/epoch: 1.6197
saving best checkpoint at epoch: 0, Acc: 72.68
saving best checkpoint at epoch: 1, Acc: 81.52
saving best checkpoint at epoch: 2, Acc: 86.81
saving best checkpoint at epoch: 3, Acc: 87.67
saving best checkpoint at epoch: 4, Acc: 88.44
saving best checkpoint at epoch: 5, Acc: 89.17
saving best checkpoint at epoch: 6, Acc: 89.8
saving best checkpoint at epoch: 7, Acc: 90.31
saving best checkpoint at epoch: 8, Acc: 90.68
saving best checkpoint at epoch: 9, Acc: 91.12
EPOCH 10. Progress: 10.0%.
Train loss: 0.0004. Train Acc: 91.7925, Test loss: 0.0004. Test Acc: 91.6900. Time/epoch: 1.5534
saving best checkpoint at epoch: 10, Acc: 91.69
saving best checkpoint at epoch: 11, Acc: 92.36
saving best checkpoint at epoch: 12, Acc: 92.88
saving best checkpoint at epoch: 13, Acc: 93.31
saving best checkpoint at epoch: 14, Acc: 93.35
saving best checkpoint at epoch: 16, Acc: 94.04
saving best checkpoint at epoch: 18, Acc: 94.29
saving best checkpoint at epoch: 19, Acc: 94.71
EPOCH 20. Progress: 20.0%.
Train loss: 0.0003. Train Acc: 94.8150, Test loss: 0.0003. Test Acc: 95.0800. Time/epoch: 1.5497
saving best checkpoint at epoch: 20, Acc: 95.08
saving best checkpoint at epoch: 21, Acc: 95.19
saving best checkpoint at epoch: 26, Acc: 95.21
saving best checkpoint at epoch: 27, Acc: 95.68
EPOCH 30. Progress: 30.0%.
Train loss: 0.0002. Train Acc: 95.7725, Test loss: 0.0002. Test Acc: 95.7800. Time/epoch: 1.5550
saving best checkpoint at epoch: 30, Acc: 95.78
saving best checkpoint at epoch: 35, Acc: 96.01
saving best checkpoint at epoch: 36, Acc: 96.16
EPOCH 40. Progress: 40.0%.
Train loss: 0.0002. Train Acc: 96.1400, Test loss: 0.0002. Test Acc: 96.0000. Time/epoch: 1.7080
saving best checkpoint at epoch: 44, Acc: 96.17
saving best checkpoint at epoch: 45, Acc: 96.29
saving best checkpoint at epoch: 48, Acc: 96.4
EPOCH 50. Progress: 50.0%.
Train loss: 0.0002. Train Acc: 96.6575, Test loss: 0.0002. Test Acc: 96.4000. Time/epoch: 1.5935
saving best checkpoint at epoch: 51, Acc: 96.44
saving best checkpoint at epoch: 57, Acc: 96.59
EPOCH 60. Progress: 60.0%.
Train loss: 0.0002. Train Acc: 96.2350, Test loss: 0.0002. Test Acc: 95.9700. Time/epoch: 1.7114
saving best checkpoint at epoch: 64, Acc: 96.67
saving best checkpoint at epoch: 68, Acc: 96.75
EPOCH 70. Progress: 70.0%.
Train loss: 0.0002. Train Acc: 96.9300, Test loss: 0.0002. Test Acc: 96.7400. Time/epoch: 1.5511
saving best checkpoint at epoch: 72, Acc: 96.82
saving best checkpoint at epoch: 75, Acc: 96.84
EPOCH 80. Progress: 80.0%.
Train loss: 0.0002. Train Acc: 96.9175, Test loss: 0.0002. Test Acc: 96.6100. Time/epoch: 1.5823
saving best checkpoint at epoch: 82, Acc: 96.9
saving best checkpoint at epoch: 83, Acc: 96.93
saving best checkpoint at epoch: 85, Acc: 96.99
EPOCH 90. Progress: 90.0%.
Train loss: 0.0001. Train Acc: 97.3625, Test loss: 0.0002. Test Acc: 97.0100. Time/epoch: 1.6932
saving best checkpoint at epoch: 90, Acc: 97.01
saving best checkpoint at epoch: 96, Acc: 97.06
saving best checkpoint at epoch: 99, Acc: 97.1
EPOCH 100. Progress: 100.0%.
Train loss: 0.0002. Train Acc: 97.3125, Test loss: 0.0002. Test Acc: 96.9500. Time/epoch: 1.5486
Run history:
Accuracy/train | ▁▅▆▆▆▇▇▇▇▇▇█████████████████████████████ |
Accuracy/val | ▁▅▆▆▆▇▇▇▇▇▇█████████████████████████████ |
Loss/train | █▄▃▃▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▃▃▃▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 97.3125 |
Accuracy/val | 96.95 |
Loss/train | 0.00015 |
Loss/val | 0.00017 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_093221-stp1cco3/logs
wandb: Agent Starting Run: 8jae2l3f with config:
wandb: batch_size: 128
wandb: epochs: 100
wandb: learning_rate: 0.0001
wandb: optimizer: adam
wandb: weight_decay: 0.0005
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_093518-8jae2l3f
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0016. Train Acc: 91.7650, Test loss: 0.0017. Test Acc: 91.6300. Time/epoch: 2.1920
saving best checkpoint at epoch: 0, Acc: 91.63
saving best checkpoint at epoch: 1, Acc: 92.05
saving best checkpoint at epoch: 2, Acc: 93.15
saving best checkpoint at epoch: 3, Acc: 94.19
saving best checkpoint at epoch: 6, Acc: 94.37
saving best checkpoint at epoch: 7, Acc: 95.34
EPOCH 10. Progress: 10.0%.
Train loss: 0.0008. Train Acc: 96.1525, Test loss: 0.0009. Test Acc: 95.9300. Time/epoch: 2.1749
saving best checkpoint at epoch: 10, Acc: 95.93
saving best checkpoint at epoch: 11, Acc: 96.28
saving best checkpoint at epoch: 15, Acc: 96.49
saving best checkpoint at epoch: 18, Acc: 96.77
EPOCH 20. Progress: 20.0%.
Train loss: 0.0007. Train Acc: 96.1000, Test loss: 0.0009. Test Acc: 95.4600. Time/epoch: 2.1818
saving best checkpoint at epoch: 21, Acc: 96.82
saving best checkpoint at epoch: 22, Acc: 96.92
saving best checkpoint at epoch: 25, Acc: 97.11
saving best checkpoint at epoch: 26, Acc: 97.21
saving best checkpoint at epoch: 27, Acc: 97.3
EPOCH 30. Progress: 30.0%.
Train loss: 0.0005. Train Acc: 97.8350, Test loss: 0.0006. Test Acc: 97.3300. Time/epoch: 2.1733
saving best checkpoint at epoch: 30, Acc: 97.33
saving best checkpoint at epoch: 34, Acc: 97.48
saving best checkpoint at epoch: 36, Acc: 97.56
saving best checkpoint at epoch: 39, Acc: 97.64
EPOCH 40. Progress: 40.0%.
Train loss: 0.0005. Train Acc: 97.6200, Test loss: 0.0007. Test Acc: 96.9800. Time/epoch: 2.1892
saving best checkpoint at epoch: 42, Acc: 97.77
EPOCH 50. Progress: 50.0%.
Train loss: 0.0004. Train Acc: 98.2975, Test loss: 0.0005. Test Acc: 97.5900. Time/epoch: 2.1758
saving best checkpoint at epoch: 51, Acc: 97.81
saving best checkpoint at epoch: 52, Acc: 97.85
EPOCH 60. Progress: 60.0%.
Train loss: 0.0003. Train Acc: 98.7050, Test loss: 0.0005. Test Acc: 97.7200. Time/epoch: 2.0515
EPOCH 70. Progress: 70.0%.
Train loss: 0.0003. Train Acc: 98.6150, Test loss: 0.0006. Test Acc: 97.5200. Time/epoch: 2.1924
saving best checkpoint at epoch: 76, Acc: 97.94
EPOCH 80. Progress: 80.0%.
Train loss: 0.0002. Train Acc: 99.1000, Test loss: 0.0005. Test Acc: 98.0300. Time/epoch: 2.1864
saving best checkpoint at epoch: 80, Acc: 98.03
EPOCH 90. Progress: 90.0%.
Train loss: 0.0002. Train Acc: 99.1375, Test loss: 0.0006. Test Acc: 97.8000. Time/epoch: 2.1853
saving best checkpoint at epoch: 92, Acc: 98.09
EPOCH 100. Progress: 100.0%.
Train loss: 0.0002. Train Acc: 99.1850, Test loss: 0.0006. Test Acc: 97.7100. Time/epoch: 2.1890
Run history:
Accuracy/train | ▁▂▂▄▅▅▆▆▅▆▆▆▇▇▆▆▆▇▇▇▇▇▇▇▇▇▇▇▇███████████ |
Accuracy/val | ▁▃▃▅▆▆▆▆▅▆▇▆▇▇▇▇▇▇▇▇█▇█▇▇█▇█▇██████▇██▇█ |
Loss/train | █▆▆▅▄▄▃▃▄▃▃▃▂▂▃▃▃▂▂▂▂▂▂▂▂▂▂▁▂▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▆▆▄▃▃▃▃▃▂▂▃▂▂▂▂▂▁▁▁▁▁▁▁▂▁▂▁▂▁▁▁▁▁▁▂▁▁▂▂ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 99.185 |
Accuracy/val | 97.71 |
Loss/train | 0.00018 |
Loss/val | 0.00056 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_093518-8jae2l3f/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: 7nbzn3kw with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 0.0001
wandb: optimizer: adam
wandb: weight_decay: 0.0005
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_093922-7nbzn3kw
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0008. Train Acc: 86.8475, Test loss: 0.0008. Test Acc: 86.3900. Time/epoch: 1.5903
saving best checkpoint at epoch: 0, Acc: 86.39
saving best checkpoint at epoch: 1, Acc: 90.06
saving best checkpoint at epoch: 2, Acc: 90.88
saving best checkpoint at epoch: 3, Acc: 92.86
saving best checkpoint at epoch: 4, Acc: 93.79
saving best checkpoint at epoch: 5, Acc: 94.21
saving best checkpoint at epoch: 6, Acc: 94.34
saving best checkpoint at epoch: 7, Acc: 94.74
EPOCH 10. Progress: 10.0%.
Train loss: 0.0003. Train Acc: 94.6750, Test loss: 0.0003. Test Acc: 94.6500. Time/epoch: 1.5472
saving best checkpoint at epoch: 11, Acc: 94.89
saving best checkpoint at epoch: 12, Acc: 95.34
saving best checkpoint at epoch: 13, Acc: 95.39
saving best checkpoint at epoch: 14, Acc: 95.63
saving best checkpoint at epoch: 16, Acc: 95.7
saving best checkpoint at epoch: 19, Acc: 95.84
EPOCH 20. Progress: 20.0%.
Train loss: 0.0002. Train Acc: 96.1825, Test loss: 0.0002. Test Acc: 96.0300. Time/epoch: 1.5501
saving best checkpoint at epoch: 20, Acc: 96.03
saving best checkpoint at epoch: 21, Acc: 96.06
saving best checkpoint at epoch: 22, Acc: 96.16
saving best checkpoint at epoch: 24, Acc: 96.28
saving best checkpoint at epoch: 28, Acc: 96.32
EPOCH 30. Progress: 30.0%.
Train loss: 0.0002. Train Acc: 96.6325, Test loss: 0.0002. Test Acc: 96.5300. Time/epoch: 1.6944
saving best checkpoint at epoch: 30, Acc: 96.53
saving best checkpoint at epoch: 31, Acc: 96.63
saving best checkpoint at epoch: 39, Acc: 96.88
EPOCH 40. Progress: 40.0%.
Train loss: 0.0001. Train Acc: 97.1775, Test loss: 0.0002. Test Acc: 96.8200. Time/epoch: 1.5563
saving best checkpoint at epoch: 41, Acc: 97.03
saving best checkpoint at epoch: 48, Acc: 97.1
EPOCH 50. Progress: 50.0%.
Train loss: 0.0001. Train Acc: 97.4100, Test loss: 0.0002. Test Acc: 97.1300. Time/epoch: 1.7222
saving best checkpoint at epoch: 50, Acc: 97.13
saving best checkpoint at epoch: 55, Acc: 97.26
saving best checkpoint at epoch: 58, Acc: 97.32
EPOCH 60. Progress: 60.0%.
Train loss: 0.0001. Train Acc: 97.9200, Test loss: 0.0001. Test Acc: 97.4200. Time/epoch: 1.5638
saving best checkpoint at epoch: 60, Acc: 97.42
EPOCH 70. Progress: 70.0%.
Train loss: 0.0001. Train Acc: 97.4600, Test loss: 0.0002. Test Acc: 97.1200. Time/epoch: 1.5538
saving best checkpoint at epoch: 72, Acc: 97.51
saving best checkpoint at epoch: 75, Acc: 97.55
saving best checkpoint at epoch: 77, Acc: 97.57
saving best checkpoint at epoch: 79, Acc: 97.64
EPOCH 80. Progress: 80.0%.
Train loss: 0.0001. Train Acc: 98.1125, Test loss: 0.0001. Test Acc: 97.6400. Time/epoch: 1.6922
saving best checkpoint at epoch: 85, Acc: 97.71
saving best checkpoint at epoch: 89, Acc: 97.78
EPOCH 90. Progress: 90.0%.
Train loss: 0.0001. Train Acc: 98.3100, Test loss: 0.0001. Test Acc: 97.7100. Time/epoch: 1.5447
saving best checkpoint at epoch: 97, Acc: 97.86
EPOCH 100. Progress: 100.0%.
Train loss: 0.0001. Train Acc: 98.2875, Test loss: 0.0001. Test Acc: 97.7900. Time/epoch: 1.5493
Run history:
Accuracy/train | ▁▃▅▆▆▆▆▅▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇██▇██████████████ |
Accuracy/val | ▁▄▆▆▆▆▆▅▇▇▇▇▇▇▇▇▇▇▇█▇▇▇██▇███▇██████████ |
Loss/train | █▄▃▃▃▂▂▃▂▂▂▂▂▂▂▂▂▂▂▁▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▄▃▂▂▂▂▃▂▂▂▂▂▂▂▂▁▁▂▁▁▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.2875 |
Accuracy/val | 97.79 |
Loss/train | 9e-05 |
Loss/val | 0.00013 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_093922-7nbzn3kw/logs
wandb: Agent Starting Run: czeyk9sq with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.005
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_094221-czeyk9sq
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0004. Train Acc: 90.8875, Test loss: 0.0005. Test Acc: 90.9600. Time/epoch: 1.5749
saving best checkpoint at epoch: 0, Acc: 90.96
saving best checkpoint at epoch: 1, Acc: 92.38
saving best checkpoint at epoch: 2, Acc: 93.02
saving best checkpoint at epoch: 4, Acc: 94.22
saving best checkpoint at epoch: 5, Acc: 95.0
saving best checkpoint at epoch: 7, Acc: 95.41
saving best checkpoint at epoch: 8, Acc: 95.49
saving best checkpoint at epoch: 9, Acc: 95.51
EPOCH 10. Progress: 10.0%.
Train loss: 0.0003. Train Acc: 93.8775, Test loss: 0.0003. Test Acc: 93.8300. Time/epoch: 1.7190
saving best checkpoint at epoch: 11, Acc: 95.54
saving best checkpoint at epoch: 13, Acc: 95.73
saving best checkpoint at epoch: 15, Acc: 96.43
saving best checkpoint at epoch: 16, Acc: 96.52
saving best checkpoint at epoch: 17, Acc: 96.55
saving best checkpoint at epoch: 18, Acc: 96.84
EPOCH 20. Progress: 20.0%.
Train loss: 0.0002. Train Acc: 95.3950, Test loss: 0.0002. Test Acc: 95.0200. Time/epoch: 1.5531
saving best checkpoint at epoch: 23, Acc: 97.06
saving best checkpoint at epoch: 25, Acc: 97.07
saving best checkpoint at epoch: 26, Acc: 97.14
EPOCH 30. Progress: 30.0%.
Train loss: 0.0001. Train Acc: 97.4650, Test loss: 0.0002. Test Acc: 96.9200. Time/epoch: 1.5515
saving best checkpoint at epoch: 37, Acc: 97.41
EPOCH 40. Progress: 40.0%.
Train loss: 0.0002. Train Acc: 96.5525, Test loss: 0.0002. Test Acc: 95.8400. Time/epoch: 1.6876
saving best checkpoint at epoch: 41, Acc: 97.43
saving best checkpoint at epoch: 44, Acc: 97.7
EPOCH 50. Progress: 50.0%.
Train loss: 0.0001. Train Acc: 98.1425, Test loss: 0.0002. Test Acc: 97.1300. Time/epoch: 1.5799
saving best checkpoint at epoch: 51, Acc: 97.76
EPOCH 60. Progress: 60.0%.
Train loss: 0.0001. Train Acc: 98.3025, Test loss: 0.0002. Test Acc: 97.4900. Time/epoch: 1.6913
EPOCH 70. Progress: 70.0%.
Train loss: 0.0001. Train Acc: 98.1900, Test loss: 0.0002. Test Acc: 97.2200. Time/epoch: 1.5658
EPOCH 80. Progress: 80.0%.
Train loss: 0.0001. Train Acc: 99.0850, Test loss: 0.0001. Test Acc: 97.7700. Time/epoch: 1.5505
saving best checkpoint at epoch: 80, Acc: 97.77
saving best checkpoint at epoch: 84, Acc: 97.88
EPOCH 90. Progress: 90.0%.
Train loss: 0.0001. Train Acc: 98.5800, Test loss: 0.0002. Test Acc: 97.3400. Time/epoch: 1.7098
saving best checkpoint at epoch: 96, Acc: 97.9
EPOCH 100. Progress: 100.0%.
Train loss: 0.0001. Train Acc: 98.7425, Test loss: 0.0002. Test Acc: 97.2700. Time/epoch: 1.5533
Run history:
Accuracy/train | ▁▃▅▅▃▅▆▆▅▇▇▇▆▆▇▇▇▇▆▇▇▇▇▇▇▇█▇▇▇██▇██▇█▇██ |
Accuracy/val | ▁▃▅▆▄▆▇▇▅▇▇▇▇▆▇▇█▇▇▇█▇▇████▇████▇██▇█▇█▇ |
Loss/train | █▆▅▄▅▄▃▃▄▃▃▂▃▃▂▂▂▂▃▂▂▂▂▂▂▂▁▂▂▂▂▁▂▁▁▂▁▂▁▁ |
Loss/val | █▅▄▃▅▃▂▂▃▂▁▂▂▂▂▂▁▂▂▂▁▂▁▁▁▁▁▂▁▂▁▁▂▁▁▃▁▂▁▂ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.7425 |
Accuracy/val | 97.27 |
Loss/train | 6e-05 |
Loss/val | 0.0002 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_094221-czeyk9sq/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: jh03s4xr with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 0.0001
wandb: optimizer: adam
wandb: weight_decay: 0.0005
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_094527-jh03s4xr
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0005. Train Acc: 90.6175, Test loss: 0.0005. Test Acc: 90.3600. Time/epoch: 1.7241
saving best checkpoint at epoch: 0, Acc: 90.36
saving best checkpoint at epoch: 1, Acc: 92.2
saving best checkpoint at epoch: 2, Acc: 92.47
saving best checkpoint at epoch: 5, Acc: 93.47
saving best checkpoint at epoch: 6, Acc: 93.51
saving best checkpoint at epoch: 7, Acc: 93.61
saving best checkpoint at epoch: 8, Acc: 94.38
EPOCH 10. Progress: 10.0%.
Train loss: 0.0002. Train Acc: 94.8975, Test loss: 0.0003. Test Acc: 94.7300. Time/epoch: 1.6912
saving best checkpoint at epoch: 10, Acc: 94.73
saving best checkpoint at epoch: 13, Acc: 94.91
saving best checkpoint at epoch: 14, Acc: 95.02
saving best checkpoint at epoch: 17, Acc: 95.15
saving best checkpoint at epoch: 19, Acc: 95.49
EPOCH 20. Progress: 20.0%.
Train loss: 0.0002. Train Acc: 95.3975, Test loss: 0.0002. Test Acc: 95.1700. Time/epoch: 1.5470
saving best checkpoint at epoch: 23, Acc: 95.6
saving best checkpoint at epoch: 25, Acc: 95.98
saving best checkpoint at epoch: 28, Acc: 96.2
EPOCH 30. Progress: 30.0%.
Train loss: 0.0002. Train Acc: 96.1625, Test loss: 0.0002. Test Acc: 95.8200. Time/epoch: 1.6889
saving best checkpoint at epoch: 31, Acc: 96.26
saving best checkpoint at epoch: 33, Acc: 96.29
saving best checkpoint at epoch: 39, Acc: 96.35
EPOCH 40. Progress: 40.0%.
Train loss: 0.0002. Train Acc: 96.8825, Test loss: 0.0002. Test Acc: 96.4100. Time/epoch: 1.5443
saving best checkpoint at epoch: 40, Acc: 96.41
saving best checkpoint at epoch: 43, Acc: 96.49
saving best checkpoint at epoch: 45, Acc: 96.54
saving best checkpoint at epoch: 46, Acc: 96.7
EPOCH 50. Progress: 50.0%.
Train loss: 0.0002. Train Acc: 96.6900, Test loss: 0.0002. Test Acc: 96.2900. Time/epoch: 1.5578
saving best checkpoint at epoch: 52, Acc: 96.79
saving best checkpoint at epoch: 59, Acc: 96.89
EPOCH 60. Progress: 60.0%.
Train loss: 0.0001. Train Acc: 97.4500, Test loss: 0.0002. Test Acc: 96.9500. Time/epoch: 1.6851
saving best checkpoint at epoch: 60, Acc: 96.95
saving best checkpoint at epoch: 64, Acc: 97.07
EPOCH 70. Progress: 70.0%.
Train loss: 0.0001. Train Acc: 97.0975, Test loss: 0.0002. Test Acc: 96.6600. Time/epoch: 1.5679
saving best checkpoint at epoch: 73, Acc: 97.08
EPOCH 80. Progress: 80.0%.
Train loss: 0.0001. Train Acc: 97.6800, Test loss: 0.0002. Test Acc: 96.8100. Time/epoch: 1.5486
saving best checkpoint at epoch: 81, Acc: 97.26
saving best checkpoint at epoch: 87, Acc: 97.35
EPOCH 90. Progress: 90.0%.
Train loss: 0.0001. Train Acc: 97.7450, Test loss: 0.0002. Test Acc: 96.9500. Time/epoch: 1.6946
saving best checkpoint at epoch: 93, Acc: 97.37
EPOCH 100. Progress: 100.0%.
Train loss: 0.0001. Train Acc: 98.1450, Test loss: 0.0001. Test Acc: 97.3500. Time/epoch: 1.5474
Run history:
Accuracy/train | ▁▃▄▄▅▅▅▅▅▆▆▆▆▇▇▆▇▇▇▇▇▇▇▇▆▇▇▇▇▇██████████ |
Accuracy/val | ▁▃▄▄▅▅▆▆▆▆▇▇▆▇▇▆▇▇▇▇▇▇▇▇▇█▇██▇██████████ |
Loss/train | █▆▅▅▄▄▄▄▃▃▃▃▃▂▂▃▂▂▂▂▂▂▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▅▅▄▃▄▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▁▁▂▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.145 |
Accuracy/val | 97.35 |
Loss/train | 0.0001 |
Loss/val | 0.00015 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_094527-jh03s4xr/logs
wandb: Agent Starting Run: fkj7tlse with config:
wandb: batch_size: 128
wandb: epochs: 100
wandb: learning_rate: 0.0001
wandb: optimizer: adam
wandb: weight_decay: 0.0005
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_094825-fkj7tlse
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0015. Train Acc: 91.4650, Test loss: 0.0016. Test Acc: 91.4700. Time/epoch: 2.2127
saving best checkpoint at epoch: 0, Acc: 91.47
saving best checkpoint at epoch: 1, Acc: 94.1
saving best checkpoint at epoch: 2, Acc: 94.58
saving best checkpoint at epoch: 4, Acc: 94.71
saving best checkpoint at epoch: 5, Acc: 95.56
saving best checkpoint at epoch: 7, Acc: 95.95
saving best checkpoint at epoch: 9, Acc: 95.97
EPOCH 10. Progress: 10.0%.
Train loss: 0.0007. Train Acc: 96.1750, Test loss: 0.0008. Test Acc: 95.9400. Time/epoch: 2.1781
saving best checkpoint at epoch: 11, Acc: 96.45
saving best checkpoint at epoch: 18, Acc: 96.7
EPOCH 20. Progress: 20.0%.
Train loss: 0.0006. Train Acc: 97.3800, Test loss: 0.0007. Test Acc: 96.8600. Time/epoch: 2.1722
saving best checkpoint at epoch: 20, Acc: 96.86
saving best checkpoint at epoch: 21, Acc: 96.97
saving best checkpoint at epoch: 25, Acc: 97.05
saving best checkpoint at epoch: 27, Acc: 97.18
EPOCH 30. Progress: 30.0%.
Train loss: 0.0005. Train Acc: 97.8575, Test loss: 0.0006. Test Acc: 97.0800. Time/epoch: 2.1942
saving best checkpoint at epoch: 34, Acc: 97.45
EPOCH 40. Progress: 40.0%.
Train loss: 0.0004. Train Acc: 98.1200, Test loss: 0.0006. Test Acc: 97.1000. Time/epoch: 2.1784
saving best checkpoint at epoch: 43, Acc: 97.48
saving best checkpoint at epoch: 47, Acc: 97.49
EPOCH 50. Progress: 50.0%.
Train loss: 0.0004. Train Acc: 97.8975, Test loss: 0.0007. Test Acc: 96.9700. Time/epoch: 2.0271
saving best checkpoint at epoch: 51, Acc: 97.7
EPOCH 60. Progress: 60.0%.
Train loss: 0.0002. Train Acc: 98.9300, Test loss: 0.0006. Test Acc: 97.5600. Time/epoch: 2.0455
saving best checkpoint at epoch: 61, Acc: 97.77
saving best checkpoint at epoch: 63, Acc: 97.81
saving best checkpoint at epoch: 69, Acc: 97.89
EPOCH 70. Progress: 70.0%.
Train loss: 0.0002. Train Acc: 99.0025, Test loss: 0.0006. Test Acc: 97.5900. Time/epoch: 2.0671
EPOCH 80. Progress: 80.0%.
Train loss: 0.0002. Train Acc: 99.2900, Test loss: 0.0006. Test Acc: 97.8000. Time/epoch: 2.0382
EPOCH 90. Progress: 90.0%.
Train loss: 0.0002. Train Acc: 99.1775, Test loss: 0.0006. Test Acc: 97.5900. Time/epoch: 2.2121
EPOCH 100. Progress: 100.0%.
Train loss: 0.0002. Train Acc: 99.0750, Test loss: 0.0008. Test Acc: 97.3000. Time/epoch: 2.1745
Run history:
Accuracy/train | ▁▄▅▅▅▅▆▅▆▆▆▆▇▆▇▇▇▇▇▇▇▇▇▇█▇▇█████████████ |
Accuracy/val | ▁▄▅▆▆▆▆▆▇▇▇▇▇▇▇▇▇█▇▇█▇███▇█████████████▇ |
Loss/train | █▆▅▄▄▄▄▄▃▃▃▃▃▃▃▂▂▂▂▂▂▂▂▂▁▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▅▄▃▃▃▂▃▂▂▂▂▂▂▂▁▂▁▁▁▁▂▁▂▁▂▂▁▁▁▂▁▁▁▂▂▂▂▂▃ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 99.075 |
Accuracy/val | 97.3 |
Loss/train | 0.00021 |
Loss/val | 0.0008 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_094825-fkj7tlse/logs
wandb: Agent Starting Run: j4buw0pg with config:
wandb: batch_size: 128
wandb: epochs: 100
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.0005
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_095222-j4buw0pg
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0014. Train Acc: 92.4650, Test loss: 0.0015. Test Acc: 92.5800. Time/epoch: 2.2078
saving best checkpoint at epoch: 0, Acc: 92.58
saving best checkpoint at epoch: 1, Acc: 93.21
saving best checkpoint at epoch: 2, Acc: 94.23
saving best checkpoint at epoch: 3, Acc: 94.3
saving best checkpoint at epoch: 5, Acc: 94.87
saving best checkpoint at epoch: 6, Acc: 96.1
saving best checkpoint at epoch: 9, Acc: 96.51
EPOCH 10. Progress: 10.0%.
Train loss: 0.0007. Train Acc: 96.4875, Test loss: 0.0008. Test Acc: 96.3200. Time/epoch: 2.1820
saving best checkpoint at epoch: 12, Acc: 96.73
saving best checkpoint at epoch: 13, Acc: 96.95
saving best checkpoint at epoch: 19, Acc: 97.05
EPOCH 20. Progress: 20.0%.
Train loss: 0.0007. Train Acc: 96.2875, Test loss: 0.0009. Test Acc: 95.7000. Time/epoch: 2.1878
saving best checkpoint at epoch: 21, Acc: 97.54
saving best checkpoint at epoch: 28, Acc: 97.73
EPOCH 30. Progress: 30.0%.
Train loss: 0.0004. Train Acc: 98.0800, Test loss: 0.0006. Test Acc: 97.2800. Time/epoch: 2.1992
EPOCH 40. Progress: 40.0%.
Train loss: 0.0003. Train Acc: 98.7725, Test loss: 0.0006. Test Acc: 97.6800. Time/epoch: 2.0404
saving best checkpoint at epoch: 42, Acc: 97.82
EPOCH 50. Progress: 50.0%.
Train loss: 0.0002. Train Acc: 99.1175, Test loss: 0.0007. Test Acc: 97.6000. Time/epoch: 2.1692
EPOCH 60. Progress: 60.0%.
Train loss: 0.0003. Train Acc: 98.6675, Test loss: 0.0009. Test Acc: 96.9700. Time/epoch: 2.1849
EPOCH 70. Progress: 70.0%.
Train loss: 0.0001. Train Acc: 99.3575, Test loss: 0.0007. Test Acc: 97.5300. Time/epoch: 2.1914
EPOCH 80. Progress: 80.0%.
Train loss: 0.0001. Train Acc: 99.5250, Test loss: 0.0007. Test Acc: 97.6600. Time/epoch: 2.1845
EPOCH 90. Progress: 90.0%.
Train loss: 0.0002. Train Acc: 99.0950, Test loss: 0.0009. Test Acc: 96.9500. Time/epoch: 2.1932
EPOCH 100. Progress: 100.0%.
Train loss: 0.0001. Train Acc: 99.5175, Test loss: 0.0010. Test Acc: 97.2000. Time/epoch: 2.1853
Run history:
Accuracy/train | ▁▃▃▄▅▆▅▆▅▅▆▇▆▇▇▆▇▆▇▆▇▇▇▇▇▆▅██▅█▇▇█████▇█ |
Accuracy/val | ▁▃▄▆▆▇▆▆▅▅██▇█▇▇█▆▇▇▇██▇▇▆▄██▄▇▇▆█▇███▇▇ |
Loss/train | █▆▅▅▄▄▄▄▄▄▃▂▃▂▂▃▂▃▂▃▂▂▂▂▂▄▅▁▁▅▁▂▂▁▁▁▁▁▂▁ |
Loss/val | █▅▄▃▃▂▃▂▄▃▁▁▂▁▂▃▃▃▂▃▂▂▂▂▃▆▇▃▂▇▄▄▄▃▄▃▃▃▆▄ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 99.5175 |
Accuracy/val | 97.2 |
Loss/train | 0.0001 |
Loss/val | 0.001 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_095222-j4buw0pg/logs
wandb: Agent Starting Run: 9gmhu4iw with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 0.0001
wandb: optimizer: adam
wandb: weight_decay: 0.0005
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_095617-9gmhu4iw
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0006. Train Acc: 89.4825, Test loss: 0.0006. Test Acc: 89.4900. Time/epoch: 1.5772
saving best checkpoint at epoch: 0, Acc: 89.49
saving best checkpoint at epoch: 1, Acc: 92.46
saving best checkpoint at epoch: 2, Acc: 93.29
saving best checkpoint at epoch: 4, Acc: 94.32
saving best checkpoint at epoch: 5, Acc: 94.65
saving best checkpoint at epoch: 9, Acc: 94.87
EPOCH 10. Progress: 10.0%.
Train loss: 0.0002. Train Acc: 95.3025, Test loss: 0.0003. Test Acc: 95.2600. Time/epoch: 1.5569
saving best checkpoint at epoch: 10, Acc: 95.26
saving best checkpoint at epoch: 12, Acc: 95.29
saving best checkpoint at epoch: 13, Acc: 95.33
saving best checkpoint at epoch: 14, Acc: 95.85
saving best checkpoint at epoch: 17, Acc: 95.95
EPOCH 20. Progress: 20.0%.
Train loss: 0.0002. Train Acc: 95.9000, Test loss: 0.0002. Test Acc: 95.9200. Time/epoch: 1.6925
saving best checkpoint at epoch: 22, Acc: 96.3
saving best checkpoint at epoch: 25, Acc: 96.31
EPOCH 30. Progress: 30.0%.
Train loss: 0.0002. Train Acc: 96.6225, Test loss: 0.0002. Test Acc: 96.3100. Time/epoch: 1.5483
saving best checkpoint at epoch: 31, Acc: 96.47
saving best checkpoint at epoch: 32, Acc: 96.64
saving best checkpoint at epoch: 37, Acc: 96.74
EPOCH 40. Progress: 40.0%.
Train loss: 0.0001. Train Acc: 97.1375, Test loss: 0.0002. Test Acc: 96.7300. Time/epoch: 1.6898
saving best checkpoint at epoch: 45, Acc: 96.8
saving best checkpoint at epoch: 47, Acc: 96.87
EPOCH 50. Progress: 50.0%.
Train loss: 0.0002. Train Acc: 97.1150, Test loss: 0.0002. Test Acc: 96.7400. Time/epoch: 1.5509
saving best checkpoint at epoch: 56, Acc: 97.14
EPOCH 60. Progress: 60.0%.
Train loss: 0.0001. Train Acc: 97.3250, Test loss: 0.0002. Test Acc: 96.7100. Time/epoch: 1.6891
saving best checkpoint at epoch: 65, Acc: 97.28
saving best checkpoint at epoch: 66, Acc: 97.32
saving best checkpoint at epoch: 69, Acc: 97.38
EPOCH 70. Progress: 70.0%.
Train loss: 0.0001. Train Acc: 97.7275, Test loss: 0.0002. Test Acc: 97.1200. Time/epoch: 1.5383
saving best checkpoint at epoch: 74, Acc: 97.39
EPOCH 80. Progress: 80.0%.
Train loss: 0.0001. Train Acc: 97.5500, Test loss: 0.0002. Test Acc: 96.7900. Time/epoch: 1.5497
saving best checkpoint at epoch: 84, Acc: 97.49
saving best checkpoint at epoch: 86, Acc: 97.57
saving best checkpoint at epoch: 89, Acc: 97.59
EPOCH 90. Progress: 90.0%.
Train loss: 0.0001. Train Acc: 98.2500, Test loss: 0.0001. Test Acc: 97.5300. Time/epoch: 1.5452
EPOCH 100. Progress: 100.0%.
Train loss: 0.0001. Train Acc: 98.4100, Test loss: 0.0001. Test Acc: 97.6500. Time/epoch: 1.6866
saving best checkpoint at epoch: 100, Acc: 97.65
Run history:
Accuracy/train | ▁▄▅▅▆▆▆▆▆▆▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇███▇███████████ |
Accuracy/val | ▁▄▅▅▆▆▆▇▇▇▇▆▇▇▇▇▇▇▇▇▇▇█▇▇███████████████ |
Loss/train | █▄▃▃▃▃▃▃▃▂▂▃▂▂▂▂▂▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▄▃▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▁▁▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.41 |
Accuracy/val | 97.65 |
Loss/train | 9e-05 |
Loss/val | 0.00014 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_095617-9gmhu4iw/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: 6urholcs with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.005
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_095933-6urholcs
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0012. Train Acc: 69.6500, Test loss: 0.0012. Test Acc: 69.6100. Time/epoch: 1.5563
saving best checkpoint at epoch: 0, Acc: 69.61
saving best checkpoint at epoch: 1, Acc: 89.65
saving best checkpoint at epoch: 2, Acc: 90.12
saving best checkpoint at epoch: 3, Acc: 91.67
saving best checkpoint at epoch: 5, Acc: 91.8
saving best checkpoint at epoch: 6, Acc: 92.31
saving best checkpoint at epoch: 7, Acc: 92.79
saving best checkpoint at epoch: 8, Acc: 94.14
saving best checkpoint at epoch: 9, Acc: 94.66
EPOCH 10. Progress: 10.0%.
Train loss: 0.0003. Train Acc: 94.6175, Test loss: 0.0003. Test Acc: 94.4100. Time/epoch: 1.6953
saving best checkpoint at epoch: 11, Acc: 95.09
saving best checkpoint at epoch: 15, Acc: 95.78
saving best checkpoint at epoch: 17, Acc: 96.03
saving best checkpoint at epoch: 19, Acc: 96.07
EPOCH 20. Progress: 20.0%.
Train loss: 0.0002. Train Acc: 96.3750, Test loss: 0.0002. Test Acc: 95.8500. Time/epoch: 1.5555
saving best checkpoint at epoch: 21, Acc: 96.15
saving best checkpoint at epoch: 22, Acc: 96.39
saving best checkpoint at epoch: 26, Acc: 96.87
EPOCH 30. Progress: 30.0%.
Train loss: 0.0001. Train Acc: 97.3100, Test loss: 0.0002. Test Acc: 96.5200. Time/epoch: 1.5510
saving best checkpoint at epoch: 37, Acc: 96.94
saving best checkpoint at epoch: 39, Acc: 97.0
EPOCH 40. Progress: 40.0%.
Train loss: 0.0001. Train Acc: 97.8825, Test loss: 0.0002. Test Acc: 97.0100. Time/epoch: 1.6989
saving best checkpoint at epoch: 40, Acc: 97.01
saving best checkpoint at epoch: 46, Acc: 97.08
EPOCH 50. Progress: 50.0%.
Train loss: 0.0001. Train Acc: 98.0050, Test loss: 0.0002. Test Acc: 96.9200. Time/epoch: 1.5708
EPOCH 60. Progress: 60.0%.
Train loss: 0.0001. Train Acc: 98.1275, Test loss: 0.0002. Test Acc: 96.9700. Time/epoch: 1.7066
saving best checkpoint at epoch: 64, Acc: 97.12
saving best checkpoint at epoch: 68, Acc: 97.19
EPOCH 70. Progress: 70.0%.
Train loss: 0.0001. Train Acc: 97.3900, Test loss: 0.0002. Test Acc: 96.0400. Time/epoch: 1.5741
saving best checkpoint at epoch: 73, Acc: 97.29
EPOCH 80. Progress: 80.0%.
Train loss: 0.0001. Train Acc: 98.7425, Test loss: 0.0002. Test Acc: 97.0300. Time/epoch: 1.5584
saving best checkpoint at epoch: 86, Acc: 97.31
EPOCH 90. Progress: 90.0%.
Train loss: 0.0000. Train Acc: 99.1250, Test loss: 0.0002. Test Acc: 97.2700. Time/epoch: 1.7039
saving best checkpoint at epoch: 96, Acc: 97.32
EPOCH 100. Progress: 100.0%.
Train loss: 0.0000. Train Acc: 99.2700, Test loss: 0.0002. Test Acc: 97.2500. Time/epoch: 1.5596
Run history:
Accuracy/train | ▁▆▆▇▇▇▇▇▇▇▇▇█▇█▇███▇██████████▇█████████ |
Accuracy/val | ▁▆▇▇▇▇██████████████████████████████████ |
Loss/train | █▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▁▁▁▂▁▁▁▁▁▁▁▁▂▁▂▁▁▁▁▁▁▁▁▁ |
Loss/val | █▃▂▂▂▂▁▁▁▁▁▁▁▂▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▂▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 99.27 |
Accuracy/val | 97.25 |
Loss/train | 4e-05 |
Loss/val | 0.00021 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_095933-6urholcs/logs
wandb: Agent Starting Run: 6pdijj9r with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 0.0001
wandb: optimizer: adam
wandb: weight_decay: 0.0005
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_100229-6pdijj9r
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0008. Train Acc: 85.5125, Test loss: 0.0008. Test Acc: 85.2600. Time/epoch: 1.7448
saving best checkpoint at epoch: 0, Acc: 85.26
saving best checkpoint at epoch: 1, Acc: 90.79
saving best checkpoint at epoch: 2, Acc: 92.17
saving best checkpoint at epoch: 3, Acc: 92.47
saving best checkpoint at epoch: 4, Acc: 93.36
saving best checkpoint at epoch: 6, Acc: 93.93
saving best checkpoint at epoch: 7, Acc: 94.28
saving best checkpoint at epoch: 8, Acc: 94.67
EPOCH 10. Progress: 10.0%.
Train loss: 0.0003. Train Acc: 94.6975, Test loss: 0.0003. Test Acc: 94.7200. Time/epoch: 1.6724
saving best checkpoint at epoch: 10, Acc: 94.72
saving best checkpoint at epoch: 11, Acc: 95.06
saving best checkpoint at epoch: 13, Acc: 95.16
saving best checkpoint at epoch: 15, Acc: 95.65
saving best checkpoint at epoch: 19, Acc: 95.81
EPOCH 20. Progress: 20.0%.
Train loss: 0.0002. Train Acc: 95.2800, Test loss: 0.0002. Test Acc: 95.0600. Time/epoch: 1.5332
saving best checkpoint at epoch: 21, Acc: 95.9
saving best checkpoint at epoch: 22, Acc: 95.92
saving best checkpoint at epoch: 23, Acc: 96.01
saving best checkpoint at epoch: 24, Acc: 96.04
saving best checkpoint at epoch: 25, Acc: 96.1
saving best checkpoint at epoch: 29, Acc: 96.47
EPOCH 30. Progress: 30.0%.
Train loss: 0.0002. Train Acc: 96.5400, Test loss: 0.0002. Test Acc: 96.3400. Time/epoch: 1.5346
saving best checkpoint at epoch: 35, Acc: 96.55
saving best checkpoint at epoch: 37, Acc: 96.68
EPOCH 40. Progress: 40.0%.
Train loss: 0.0002. Train Acc: 97.1650, Test loss: 0.0002. Test Acc: 96.8700. Time/epoch: 1.6825
saving best checkpoint at epoch: 40, Acc: 96.87
saving best checkpoint at epoch: 43, Acc: 96.94
saving best checkpoint at epoch: 49, Acc: 97.12
EPOCH 50. Progress: 50.0%.
Train loss: 0.0001. Train Acc: 97.3625, Test loss: 0.0002. Test Acc: 96.8200. Time/epoch: 1.5875
saving best checkpoint at epoch: 54, Acc: 97.18
EPOCH 60. Progress: 60.0%.
Train loss: 0.0001. Train Acc: 97.3975, Test loss: 0.0002. Test Acc: 97.0400. Time/epoch: 1.5533
saving best checkpoint at epoch: 63, Acc: 97.21
saving best checkpoint at epoch: 64, Acc: 97.28
saving best checkpoint at epoch: 67, Acc: 97.31
EPOCH 70. Progress: 70.0%.
Train loss: 0.0001. Train Acc: 97.9650, Test loss: 0.0001. Test Acc: 97.3900. Time/epoch: 1.6906
saving best checkpoint at epoch: 70, Acc: 97.39
saving best checkpoint at epoch: 71, Acc: 97.46
EPOCH 80. Progress: 80.0%.
Train loss: 0.0001. Train Acc: 98.0625, Test loss: 0.0001. Test Acc: 97.3700. Time/epoch: 1.5684
saving best checkpoint at epoch: 81, Acc: 97.61
EPOCH 90. Progress: 90.0%.
Train loss: 0.0001. Train Acc: 98.0600, Test loss: 0.0001. Test Acc: 97.4500. Time/epoch: 1.6941
saving best checkpoint at epoch: 92, Acc: 97.68
EPOCH 100. Progress: 100.0%.
Train loss: 0.0001. Train Acc: 97.9675, Test loss: 0.0002. Test Acc: 97.1600. Time/epoch: 1.5800
Run history:
Accuracy/train | ▁▅▅▆▆▆▇▇▆▇▇▇▇▇▇▇▇██▇█▇██████████████████ |
Accuracy/val | ▁▅▆▆▆▇▇▇▇▇▇▇▇▇▇▇▇█▇▇█▇██████████████████ |
Loss/train | █▄▃▃▃▃▂▂▃▂▂▂▂▂▂▂▂▂▂▂▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▄▃▃▂▂▂▂▂▂▂▂▂▂▂▂▁▁▁▂▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 97.9675 |
Accuracy/val | 97.16 |
Loss/train | 0.00011 |
Loss/val | 0.00015 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_100229-6pdijj9r/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: x5tmqhlb with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 0.001
wandb: optimizer: adam
wandb: weight_decay: 0.0005
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_100605-x5tmqhlb
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0006. Train Acc: 86.6850, Test loss: 0.0006. Test Acc: 86.9800. Time/epoch: 1.7173
saving best checkpoint at epoch: 0, Acc: 86.98
saving best checkpoint at epoch: 1, Acc: 87.34
saving best checkpoint at epoch: 2, Acc: 89.27
saving best checkpoint at epoch: 3, Acc: 93.18
saving best checkpoint at epoch: 5, Acc: 94.76
saving best checkpoint at epoch: 8, Acc: 95.58
EPOCH 10. Progress: 10.0%.
Train loss: 0.0002. Train Acc: 95.5725, Test loss: 0.0002. Test Acc: 95.4000. Time/epoch: 1.5544
saving best checkpoint at epoch: 11, Acc: 95.61
saving best checkpoint at epoch: 17, Acc: 96.14
saving best checkpoint at epoch: 18, Acc: 96.39
saving best checkpoint at epoch: 19, Acc: 96.71
EPOCH 20. Progress: 20.0%.
Train loss: 0.0003. Train Acc: 93.0150, Test loss: 0.0004. Test Acc: 92.3900. Time/epoch: 1.5428
saving best checkpoint at epoch: 21, Acc: 96.85
EPOCH 30. Progress: 30.0%.
Train loss: 0.0002. Train Acc: 96.7325, Test loss: 0.0002. Test Acc: 95.9100. Time/epoch: 1.7182
saving best checkpoint at epoch: 33, Acc: 97.02
saving best checkpoint at epoch: 35, Acc: 97.04
EPOCH 40. Progress: 40.0%.
Train loss: 0.0001. Train Acc: 97.6800, Test loss: 0.0002. Test Acc: 96.5900. Time/epoch: 1.5697
saving best checkpoint at epoch: 43, Acc: 97.35
EPOCH 50. Progress: 50.0%.
Train loss: 0.0001. Train Acc: 98.4400, Test loss: 0.0002. Test Acc: 96.8300. Time/epoch: 1.5753
EPOCH 60. Progress: 60.0%.
Train loss: 0.0001. Train Acc: 98.3000, Test loss: 0.0002. Test Acc: 96.8600. Time/epoch: 1.5504
EPOCH 70. Progress: 70.0%.
Train loss: 0.0001. Train Acc: 98.2875, Test loss: 0.0003. Test Acc: 96.5100. Time/epoch: 1.6850
EPOCH 80. Progress: 80.0%.
Train loss: 0.0001. Train Acc: 99.0150, Test loss: 0.0002. Test Acc: 96.9100. Time/epoch: 1.5626
EPOCH 90. Progress: 90.0%.
Train loss: 0.0000. Train Acc: 99.2300, Test loss: 0.0002. Test Acc: 96.7600. Time/epoch: 1.5536
EPOCH 100. Progress: 100.0%.
Train loss: 0.0000. Train Acc: 99.5925, Test loss: 0.0003. Test Acc: 96.9600. Time/epoch: 1.6883
Run history:
Accuracy/train | ▁▂▆▅▆▅▅▆▄▆▆▇▆▇▇▇▇▇▇▇▇▇▇█▇▇▇▇▇█▇▇███▇▇███ |
Accuracy/val | ▁▃▆▆▇▆▆▇▅▆▇▇▇████████▇██▇█▇▇▇█▇▇███▇▇███ |
Loss/train | █▇▄▄▄▄▄▃▅▄▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▁▂▂▂▁▁▂▃▂▁▁ |
Loss/val | █▇▃▃▃▃▃▂▄▃▂▂▂▁▁▁▂▁▂▂▂▃▂▁▂▂▃▃▃▂▃▃▃▂▂▃▄▂▂▃ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 99.5925 |
Accuracy/val | 96.96 |
Loss/train | 2e-05 |
Loss/val | 0.00025 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_100605-x5tmqhlb/logs
wandb: Agent Starting Run: 266ntvle with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.0005
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_100901-266ntvle
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0005. Train Acc: 87.0625, Test loss: 0.0005. Test Acc: 87.4600. Time/epoch: 1.5719
saving best checkpoint at epoch: 0, Acc: 87.46
saving best checkpoint at epoch: 1, Acc: 92.26
saving best checkpoint at epoch: 2, Acc: 92.8
saving best checkpoint at epoch: 3, Acc: 93.65
saving best checkpoint at epoch: 4, Acc: 94.29
saving best checkpoint at epoch: 6, Acc: 95.1
EPOCH 10. Progress: 10.0%.
Train loss: 0.0002. Train Acc: 95.4900, Test loss: 0.0002. Test Acc: 95.2700. Time/epoch: 1.5569
saving best checkpoint at epoch: 10, Acc: 95.27
saving best checkpoint at epoch: 11, Acc: 95.63
saving best checkpoint at epoch: 15, Acc: 95.9
saving best checkpoint at epoch: 16, Acc: 96.07
saving best checkpoint at epoch: 17, Acc: 96.14
EPOCH 20. Progress: 20.0%.
Train loss: 0.0002. Train Acc: 96.5500, Test loss: 0.0002. Test Acc: 96.0800. Time/epoch: 1.7029
saving best checkpoint at epoch: 24, Acc: 96.51
saving best checkpoint at epoch: 28, Acc: 96.77
EPOCH 30. Progress: 30.0%.
Train loss: 0.0001. Train Acc: 97.0875, Test loss: 0.0002. Test Acc: 96.5900. Time/epoch: 1.5791
saving best checkpoint at epoch: 31, Acc: 96.82
saving best checkpoint at epoch: 32, Acc: 96.93
EPOCH 40. Progress: 40.0%.
Train loss: 0.0001. Train Acc: 97.8100, Test loss: 0.0002. Test Acc: 97.1200. Time/epoch: 1.5583
saving best checkpoint at epoch: 40, Acc: 97.12
saving best checkpoint at epoch: 45, Acc: 97.25
EPOCH 50. Progress: 50.0%.
Train loss: 0.0001. Train Acc: 97.3475, Test loss: 0.0002. Test Acc: 96.4500. Time/epoch: 1.7027
EPOCH 60. Progress: 60.0%.
Train loss: 0.0001. Train Acc: 97.7800, Test loss: 0.0002. Test Acc: 96.7700. Time/epoch: 1.5594
saving best checkpoint at epoch: 66, Acc: 97.41
EPOCH 70. Progress: 70.0%.
Train loss: 0.0001. Train Acc: 98.0450, Test loss: 0.0002. Test Acc: 96.9900. Time/epoch: 1.5679
saving best checkpoint at epoch: 71, Acc: 97.52
EPOCH 80. Progress: 80.0%.
Train loss: 0.0001. Train Acc: 98.0575, Test loss: 0.0002. Test Acc: 96.7800. Time/epoch: 1.5498
saving best checkpoint at epoch: 82, Acc: 97.56
saving best checkpoint at epoch: 88, Acc: 97.68
EPOCH 90. Progress: 90.0%.
Train loss: 0.0001. Train Acc: 98.3725, Test loss: 0.0002. Test Acc: 97.0900. Time/epoch: 1.5568
saving best checkpoint at epoch: 91, Acc: 97.71
saving best checkpoint at epoch: 97, Acc: 97.72
EPOCH 100. Progress: 100.0%.
Train loss: 0.0001. Train Acc: 99.0325, Test loss: 0.0002. Test Acc: 97.5800. Time/epoch: 1.7053
Run history:
Accuracy/train | ▁▄▅▅▆▆▆▇▇▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇█▆██▇▇██▇▇████ |
Accuracy/val | ▁▅▆▆▆▆▇▇▇▇▇▇▇▇▇▇▇█▇▇▇▇▇▇███▇██▇▇██▇▇████ |
Loss/train | █▅▄▄▃▄▃▃▃▃▃▂▂▂▂▂▂▂▃▂▂▂▂▂▂▂▁▃▁▁▂▂▁▁▃▂▁▁▁▁ |
Loss/val | █▄▃▃▃▃▂▂▂▂▁▁▁▁▂▂▁▁▂▂▂▂▁▂▁▁▁▃▁▁▂▂▁▂▃▂▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 99.0325 |
Accuracy/val | 97.58 |
Loss/train | 5e-05 |
Loss/val | 0.00017 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_100901-266ntvle/logs
wandb: Agent Starting Run: rr5vlvk0 with config:
wandb: batch_size: 64
wandb: epochs: 100
wandb: learning_rate: 0.001
wandb: optimizer: adam
wandb: weight_decay: 0.0005
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_101158-rr5vlvk0
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0043. Train Acc: 90.2450, Test loss: 0.0043. Test Acc: 90.0800. Time/epoch: 3.2289
saving best checkpoint at epoch: 0, Acc: 90.08
saving best checkpoint at epoch: 1, Acc: 93.92
saving best checkpoint at epoch: 2, Acc: 94.91
saving best checkpoint at epoch: 3, Acc: 95.44
saving best checkpoint at epoch: 6, Acc: 95.71
EPOCH 10. Progress: 10.0%.
Train loss: 0.0018. Train Acc: 95.1350, Test loss: 0.0020. Test Acc: 94.5200. Time/epoch: 3.2070
saving best checkpoint at epoch: 11, Acc: 96.56
saving best checkpoint at epoch: 17, Acc: 96.88
EPOCH 20. Progress: 20.0%.
Train loss: 0.0013. Train Acc: 96.5725, Test loss: 0.0019. Test Acc: 95.6000. Time/epoch: 3.2035
saving best checkpoint at epoch: 23, Acc: 96.98
EPOCH 30. Progress: 30.0%.
Train loss: 0.0015. Train Acc: 96.2325, Test loss: 0.0023. Test Acc: 95.1800. Time/epoch: 3.2075
saving best checkpoint at epoch: 37, Acc: 97.03
EPOCH 40. Progress: 40.0%.
Train loss: 0.0008. Train Acc: 98.1425, Test loss: 0.0018. Test Acc: 96.8000. Time/epoch: 3.2171
saving best checkpoint at epoch: 47, Acc: 97.07
EPOCH 50. Progress: 50.0%.
Train loss: 0.0007. Train Acc: 98.2350, Test loss: 0.0018. Test Acc: 96.9300. Time/epoch: 3.2140
EPOCH 60. Progress: 60.0%.
Train loss: 0.0008. Train Acc: 98.1900, Test loss: 0.0022. Test Acc: 96.6500. Time/epoch: 3.2068
saving best checkpoint at epoch: 62, Acc: 97.1
EPOCH 70. Progress: 70.0%.
Train loss: 0.0016. Train Acc: 96.3900, Test loss: 0.0034. Test Acc: 95.1000. Time/epoch: 3.2150
EPOCH 80. Progress: 80.0%.
Train loss: 0.0006. Train Acc: 98.7425, Test loss: 0.0021. Test Acc: 97.1200. Time/epoch: 3.2109
saving best checkpoint at epoch: 80, Acc: 97.12
EPOCH 90. Progress: 90.0%.
Train loss: 0.0022. Train Acc: 95.2250, Test loss: 0.0039. Test Acc: 93.9600. Time/epoch: 3.2242
EPOCH 100. Progress: 100.0%.
Train loss: 0.0006. Train Acc: 98.7425, Test loss: 0.0027. Test Acc: 96.7400. Time/epoch: 3.2204
Run history:
Accuracy/train | ▁▅▅▆▅▇▅▇▆▇▇▇▆▆▆▅▇▇█▇▇▆▆█▇███▇██▇██▅█████ |
Accuracy/val | ▁▆▆▇▅▇▅█▇███▆▇▆▆▇██▇█▆▇█▇██████▇██▅█████ |
Loss/train | █▃▄▃▃▂▄▂▂▂▂▂▃▃▃▃▂▂▁▂▂▃▃▁▂▁▁▁▂▁▁▂▁▁▄▁▁▁▁▁ |
Loss/val | ▇▂▂▂▂▁▃▁▂▁▁▂▃▂▃▄▃▂▁▂▃▅▃▂▃▂▂▂▂▂▂▄▄▄█▃▃▃▂▄ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.7425 |
Accuracy/val | 96.74 |
Loss/train | 0.0006 |
Loss/val | 0.00272 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_101158-rr5vlvk0/logs
wandb: Agent Starting Run: 0n0s9pss with config:
wandb: batch_size: 32
wandb: epochs: 10
wandb: learning_rate: 0.01
wandb: optimizer: adam
wandb: weight_decay: 0.0005
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_101735-0n0s9pss
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0483. Train Acc: 36.8250, Test loss: 0.0481. Test Acc: 37.5400. Time/epoch: 5.1060
saving best checkpoint at epoch: 0, Acc: 37.54
EPOCH 10. Progress: 100.0%.
Train loss: 0.0481. Train Acc: 36.8250, Test loss: 0.0480. Test Acc: 37.5400. Time/epoch: 5.0873
Run history:
Accuracy/train | ▁▁▁▁▁▁▁▁▁▁▁ |
Accuracy/val | ▁▁▁▁▁▁▁▁▁▁▁ |
Loss/train | █▂▂▁▂▂▂▂▁▃▂ |
Loss/val | █▂▄▁▂▁▂▂▂▄▃ |
epoch | ▁▂▂▃▄▅▅▆▇▇█ |
Run summary:
Accuracy/train | 36.825 |
Accuracy/val | 37.54 |
Loss/train | 0.04807 |
Loss/val | 0.04798 |
epoch | 10 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_101735-0n0s9pss/logs
wandb: Agent Starting Run: 8m1lsuw6 with config:
wandb: batch_size: 512
wandb: epochs: 50
wandb: learning_rate: 1e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_101849-8m1lsuw6
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0028. Train Acc: 58.7700, Test loss: 0.0029. Test Acc: 58.9700. Time/epoch: 1.7256
saving best checkpoint at epoch: 0, Acc: 58.97
saving best checkpoint at epoch: 1, Acc: 63.45
saving best checkpoint at epoch: 2, Acc: 80.97
saving best checkpoint at epoch: 3, Acc: 82.18
saving best checkpoint at epoch: 4, Acc: 84.26
saving best checkpoint at epoch: 5, Acc: 85.96
saving best checkpoint at epoch: 6, Acc: 87.13
saving best checkpoint at epoch: 7, Acc: 88.07
saving best checkpoint at epoch: 8, Acc: 88.52
saving best checkpoint at epoch: 9, Acc: 89.06
EPOCH 10. Progress: 20.0%.
Train loss: 0.0005. Train Acc: 89.8100, Test loss: 0.0005. Test Acc: 89.6900. Time/epoch: 1.5481
saving best checkpoint at epoch: 10, Acc: 89.69
saving best checkpoint at epoch: 11, Acc: 90.03
saving best checkpoint at epoch: 12, Acc: 90.48
saving best checkpoint at epoch: 13, Acc: 90.92
saving best checkpoint at epoch: 14, Acc: 91.3
saving best checkpoint at epoch: 16, Acc: 91.78
saving best checkpoint at epoch: 17, Acc: 91.98
saving best checkpoint at epoch: 18, Acc: 92.34
saving best checkpoint at epoch: 19, Acc: 92.5
EPOCH 20. Progress: 40.0%.
Train loss: 0.0004. Train Acc: 92.5675, Test loss: 0.0004. Test Acc: 92.7200. Time/epoch: 1.5397
saving best checkpoint at epoch: 20, Acc: 92.72
saving best checkpoint at epoch: 21, Acc: 93.22
saving best checkpoint at epoch: 24, Acc: 93.49
saving best checkpoint at epoch: 25, Acc: 93.52
saving best checkpoint at epoch: 27, Acc: 93.56
saving best checkpoint at epoch: 28, Acc: 93.92
EPOCH 30. Progress: 60.0%.
Train loss: 0.0003. Train Acc: 93.8200, Test loss: 0.0003. Test Acc: 93.9200. Time/epoch: 1.6722
saving best checkpoint at epoch: 31, Acc: 93.95
saving best checkpoint at epoch: 32, Acc: 94.0
saving best checkpoint at epoch: 33, Acc: 94.07
saving best checkpoint at epoch: 34, Acc: 94.17
saving best checkpoint at epoch: 36, Acc: 94.36
saving best checkpoint at epoch: 38, Acc: 94.55
EPOCH 40. Progress: 80.0%.
Train loss: 0.0003. Train Acc: 94.3475, Test loss: 0.0003. Test Acc: 94.4400. Time/epoch: 1.5486
saving best checkpoint at epoch: 44, Acc: 94.77
saving best checkpoint at epoch: 46, Acc: 94.82
EPOCH 50. Progress: 100.0%.
Train loss: 0.0003. Train Acc: 94.8550, Test loss: 0.0003. Test Acc: 94.8200. Time/epoch: 1.6937
Run history:
Accuracy/train | ▁▂▅▅▆▇▇▇▇▇▇▇▇▇▇█████████████████████████ |
Accuracy/val | ▁▂▅▆▆▆▇▇▇▇▇▇▇▇▇█████████████████████████ |
Loss/train | █▅▄▃▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▅▄▃▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███ |
Run summary:
Accuracy/train | 94.855 |
Accuracy/val | 94.82 |
Loss/train | 0.00027 |
Loss/val | 0.00029 |
epoch | 50 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_101849-8m1lsuw6/logs
wandb: Agent Starting Run: 3nw2fjlb with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 1e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_102027-3nw2fjlb
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0024. Train Acc: 64.5800, Test loss: 0.0024. Test Acc: 65.5100. Time/epoch: 1.5496
saving best checkpoint at epoch: 0, Acc: 65.51
saving best checkpoint at epoch: 1, Acc: 75.52
saving best checkpoint at epoch: 2, Acc: 79.1
saving best checkpoint at epoch: 3, Acc: 82.91
saving best checkpoint at epoch: 4, Acc: 85.02
saving best checkpoint at epoch: 5, Acc: 85.85
saving best checkpoint at epoch: 6, Acc: 86.43
saving best checkpoint at epoch: 7, Acc: 86.81
saving best checkpoint at epoch: 8, Acc: 87.11
saving best checkpoint at epoch: 9, Acc: 87.46
EPOCH 10. Progress: 10.0%.
Train loss: 0.0006. Train Acc: 87.7750, Test loss: 0.0006. Test Acc: 87.9500. Time/epoch: 1.6865
saving best checkpoint at epoch: 10, Acc: 87.95
saving best checkpoint at epoch: 11, Acc: 88.19
saving best checkpoint at epoch: 12, Acc: 88.5
saving best checkpoint at epoch: 13, Acc: 89.22
saving best checkpoint at epoch: 14, Acc: 89.29
saving best checkpoint at epoch: 15, Acc: 89.67
saving best checkpoint at epoch: 16, Acc: 89.99
saving best checkpoint at epoch: 17, Acc: 90.19
saving best checkpoint at epoch: 18, Acc: 90.64
saving best checkpoint at epoch: 19, Acc: 90.69
EPOCH 20. Progress: 20.0%.
Train loss: 0.0004. Train Acc: 91.1400, Test loss: 0.0004. Test Acc: 90.8500. Time/epoch: 1.5560
saving best checkpoint at epoch: 20, Acc: 90.85
saving best checkpoint at epoch: 21, Acc: 91.26
saving best checkpoint at epoch: 22, Acc: 91.47
saving best checkpoint at epoch: 23, Acc: 91.6
saving best checkpoint at epoch: 24, Acc: 91.87
saving best checkpoint at epoch: 25, Acc: 92.18
saving best checkpoint at epoch: 27, Acc: 92.37
saving best checkpoint at epoch: 28, Acc: 92.58
saving best checkpoint at epoch: 29, Acc: 92.65
EPOCH 30. Progress: 30.0%.
Train loss: 0.0003. Train Acc: 92.9575, Test loss: 0.0004. Test Acc: 92.7600. Time/epoch: 1.5399
saving best checkpoint at epoch: 30, Acc: 92.76
saving best checkpoint at epoch: 31, Acc: 92.89
saving best checkpoint at epoch: 32, Acc: 92.92
saving best checkpoint at epoch: 33, Acc: 93.14
saving best checkpoint at epoch: 34, Acc: 93.25
saving best checkpoint at epoch: 35, Acc: 93.36
saving best checkpoint at epoch: 36, Acc: 93.54
saving best checkpoint at epoch: 37, Acc: 93.64
saving best checkpoint at epoch: 39, Acc: 93.74
EPOCH 40. Progress: 40.0%.
Train loss: 0.0003. Train Acc: 93.8075, Test loss: 0.0003. Test Acc: 93.7600. Time/epoch: 1.6792
saving best checkpoint at epoch: 40, Acc: 93.76
saving best checkpoint at epoch: 41, Acc: 93.88
saving best checkpoint at epoch: 42, Acc: 93.93
saving best checkpoint at epoch: 44, Acc: 93.96
saving best checkpoint at epoch: 45, Acc: 94.04
saving best checkpoint at epoch: 46, Acc: 94.17
saving best checkpoint at epoch: 48, Acc: 94.22
EPOCH 50. Progress: 50.0%.
Train loss: 0.0003. Train Acc: 94.1300, Test loss: 0.0003. Test Acc: 94.1500. Time/epoch: 1.5607
saving best checkpoint at epoch: 51, Acc: 94.31
saving best checkpoint at epoch: 56, Acc: 94.43
saving best checkpoint at epoch: 58, Acc: 94.5
EPOCH 60. Progress: 60.0%.
Train loss: 0.0003. Train Acc: 94.2525, Test loss: 0.0003. Test Acc: 94.3900. Time/epoch: 1.5341
saving best checkpoint at epoch: 61, Acc: 94.57
saving best checkpoint at epoch: 67, Acc: 94.72
EPOCH 70. Progress: 70.0%.
Train loss: 0.0003. Train Acc: 94.7300, Test loss: 0.0003. Test Acc: 94.6200. Time/epoch: 1.6901
saving best checkpoint at epoch: 76, Acc: 94.76
EPOCH 80. Progress: 80.0%.
Train loss: 0.0002. Train Acc: 94.6675, Test loss: 0.0003. Test Acc: 94.5400. Time/epoch: 1.5367
saving best checkpoint at epoch: 81, Acc: 94.81
saving best checkpoint at epoch: 82, Acc: 94.82
saving best checkpoint at epoch: 85, Acc: 94.83
saving best checkpoint at epoch: 86, Acc: 94.88
saving best checkpoint at epoch: 87, Acc: 94.92
saving best checkpoint at epoch: 89, Acc: 95.02
EPOCH 90. Progress: 90.0%.
Train loss: 0.0002. Train Acc: 95.1400, Test loss: 0.0003. Test Acc: 94.9800. Time/epoch: 1.5398
saving best checkpoint at epoch: 93, Acc: 95.04
saving best checkpoint at epoch: 95, Acc: 95.09
saving best checkpoint at epoch: 97, Acc: 95.14
EPOCH 100. Progress: 100.0%.
Train loss: 0.0002. Train Acc: 95.1975, Test loss: 0.0002. Test Acc: 95.0700. Time/epoch: 1.6824
Run history:
Accuracy/train | ▁▄▆▆▆▆▇▇▇▇▇▇▇███████████████████████████ |
Accuracy/val | ▁▄▆▆▆▆▇▇▇▇▇▇▇███████████████████████████ |
Loss/train | █▅▃▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▅▃▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 95.1975 |
Accuracy/val | 95.07 |
Loss/train | 0.00023 |
Loss/val | 0.00025 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_102027-3nw2fjlb/logs
wandb: Agent Starting Run: w4otvfdn with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 3e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_102326-w4otvfdn
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0018. Train Acc: 73.3325, Test loss: 0.0019. Test Acc: 73.3900. Time/epoch: 1.5575
saving best checkpoint at epoch: 0, Acc: 73.39
saving best checkpoint at epoch: 1, Acc: 81.17
saving best checkpoint at epoch: 2, Acc: 84.62
saving best checkpoint at epoch: 3, Acc: 87.72
saving best checkpoint at epoch: 4, Acc: 88.33
saving best checkpoint at epoch: 5, Acc: 90.26
saving best checkpoint at epoch: 6, Acc: 90.75
saving best checkpoint at epoch: 7, Acc: 91.93
saving best checkpoint at epoch: 9, Acc: 92.59
EPOCH 10. Progress: 10.0%.
Train loss: 0.0004. Train Acc: 92.5625, Test loss: 0.0004. Test Acc: 92.7200. Time/epoch: 1.6854
saving best checkpoint at epoch: 10, Acc: 92.72
saving best checkpoint at epoch: 11, Acc: 92.87
saving best checkpoint at epoch: 12, Acc: 93.13
saving best checkpoint at epoch: 13, Acc: 93.32
saving best checkpoint at epoch: 14, Acc: 93.57
saving best checkpoint at epoch: 16, Acc: 93.96
saving best checkpoint at epoch: 17, Acc: 94.05
EPOCH 20. Progress: 20.0%.
Train loss: 0.0003. Train Acc: 94.1950, Test loss: 0.0003. Test Acc: 94.1600. Time/epoch: 1.5483
saving best checkpoint at epoch: 20, Acc: 94.16
saving best checkpoint at epoch: 21, Acc: 94.38
saving best checkpoint at epoch: 22, Acc: 94.43
saving best checkpoint at epoch: 25, Acc: 94.65
saving best checkpoint at epoch: 27, Acc: 94.79
EPOCH 30. Progress: 30.0%.
Train loss: 0.0002. Train Acc: 94.8325, Test loss: 0.0003. Test Acc: 94.8600. Time/epoch: 1.5352
saving best checkpoint at epoch: 30, Acc: 94.86
saving best checkpoint at epoch: 31, Acc: 95.04
saving best checkpoint at epoch: 32, Acc: 95.09
saving best checkpoint at epoch: 33, Acc: 95.23
saving best checkpoint at epoch: 35, Acc: 95.26
saving best checkpoint at epoch: 39, Acc: 95.39
EPOCH 40. Progress: 40.0%.
Train loss: 0.0002. Train Acc: 95.6375, Test loss: 0.0002. Test Acc: 95.4400. Time/epoch: 1.6827
saving best checkpoint at epoch: 40, Acc: 95.44
saving best checkpoint at epoch: 43, Acc: 95.68
EPOCH 50. Progress: 50.0%.
Train loss: 0.0002. Train Acc: 96.0175, Test loss: 0.0002. Test Acc: 95.8600. Time/epoch: 1.5663
saving best checkpoint at epoch: 50, Acc: 95.86
saving best checkpoint at epoch: 51, Acc: 95.99
saving best checkpoint at epoch: 57, Acc: 96.08
EPOCH 60. Progress: 60.0%.
Train loss: 0.0002. Train Acc: 96.2700, Test loss: 0.0002. Test Acc: 96.1000. Time/epoch: 1.5531
saving best checkpoint at epoch: 60, Acc: 96.1
saving best checkpoint at epoch: 62, Acc: 96.17
saving best checkpoint at epoch: 64, Acc: 96.24
saving best checkpoint at epoch: 68, Acc: 96.29
EPOCH 70. Progress: 70.0%.
Train loss: 0.0002. Train Acc: 96.4100, Test loss: 0.0002. Test Acc: 96.1500. Time/epoch: 1.6810
saving best checkpoint at epoch: 73, Acc: 96.36
saving best checkpoint at epoch: 75, Acc: 96.4
saving best checkpoint at epoch: 77, Acc: 96.49
EPOCH 80. Progress: 80.0%.
Train loss: 0.0002. Train Acc: 96.7775, Test loss: 0.0002. Test Acc: 96.4200. Time/epoch: 1.5384
saving best checkpoint at epoch: 81, Acc: 96.5
saving best checkpoint at epoch: 86, Acc: 96.53
EPOCH 90. Progress: 90.0%.
Train loss: 0.0002. Train Acc: 96.9825, Test loss: 0.0002. Test Acc: 96.6100. Time/epoch: 1.5540
saving best checkpoint at epoch: 90, Acc: 96.61
saving best checkpoint at epoch: 99, Acc: 96.65
EPOCH 100. Progress: 100.0%.
Train loss: 0.0002. Train Acc: 96.9925, Test loss: 0.0002. Test Acc: 96.6000. Time/epoch: 1.6825
Run history:
Accuracy/train | ▁▄▆▆▇▇▇▇▇▇▇▇▇██▇████████████████████████ |
Accuracy/val | ▁▄▆▇▇▇▇▇▇▇▇▇▇███████████████████████████ |
Loss/train | █▃▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▃▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 96.9925 |
Accuracy/val | 96.6 |
Loss/train | 0.00015 |
Loss/val | 0.00018 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_102326-w4otvfdn/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: s6qmnn97 with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 3e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_102631-s6qmnn97
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0013. Train Acc: 76.8100, Test loss: 0.0013. Test Acc: 76.4800. Time/epoch: 1.5949
saving best checkpoint at epoch: 0, Acc: 76.48
saving best checkpoint at epoch: 1, Acc: 82.21
saving best checkpoint at epoch: 2, Acc: 85.55
saving best checkpoint at epoch: 3, Acc: 87.69
saving best checkpoint at epoch: 4, Acc: 89.17
saving best checkpoint at epoch: 5, Acc: 90.42
saving best checkpoint at epoch: 6, Acc: 91.1
saving best checkpoint at epoch: 7, Acc: 91.56
saving best checkpoint at epoch: 8, Acc: 92.04
saving best checkpoint at epoch: 9, Acc: 92.41
EPOCH 10. Progress: 10.0%.
Train loss: 0.0003. Train Acc: 92.6875, Test loss: 0.0004. Test Acc: 92.7900. Time/epoch: 1.6882
saving best checkpoint at epoch: 10, Acc: 92.79
saving best checkpoint at epoch: 11, Acc: 93.23
saving best checkpoint at epoch: 13, Acc: 93.8
saving best checkpoint at epoch: 14, Acc: 93.85
saving best checkpoint at epoch: 15, Acc: 93.89
saving best checkpoint at epoch: 18, Acc: 94.36
EPOCH 20. Progress: 20.0%.
Train loss: 0.0003. Train Acc: 94.5025, Test loss: 0.0003. Test Acc: 94.4200. Time/epoch: 1.5432
saving best checkpoint at epoch: 20, Acc: 94.42
saving best checkpoint at epoch: 21, Acc: 94.67
saving best checkpoint at epoch: 23, Acc: 94.75
saving best checkpoint at epoch: 24, Acc: 95.08
EPOCH 30. Progress: 30.0%.
Train loss: 0.0002. Train Acc: 95.2675, Test loss: 0.0003. Test Acc: 95.2600. Time/epoch: 1.5424
saving best checkpoint at epoch: 30, Acc: 95.26
saving best checkpoint at epoch: 32, Acc: 95.39
EPOCH 40. Progress: 40.0%.
Train loss: 0.0002. Train Acc: 95.4625, Test loss: 0.0003. Test Acc: 95.2200. Time/epoch: 1.5504
saving best checkpoint at epoch: 41, Acc: 95.5
saving best checkpoint at epoch: 45, Acc: 95.55
saving best checkpoint at epoch: 48, Acc: 95.68
EPOCH 50. Progress: 50.0%.
Train loss: 0.0002. Train Acc: 96.0050, Test loss: 0.0002. Test Acc: 95.6700. Time/epoch: 1.6977
saving best checkpoint at epoch: 55, Acc: 95.75
saving best checkpoint at epoch: 56, Acc: 95.78
saving best checkpoint at epoch: 57, Acc: 95.82
saving best checkpoint at epoch: 58, Acc: 95.83
EPOCH 60. Progress: 60.0%.
Train loss: 0.0002. Train Acc: 95.7000, Test loss: 0.0002. Test Acc: 95.5300. Time/epoch: 1.5415
saving best checkpoint at epoch: 62, Acc: 95.91
saving best checkpoint at epoch: 66, Acc: 95.97
EPOCH 70. Progress: 70.0%.
Train loss: 0.0002. Train Acc: 96.4200, Test loss: 0.0002. Test Acc: 95.9700. Time/epoch: 1.5387
saving best checkpoint at epoch: 71, Acc: 95.98
saving best checkpoint at epoch: 73, Acc: 96.0
saving best checkpoint at epoch: 78, Acc: 96.05
saving best checkpoint at epoch: 79, Acc: 96.09
EPOCH 80. Progress: 80.0%.
Train loss: 0.0002. Train Acc: 96.4050, Test loss: 0.0002. Test Acc: 95.9200. Time/epoch: 1.6814
saving best checkpoint at epoch: 82, Acc: 96.15
saving best checkpoint at epoch: 85, Acc: 96.18
saving best checkpoint at epoch: 87, Acc: 96.25
EPOCH 90. Progress: 90.0%.
Train loss: 0.0002. Train Acc: 96.7525, Test loss: 0.0002. Test Acc: 96.2400. Time/epoch: 1.5529
saving best checkpoint at epoch: 94, Acc: 96.28
EPOCH 100. Progress: 100.0%.
Train loss: 0.0002. Train Acc: 96.8125, Test loss: 0.0002. Test Acc: 96.2700. Time/epoch: 1.5407
Run history:
Accuracy/train | ▁▄▆▆▇▇▇▇▇▇▇▇▇▇██████████████████████████ |
Accuracy/val | ▁▄▆▆▇▇▇▇▇▇██████████████████████████████ |
Loss/train | █▄▃▂▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▄▃▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 96.8125 |
Accuracy/val | 96.27 |
Loss/train | 0.00017 |
Loss/val | 0.0002 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_102631-s6qmnn97/logs
wandb: Agent Starting Run: pwurgze0 with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 1e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_102931-pwurgze0
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0031. Train Acc: 47.5750, Test loss: 0.0031. Test Acc: 47.7700. Time/epoch: 1.5660
saving best checkpoint at epoch: 0, Acc: 47.77
saving best checkpoint at epoch: 1, Acc: 60.28
saving best checkpoint at epoch: 2, Acc: 66.63
saving best checkpoint at epoch: 3, Acc: 71.05
saving best checkpoint at epoch: 4, Acc: 73.34
saving best checkpoint at epoch: 5, Acc: 75.86
saving best checkpoint at epoch: 6, Acc: 79.66
saving best checkpoint at epoch: 7, Acc: 81.76
saving best checkpoint at epoch: 8, Acc: 84.55
saving best checkpoint at epoch: 9, Acc: 86.29
EPOCH 10. Progress: 10.0%.
Train loss: 0.0006. Train Acc: 86.6850, Test loss: 0.0006. Test Acc: 86.5300. Time/epoch: 1.6877
saving best checkpoint at epoch: 10, Acc: 86.53
saving best checkpoint at epoch: 11, Acc: 87.31
saving best checkpoint at epoch: 12, Acc: 88.37
saving best checkpoint at epoch: 13, Acc: 89.03
saving best checkpoint at epoch: 14, Acc: 89.34
saving best checkpoint at epoch: 15, Acc: 89.58
saving best checkpoint at epoch: 16, Acc: 89.84
saving best checkpoint at epoch: 17, Acc: 90.24
saving best checkpoint at epoch: 18, Acc: 90.44
saving best checkpoint at epoch: 19, Acc: 90.61
EPOCH 20. Progress: 20.0%.
Train loss: 0.0004. Train Acc: 91.2475, Test loss: 0.0004. Test Acc: 90.9300. Time/epoch: 1.5504
saving best checkpoint at epoch: 20, Acc: 90.93
saving best checkpoint at epoch: 21, Acc: 91.07
saving best checkpoint at epoch: 23, Acc: 91.43
saving best checkpoint at epoch: 25, Acc: 91.56
saving best checkpoint at epoch: 26, Acc: 91.69
saving best checkpoint at epoch: 27, Acc: 91.98
saving best checkpoint at epoch: 28, Acc: 92.02
saving best checkpoint at epoch: 29, Acc: 92.06
EPOCH 30. Progress: 30.0%.
Train loss: 0.0004. Train Acc: 92.2625, Test loss: 0.0004. Test Acc: 92.0600. Time/epoch: 1.6804
saving best checkpoint at epoch: 31, Acc: 92.13
saving best checkpoint at epoch: 32, Acc: 92.31
saving best checkpoint at epoch: 33, Acc: 92.34
saving best checkpoint at epoch: 34, Acc: 92.37
saving best checkpoint at epoch: 35, Acc: 92.55
saving best checkpoint at epoch: 37, Acc: 92.6
saving best checkpoint at epoch: 38, Acc: 92.78
saving best checkpoint at epoch: 39, Acc: 92.85
EPOCH 40. Progress: 40.0%.
Train loss: 0.0003. Train Acc: 93.1400, Test loss: 0.0003. Test Acc: 92.8800. Time/epoch: 1.5314
saving best checkpoint at epoch: 40, Acc: 92.88
saving best checkpoint at epoch: 41, Acc: 93.02
saving best checkpoint at epoch: 42, Acc: 93.08
saving best checkpoint at epoch: 44, Acc: 93.1
saving best checkpoint at epoch: 45, Acc: 93.18
saving best checkpoint at epoch: 47, Acc: 93.33
saving best checkpoint at epoch: 49, Acc: 93.45
EPOCH 50. Progress: 50.0%.
Train loss: 0.0003. Train Acc: 93.9575, Test loss: 0.0003. Test Acc: 93.5600. Time/epoch: 1.7005
saving best checkpoint at epoch: 50, Acc: 93.56
saving best checkpoint at epoch: 51, Acc: 93.59
saving best checkpoint at epoch: 53, Acc: 93.64
saving best checkpoint at epoch: 55, Acc: 93.74
saving best checkpoint at epoch: 56, Acc: 93.81
saving best checkpoint at epoch: 58, Acc: 93.85
saving best checkpoint at epoch: 59, Acc: 93.9
EPOCH 60. Progress: 60.0%.
Train loss: 0.0003. Train Acc: 94.4750, Test loss: 0.0003. Test Acc: 93.9700. Time/epoch: 1.5386
saving best checkpoint at epoch: 60, Acc: 93.97
saving best checkpoint at epoch: 65, Acc: 94.17
saving best checkpoint at epoch: 67, Acc: 94.22
saving best checkpoint at epoch: 68, Acc: 94.23
EPOCH 70. Progress: 70.0%.
Train loss: 0.0003. Train Acc: 94.8150, Test loss: 0.0003. Test Acc: 94.2900. Time/epoch: 1.5432
saving best checkpoint at epoch: 70, Acc: 94.29
saving best checkpoint at epoch: 71, Acc: 94.41
saving best checkpoint at epoch: 77, Acc: 94.45
saving best checkpoint at epoch: 78, Acc: 94.6
saving best checkpoint at epoch: 79, Acc: 94.63
EPOCH 80. Progress: 80.0%.
Train loss: 0.0002. Train Acc: 95.0225, Test loss: 0.0003. Test Acc: 94.6100. Time/epoch: 1.5393
saving best checkpoint at epoch: 81, Acc: 94.65
saving best checkpoint at epoch: 83, Acc: 94.73
saving best checkpoint at epoch: 86, Acc: 94.79
saving best checkpoint at epoch: 88, Acc: 94.81
saving best checkpoint at epoch: 89, Acc: 94.82
EPOCH 90. Progress: 90.0%.
Train loss: 0.0002. Train Acc: 95.4000, Test loss: 0.0003. Test Acc: 94.8200. Time/epoch: 1.6811
saving best checkpoint at epoch: 91, Acc: 94.88
saving best checkpoint at epoch: 93, Acc: 94.9
saving best checkpoint at epoch: 97, Acc: 94.97
saving best checkpoint at epoch: 98, Acc: 95.07
EPOCH 100. Progress: 100.0%.
Train loss: 0.0002. Train Acc: 95.3650, Test loss: 0.0003. Test Acc: 94.9600. Time/epoch: 1.6837
Run history:
Accuracy/train | ▁▄▅▆▇▇▇▇▇▇▇█████████████████████████████ |
Accuracy/val | ▁▄▅▆▇▇▇▇▇▇▇█████████████████████████████ |
Loss/train | █▅▃▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▅▃▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 95.365 |
Accuracy/val | 94.96 |
Loss/train | 0.00023 |
Loss/val | 0.00026 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_102931-pwurgze0/logs
wandb: Agent Starting Run: ax3vvrwq with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 3e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_103229-ax3vvrwq
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0024. Train Acc: 73.6525, Test loss: 0.0024. Test Acc: 73.7300. Time/epoch: 1.5804
saving best checkpoint at epoch: 0, Acc: 73.73
saving best checkpoint at epoch: 1, Acc: 80.75
saving best checkpoint at epoch: 2, Acc: 86.08
saving best checkpoint at epoch: 3, Acc: 87.72
saving best checkpoint at epoch: 4, Acc: 88.2
saving best checkpoint at epoch: 5, Acc: 89.02
saving best checkpoint at epoch: 6, Acc: 89.41
saving best checkpoint at epoch: 7, Acc: 90.2
saving best checkpoint at epoch: 8, Acc: 90.76
saving best checkpoint at epoch: 9, Acc: 91.02
EPOCH 10. Progress: 10.0%.
Train loss: 0.0004. Train Acc: 91.3175, Test loss: 0.0004. Test Acc: 91.3100. Time/epoch: 1.6877
saving best checkpoint at epoch: 10, Acc: 91.31
saving best checkpoint at epoch: 11, Acc: 91.9
saving best checkpoint at epoch: 13, Acc: 92.29
saving best checkpoint at epoch: 14, Acc: 92.78
saving best checkpoint at epoch: 15, Acc: 93.1
saving best checkpoint at epoch: 16, Acc: 93.18
saving best checkpoint at epoch: 17, Acc: 93.65
saving best checkpoint at epoch: 18, Acc: 93.88
saving best checkpoint at epoch: 19, Acc: 93.99
EPOCH 20. Progress: 20.0%.
Train loss: 0.0003. Train Acc: 93.9350, Test loss: 0.0003. Test Acc: 94.2200. Time/epoch: 1.5540
saving best checkpoint at epoch: 20, Acc: 94.22
saving best checkpoint at epoch: 21, Acc: 94.34
saving best checkpoint at epoch: 22, Acc: 94.48
saving best checkpoint at epoch: 24, Acc: 94.51
saving best checkpoint at epoch: 26, Acc: 94.85
saving best checkpoint at epoch: 27, Acc: 95.05
EPOCH 30. Progress: 30.0%.
Train loss: 0.0003. Train Acc: 94.9075, Test loss: 0.0003. Test Acc: 95.0100. Time/epoch: 1.6922
saving best checkpoint at epoch: 31, Acc: 95.11
saving best checkpoint at epoch: 32, Acc: 95.24
saving best checkpoint at epoch: 33, Acc: 95.42
saving best checkpoint at epoch: 37, Acc: 95.7
saving best checkpoint at epoch: 39, Acc: 95.72
EPOCH 40. Progress: 40.0%.
Train loss: 0.0002. Train Acc: 95.6025, Test loss: 0.0003. Test Acc: 95.5300. Time/epoch: 1.6833
saving best checkpoint at epoch: 41, Acc: 95.94
EPOCH 50. Progress: 50.0%.
Train loss: 0.0002. Train Acc: 96.1675, Test loss: 0.0002. Test Acc: 96.0000. Time/epoch: 1.5599
saving best checkpoint at epoch: 50, Acc: 96.0
saving best checkpoint at epoch: 52, Acc: 96.06
saving best checkpoint at epoch: 54, Acc: 96.18
EPOCH 60. Progress: 60.0%.
Train loss: 0.0002. Train Acc: 96.2350, Test loss: 0.0002. Test Acc: 96.1100. Time/epoch: 1.6841
saving best checkpoint at epoch: 61, Acc: 96.21
saving best checkpoint at epoch: 63, Acc: 96.34
saving best checkpoint at epoch: 69, Acc: 96.35
EPOCH 70. Progress: 70.0%.
Train loss: 0.0002. Train Acc: 96.4100, Test loss: 0.0002. Test Acc: 96.2100. Time/epoch: 1.5318
saving best checkpoint at epoch: 72, Acc: 96.43
saving best checkpoint at epoch: 75, Acc: 96.57
saving best checkpoint at epoch: 78, Acc: 96.65
EPOCH 80. Progress: 80.0%.
Train loss: 0.0002. Train Acc: 96.7125, Test loss: 0.0002. Test Acc: 96.4800. Time/epoch: 1.6840
saving best checkpoint at epoch: 83, Acc: 96.67
saving best checkpoint at epoch: 84, Acc: 96.77
saving best checkpoint at epoch: 89, Acc: 96.81
EPOCH 90. Progress: 90.0%.
Train loss: 0.0002. Train Acc: 96.7375, Test loss: 0.0002. Test Acc: 96.4500. Time/epoch: 1.5350
saving best checkpoint at epoch: 93, Acc: 96.87
EPOCH 100. Progress: 100.0%.
Train loss: 0.0002. Train Acc: 97.0350, Test loss: 0.0002. Test Acc: 96.7900. Time/epoch: 1.5425
Run history:
Accuracy/train | ▁▅▆▆▆▆▇▇▇▇▇▇▇▇▇██▇██████████████████████ |
Accuracy/val | ▁▅▆▆▆▇▇▇▇▇▇▇▇███████████████████████████ |
Loss/train | █▃▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▃▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 97.035 |
Accuracy/val | 96.79 |
Loss/train | 0.00016 |
Loss/val | 0.00018 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_103229-ax3vvrwq/logs
wandb: Agent Starting Run: o8negy92 with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 1e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_103528-o8negy92
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0029. Train Acc: 52.5725, Test loss: 0.0030. Test Acc: 53.4100. Time/epoch: 1.5657
saving best checkpoint at epoch: 0, Acc: 53.41
saving best checkpoint at epoch: 1, Acc: 74.71
saving best checkpoint at epoch: 2, Acc: 78.01
saving best checkpoint at epoch: 3, Acc: 80.75
saving best checkpoint at epoch: 4, Acc: 83.03
saving best checkpoint at epoch: 5, Acc: 85.52
saving best checkpoint at epoch: 6, Acc: 87.68
saving best checkpoint at epoch: 7, Acc: 88.61
saving best checkpoint at epoch: 8, Acc: 89.57
saving best checkpoint at epoch: 9, Acc: 90.16
EPOCH 10. Progress: 10.0%.
Train loss: 0.0005. Train Acc: 90.6600, Test loss: 0.0005. Test Acc: 90.3800. Time/epoch: 1.7099
saving best checkpoint at epoch: 10, Acc: 90.38
saving best checkpoint at epoch: 11, Acc: 90.82
saving best checkpoint at epoch: 12, Acc: 91.08
saving best checkpoint at epoch: 13, Acc: 91.3
saving best checkpoint at epoch: 14, Acc: 91.44
saving best checkpoint at epoch: 15, Acc: 91.64
saving best checkpoint at epoch: 16, Acc: 91.67
saving best checkpoint at epoch: 17, Acc: 91.83
saving best checkpoint at epoch: 18, Acc: 92.07
saving best checkpoint at epoch: 19, Acc: 92.08
EPOCH 20. Progress: 20.0%.
Train loss: 0.0004. Train Acc: 92.5325, Test loss: 0.0004. Test Acc: 92.2800. Time/epoch: 1.5457
saving best checkpoint at epoch: 20, Acc: 92.28
saving best checkpoint at epoch: 21, Acc: 92.3
saving best checkpoint at epoch: 22, Acc: 92.32
saving best checkpoint at epoch: 24, Acc: 92.45
saving best checkpoint at epoch: 26, Acc: 92.57
saving best checkpoint at epoch: 27, Acc: 92.72
saving best checkpoint at epoch: 29, Acc: 92.79
EPOCH 30. Progress: 30.0%.
Train loss: 0.0003. Train Acc: 92.9850, Test loss: 0.0003. Test Acc: 92.9800. Time/epoch: 1.6818
saving best checkpoint at epoch: 30, Acc: 92.98
saving best checkpoint at epoch: 31, Acc: 93.0
saving best checkpoint at epoch: 34, Acc: 93.11
saving best checkpoint at epoch: 35, Acc: 93.22
saving best checkpoint at epoch: 38, Acc: 93.31
EPOCH 40. Progress: 40.0%.
Train loss: 0.0003. Train Acc: 93.4650, Test loss: 0.0003. Test Acc: 93.3400. Time/epoch: 1.5396
saving best checkpoint at epoch: 40, Acc: 93.34
saving best checkpoint at epoch: 41, Acc: 93.4
saving best checkpoint at epoch: 42, Acc: 93.51
saving best checkpoint at epoch: 43, Acc: 93.53
saving best checkpoint at epoch: 44, Acc: 93.67
saving best checkpoint at epoch: 46, Acc: 93.74
EPOCH 50. Progress: 50.0%.
Train loss: 0.0003. Train Acc: 93.9100, Test loss: 0.0003. Test Acc: 93.9100. Time/epoch: 1.6861
saving best checkpoint at epoch: 50, Acc: 93.91
saving best checkpoint at epoch: 51, Acc: 93.94
saving best checkpoint at epoch: 55, Acc: 94.19
saving best checkpoint at epoch: 57, Acc: 94.22
EPOCH 60. Progress: 60.0%.
Train loss: 0.0003. Train Acc: 94.1975, Test loss: 0.0003. Test Acc: 94.3200. Time/epoch: 1.5335
saving best checkpoint at epoch: 60, Acc: 94.32
saving best checkpoint at epoch: 65, Acc: 94.67
saving best checkpoint at epoch: 69, Acc: 94.7
EPOCH 70. Progress: 70.0%.
Train loss: 0.0003. Train Acc: 94.2275, Test loss: 0.0003. Test Acc: 94.4500. Time/epoch: 1.5460
saving best checkpoint at epoch: 72, Acc: 94.75
saving best checkpoint at epoch: 77, Acc: 94.86
EPOCH 80. Progress: 80.0%.
Train loss: 0.0003. Train Acc: 94.6300, Test loss: 0.0003. Test Acc: 94.8400. Time/epoch: 1.5532
saving best checkpoint at epoch: 82, Acc: 94.89
saving best checkpoint at epoch: 83, Acc: 95.02
saving best checkpoint at epoch: 85, Acc: 95.09
EPOCH 90. Progress: 90.0%.
Train loss: 0.0003. Train Acc: 94.9225, Test loss: 0.0003. Test Acc: 95.1900. Time/epoch: 1.5430
saving best checkpoint at epoch: 90, Acc: 95.19
saving best checkpoint at epoch: 94, Acc: 95.25
saving best checkpoint at epoch: 95, Acc: 95.3
saving best checkpoint at epoch: 99, Acc: 95.35
EPOCH 100. Progress: 100.0%.
Train loss: 0.0002. Train Acc: 95.0700, Test loss: 0.0003. Test Acc: 95.2900. Time/epoch: 1.6845
Run history:
Accuracy/train | ▁▅▆▇▇▇▇█████████████████████████████████ |
Accuracy/val | ▁▅▆▇▇▇▇▇▇▇██████████████████████████████ |
Loss/train | █▄▃▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▄▃▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 95.07 |
Accuracy/val | 95.29 |
Loss/train | 0.00024 |
Loss/val | 0.00026 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_103528-o8negy92/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: b7mppksc with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 0.0001
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_103834-b7mppksc
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0009. Train Acc: 83.2800, Test loss: 0.0010. Test Acc: 82.8800. Time/epoch: 1.5677
saving best checkpoint at epoch: 0, Acc: 82.88
saving best checkpoint at epoch: 1, Acc: 87.72
saving best checkpoint at epoch: 2, Acc: 89.26
saving best checkpoint at epoch: 3, Acc: 91.18
saving best checkpoint at epoch: 5, Acc: 92.1
saving best checkpoint at epoch: 6, Acc: 92.79
saving best checkpoint at epoch: 7, Acc: 93.46
saving best checkpoint at epoch: 9, Acc: 94.3
EPOCH 10. Progress: 10.0%.
Train loss: 0.0003. Train Acc: 93.6950, Test loss: 0.0003. Test Acc: 93.7600. Time/epoch: 1.6787
saving best checkpoint at epoch: 11, Acc: 94.68
saving best checkpoint at epoch: 12, Acc: 95.18
saving best checkpoint at epoch: 17, Acc: 95.27
EPOCH 20. Progress: 20.0%.
Train loss: 0.0002. Train Acc: 96.0900, Test loss: 0.0002. Test Acc: 95.9200. Time/epoch: 1.5397
saving best checkpoint at epoch: 20, Acc: 95.92
saving best checkpoint at epoch: 25, Acc: 96.09
saving best checkpoint at epoch: 26, Acc: 96.11
EPOCH 30. Progress: 30.0%.
Train loss: 0.0002. Train Acc: 96.4625, Test loss: 0.0002. Test Acc: 96.1600. Time/epoch: 1.6787
saving best checkpoint at epoch: 30, Acc: 96.16
saving best checkpoint at epoch: 32, Acc: 96.46
saving best checkpoint at epoch: 39, Acc: 96.49
EPOCH 40. Progress: 40.0%.
Train loss: 0.0002. Train Acc: 96.9550, Test loss: 0.0002. Test Acc: 96.6700. Time/epoch: 1.5390
saving best checkpoint at epoch: 40, Acc: 96.67
EPOCH 50. Progress: 50.0%.
Train loss: 0.0002. Train Acc: 96.9625, Test loss: 0.0002. Test Acc: 96.6100. Time/epoch: 1.6923
saving best checkpoint at epoch: 52, Acc: 96.91
EPOCH 60. Progress: 60.0%.
Train loss: 0.0002. Train Acc: 96.7725, Test loss: 0.0002. Test Acc: 96.4900. Time/epoch: 1.5414
saving best checkpoint at epoch: 66, Acc: 97.08
EPOCH 70. Progress: 70.0%.
Train loss: 0.0001. Train Acc: 97.2025, Test loss: 0.0002. Test Acc: 96.7100. Time/epoch: 1.5450
saving best checkpoint at epoch: 77, Acc: 97.24
saving best checkpoint at epoch: 78, Acc: 97.28
EPOCH 80. Progress: 80.0%.
Train loss: 0.0001. Train Acc: 97.7900, Test loss: 0.0002. Test Acc: 97.3300. Time/epoch: 1.5395
saving best checkpoint at epoch: 80, Acc: 97.33
EPOCH 90. Progress: 90.0%.
Train loss: 0.0001. Train Acc: 97.9050, Test loss: 0.0002. Test Acc: 97.3400. Time/epoch: 1.5505
saving best checkpoint at epoch: 90, Acc: 97.34
saving best checkpoint at epoch: 98, Acc: 97.55
EPOCH 100. Progress: 100.0%.
Train loss: 0.0001. Train Acc: 97.8975, Test loss: 0.0002. Test Acc: 97.2800. Time/epoch: 1.6822
Run history:
Accuracy/train | ▁▄▅▆▆▇▇▇▇▇▇▇▇▇▆▇▇▇▇█▇███████████████████ |
Accuracy/val | ▁▄▅▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇██▇███████████████████ |
Loss/train | █▄▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▂▂▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▄▃▂▂▂▂▂▂▂▁▂▁▁▂▁▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 97.8975 |
Accuracy/val | 97.28 |
Loss/train | 0.00011 |
Loss/val | 0.00016 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_103834-b7mppksc/logs
wandb: Agent Starting Run: 11gt3k3i with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 1e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_104133-11gt3k3i
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0027. Train Acc: 55.9300, Test loss: 0.0027. Test Acc: 57.2700. Time/epoch: 1.5490
saving best checkpoint at epoch: 0, Acc: 57.27
saving best checkpoint at epoch: 1, Acc: 77.36
saving best checkpoint at epoch: 2, Acc: 80.7
saving best checkpoint at epoch: 3, Acc: 85.38
saving best checkpoint at epoch: 4, Acc: 87.24
saving best checkpoint at epoch: 5, Acc: 88.48
saving best checkpoint at epoch: 6, Acc: 89.05
saving best checkpoint at epoch: 7, Acc: 89.57
saving best checkpoint at epoch: 8, Acc: 89.87
saving best checkpoint at epoch: 9, Acc: 90.2
EPOCH 10. Progress: 10.0%.
Train loss: 0.0005. Train Acc: 90.3575, Test loss: 0.0005. Test Acc: 90.4400. Time/epoch: 1.6825
saving best checkpoint at epoch: 10, Acc: 90.44
saving best checkpoint at epoch: 11, Acc: 90.66
saving best checkpoint at epoch: 12, Acc: 91.02
saving best checkpoint at epoch: 13, Acc: 91.16
saving best checkpoint at epoch: 14, Acc: 91.46
saving best checkpoint at epoch: 15, Acc: 91.81
saving best checkpoint at epoch: 16, Acc: 91.89
saving best checkpoint at epoch: 17, Acc: 92.08
saving best checkpoint at epoch: 18, Acc: 92.23
saving best checkpoint at epoch: 19, Acc: 92.37
EPOCH 20. Progress: 20.0%.
Train loss: 0.0004. Train Acc: 92.1875, Test loss: 0.0004. Test Acc: 92.4400. Time/epoch: 1.5484
saving best checkpoint at epoch: 20, Acc: 92.44
saving best checkpoint at epoch: 21, Acc: 92.59
saving best checkpoint at epoch: 22, Acc: 92.68
saving best checkpoint at epoch: 23, Acc: 92.83
saving best checkpoint at epoch: 24, Acc: 93.0
saving best checkpoint at epoch: 25, Acc: 93.14
saving best checkpoint at epoch: 26, Acc: 93.16
saving best checkpoint at epoch: 27, Acc: 93.24
saving best checkpoint at epoch: 28, Acc: 93.34
saving best checkpoint at epoch: 29, Acc: 93.43
EPOCH 30. Progress: 30.0%.
Train loss: 0.0003. Train Acc: 93.3100, Test loss: 0.0003. Test Acc: 93.3700. Time/epoch: 1.5422
saving best checkpoint at epoch: 31, Acc: 93.65
saving best checkpoint at epoch: 33, Acc: 93.66
saving best checkpoint at epoch: 34, Acc: 93.71
saving best checkpoint at epoch: 35, Acc: 93.92
saving best checkpoint at epoch: 37, Acc: 93.97
saving best checkpoint at epoch: 38, Acc: 94.09
saving best checkpoint at epoch: 39, Acc: 94.13
EPOCH 40. Progress: 40.0%.
Train loss: 0.0003. Train Acc: 93.9300, Test loss: 0.0003. Test Acc: 94.2000. Time/epoch: 1.6882
saving best checkpoint at epoch: 40, Acc: 94.2
saving best checkpoint at epoch: 43, Acc: 94.23
saving best checkpoint at epoch: 44, Acc: 94.48
saving best checkpoint at epoch: 47, Acc: 94.56
EPOCH 50. Progress: 50.0%.
Train loss: 0.0003. Train Acc: 94.5775, Test loss: 0.0003. Test Acc: 94.5800. Time/epoch: 1.5991
saving best checkpoint at epoch: 50, Acc: 94.58
saving best checkpoint at epoch: 51, Acc: 94.63
saving best checkpoint at epoch: 52, Acc: 94.64
saving best checkpoint at epoch: 53, Acc: 94.68
saving best checkpoint at epoch: 54, Acc: 94.72
saving best checkpoint at epoch: 55, Acc: 94.73
saving best checkpoint at epoch: 56, Acc: 94.76
saving best checkpoint at epoch: 57, Acc: 94.94
EPOCH 60. Progress: 60.0%.
Train loss: 0.0003. Train Acc: 94.9825, Test loss: 0.0003. Test Acc: 94.9600. Time/epoch: 1.6868
saving best checkpoint at epoch: 60, Acc: 94.96
saving best checkpoint at epoch: 63, Acc: 95.0
saving best checkpoint at epoch: 65, Acc: 95.02
saving best checkpoint at epoch: 69, Acc: 95.1
EPOCH 70. Progress: 70.0%.
Train loss: 0.0002. Train Acc: 95.1475, Test loss: 0.0003. Test Acc: 95.0100. Time/epoch: 1.5420
saving best checkpoint at epoch: 72, Acc: 95.12
saving best checkpoint at epoch: 73, Acc: 95.14
saving best checkpoint at epoch: 74, Acc: 95.33
EPOCH 80. Progress: 80.0%.
Train loss: 0.0002. Train Acc: 95.4825, Test loss: 0.0002. Test Acc: 95.2300. Time/epoch: 1.6870
saving best checkpoint at epoch: 82, Acc: 95.46
saving best checkpoint at epoch: 86, Acc: 95.48
EPOCH 90. Progress: 90.0%.
Train loss: 0.0002. Train Acc: 95.7200, Test loss: 0.0002. Test Acc: 95.3800. Time/epoch: 1.5716
saving best checkpoint at epoch: 93, Acc: 95.5
saving best checkpoint at epoch: 96, Acc: 95.54
saving best checkpoint at epoch: 97, Acc: 95.56
saving best checkpoint at epoch: 98, Acc: 95.57
saving best checkpoint at epoch: 99, Acc: 95.59
EPOCH 100. Progress: 100.0%.
Train loss: 0.0002. Train Acc: 95.9875, Test loss: 0.0002. Test Acc: 95.6400. Time/epoch: 1.5398
saving best checkpoint at epoch: 100, Acc: 95.64
Run history:
Accuracy/train | ▁▅▇▇▇▇▇▇▇▇▇▇████████████████████████████ |
Accuracy/val | ▁▅▇▇▇▇▇▇▇▇██████████████████████████████ |
Loss/train | █▄▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▄▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 95.9875 |
Accuracy/val | 95.64 |
Loss/train | 0.00021 |
Loss/val | 0.00023 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_104133-11gt3k3i/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: cq3layly with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 1e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_104453-cq3layly
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0025. Train Acc: 59.3275, Test loss: 0.0026. Test Acc: 59.3100. Time/epoch: 1.5675
saving best checkpoint at epoch: 0, Acc: 59.31
saving best checkpoint at epoch: 1, Acc: 64.63
saving best checkpoint at epoch: 2, Acc: 80.01
saving best checkpoint at epoch: 3, Acc: 85.77
saving best checkpoint at epoch: 4, Acc: 89.11
saving best checkpoint at epoch: 5, Acc: 89.63
saving best checkpoint at epoch: 7, Acc: 90.2
saving best checkpoint at epoch: 8, Acc: 90.61
saving best checkpoint at epoch: 9, Acc: 90.74
EPOCH 10. Progress: 10.0%.
Train loss: 0.0004. Train Acc: 90.9175, Test loss: 0.0005. Test Acc: 90.9200. Time/epoch: 1.6891
saving best checkpoint at epoch: 10, Acc: 90.92
saving best checkpoint at epoch: 11, Acc: 91.05
saving best checkpoint at epoch: 12, Acc: 91.23
saving best checkpoint at epoch: 13, Acc: 91.3
saving best checkpoint at epoch: 14, Acc: 91.54
saving best checkpoint at epoch: 15, Acc: 91.64
saving best checkpoint at epoch: 16, Acc: 91.76
saving best checkpoint at epoch: 17, Acc: 91.9
saving best checkpoint at epoch: 18, Acc: 92.03
saving best checkpoint at epoch: 19, Acc: 92.17
EPOCH 20. Progress: 20.0%.
Train loss: 0.0004. Train Acc: 92.3400, Test loss: 0.0004. Test Acc: 92.2800. Time/epoch: 1.5481
saving best checkpoint at epoch: 20, Acc: 92.28
saving best checkpoint at epoch: 21, Acc: 92.44
saving best checkpoint at epoch: 22, Acc: 92.48
saving best checkpoint at epoch: 23, Acc: 92.68
saving best checkpoint at epoch: 24, Acc: 92.73
saving best checkpoint at epoch: 25, Acc: 92.83
saving best checkpoint at epoch: 26, Acc: 92.89
saving best checkpoint at epoch: 27, Acc: 93.03
saving best checkpoint at epoch: 28, Acc: 93.07
saving best checkpoint at epoch: 29, Acc: 93.15
EPOCH 30. Progress: 30.0%.
Train loss: 0.0003. Train Acc: 93.1200, Test loss: 0.0003. Test Acc: 93.2200. Time/epoch: 1.6815
saving best checkpoint at epoch: 30, Acc: 93.22
saving best checkpoint at epoch: 31, Acc: 93.31
saving best checkpoint at epoch: 33, Acc: 93.33
saving best checkpoint at epoch: 34, Acc: 93.45
saving best checkpoint at epoch: 35, Acc: 93.48
saving best checkpoint at epoch: 36, Acc: 93.58
saving best checkpoint at epoch: 37, Acc: 93.6
saving best checkpoint at epoch: 39, Acc: 93.64
EPOCH 40. Progress: 40.0%.
Train loss: 0.0003. Train Acc: 93.7725, Test loss: 0.0003. Test Acc: 93.8000. Time/epoch: 1.5409
saving best checkpoint at epoch: 40, Acc: 93.8
saving best checkpoint at epoch: 42, Acc: 93.83
saving best checkpoint at epoch: 44, Acc: 93.9
saving best checkpoint at epoch: 46, Acc: 94.0
saving best checkpoint at epoch: 48, Acc: 94.07
saving best checkpoint at epoch: 49, Acc: 94.11
EPOCH 50. Progress: 50.0%.
Train loss: 0.0003. Train Acc: 94.0275, Test loss: 0.0003. Test Acc: 94.0700. Time/epoch: 1.7101
saving best checkpoint at epoch: 52, Acc: 94.34
saving best checkpoint at epoch: 55, Acc: 94.35
saving best checkpoint at epoch: 56, Acc: 94.43
saving best checkpoint at epoch: 57, Acc: 94.49
EPOCH 60. Progress: 60.0%.
Train loss: 0.0003. Train Acc: 94.5300, Test loss: 0.0003. Test Acc: 94.4400. Time/epoch: 1.5592
saving best checkpoint at epoch: 63, Acc: 94.55
saving best checkpoint at epoch: 64, Acc: 94.61
saving best checkpoint at epoch: 65, Acc: 94.7
saving best checkpoint at epoch: 66, Acc: 94.76
saving best checkpoint at epoch: 68, Acc: 94.84
saving best checkpoint at epoch: 69, Acc: 94.94
EPOCH 70. Progress: 70.0%.
Train loss: 0.0003. Train Acc: 95.0575, Test loss: 0.0003. Test Acc: 94.8500. Time/epoch: 1.5495
saving best checkpoint at epoch: 78, Acc: 94.99
saving best checkpoint at epoch: 79, Acc: 95.05
EPOCH 80. Progress: 80.0%.
Train loss: 0.0002. Train Acc: 95.3800, Test loss: 0.0003. Test Acc: 95.0700. Time/epoch: 1.5475
saving best checkpoint at epoch: 80, Acc: 95.07
saving best checkpoint at epoch: 81, Acc: 95.14
saving best checkpoint at epoch: 83, Acc: 95.17
saving best checkpoint at epoch: 85, Acc: 95.2
saving best checkpoint at epoch: 88, Acc: 95.28
EPOCH 90. Progress: 90.0%.
Train loss: 0.0002. Train Acc: 95.6900, Test loss: 0.0002. Test Acc: 95.3800. Time/epoch: 1.6793
saving best checkpoint at epoch: 90, Acc: 95.38
saving best checkpoint at epoch: 92, Acc: 95.44
saving best checkpoint at epoch: 95, Acc: 95.48
saving best checkpoint at epoch: 98, Acc: 95.59
EPOCH 100. Progress: 100.0%.
Train loss: 0.0002. Train Acc: 95.9650, Test loss: 0.0002. Test Acc: 95.5900. Time/epoch: 1.5405
Run history:
Accuracy/train | ▁▅▇▇▇▇▇▇▇▇▇▇▇▇██████████████████████████ |
Accuracy/val | ▁▅▇▇▇▇▇▇▇▇▇█████████████████████████████ |
Loss/train | █▅▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▅▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 95.965 |
Accuracy/val | 95.59 |
Loss/train | 0.00022 |
Loss/val | 0.00023 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_104453-cq3layly/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: ep1a94tg with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 1e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_104759-ep1a94tg
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0028. Train Acc: 50.1925, Test loss: 0.0028. Test Acc: 50.3700. Time/epoch: 1.5582
saving best checkpoint at epoch: 0, Acc: 50.37
saving best checkpoint at epoch: 1, Acc: 70.44
saving best checkpoint at epoch: 2, Acc: 74.06
saving best checkpoint at epoch: 3, Acc: 80.47
saving best checkpoint at epoch: 4, Acc: 86.49
saving best checkpoint at epoch: 5, Acc: 88.17
saving best checkpoint at epoch: 6, Acc: 89.03
saving best checkpoint at epoch: 7, Acc: 89.3
saving best checkpoint at epoch: 8, Acc: 89.58
saving best checkpoint at epoch: 9, Acc: 89.87
EPOCH 10. Progress: 10.0%.
Train loss: 0.0004. Train Acc: 90.4275, Test loss: 0.0005. Test Acc: 90.0600. Time/epoch: 1.7016
saving best checkpoint at epoch: 10, Acc: 90.06
saving best checkpoint at epoch: 11, Acc: 90.25
saving best checkpoint at epoch: 12, Acc: 90.35
saving best checkpoint at epoch: 13, Acc: 90.62
saving best checkpoint at epoch: 14, Acc: 90.79
saving best checkpoint at epoch: 15, Acc: 90.96
saving best checkpoint at epoch: 16, Acc: 91.23
saving best checkpoint at epoch: 17, Acc: 91.31
saving best checkpoint at epoch: 18, Acc: 91.44
saving best checkpoint at epoch: 19, Acc: 91.65
EPOCH 20. Progress: 20.0%.
Train loss: 0.0004. Train Acc: 91.9925, Test loss: 0.0004. Test Acc: 91.7700. Time/epoch: 1.5473
saving best checkpoint at epoch: 20, Acc: 91.77
saving best checkpoint at epoch: 21, Acc: 91.86
saving best checkpoint at epoch: 22, Acc: 92.04
saving best checkpoint at epoch: 23, Acc: 92.25
saving best checkpoint at epoch: 24, Acc: 92.37
saving best checkpoint at epoch: 26, Acc: 92.74
saving best checkpoint at epoch: 29, Acc: 92.91
EPOCH 30. Progress: 30.0%.
Train loss: 0.0003. Train Acc: 93.0325, Test loss: 0.0003. Test Acc: 92.9700. Time/epoch: 1.6872
saving best checkpoint at epoch: 30, Acc: 92.97
saving best checkpoint at epoch: 31, Acc: 93.07
saving best checkpoint at epoch: 34, Acc: 93.26
saving best checkpoint at epoch: 36, Acc: 93.32
saving best checkpoint at epoch: 37, Acc: 93.38
saving best checkpoint at epoch: 38, Acc: 93.48
EPOCH 40. Progress: 40.0%.
Train loss: 0.0003. Train Acc: 93.5275, Test loss: 0.0003. Test Acc: 93.5600. Time/epoch: 1.5338
saving best checkpoint at epoch: 40, Acc: 93.56
saving best checkpoint at epoch: 43, Acc: 93.67
saving best checkpoint at epoch: 44, Acc: 93.71
saving best checkpoint at epoch: 45, Acc: 93.79
saving best checkpoint at epoch: 48, Acc: 93.89
EPOCH 50. Progress: 50.0%.
Train loss: 0.0003. Train Acc: 93.8750, Test loss: 0.0003. Test Acc: 93.9000. Time/epoch: 1.7060
saving best checkpoint at epoch: 50, Acc: 93.9
saving best checkpoint at epoch: 51, Acc: 93.99
saving best checkpoint at epoch: 52, Acc: 94.01
saving best checkpoint at epoch: 53, Acc: 94.07
saving best checkpoint at epoch: 54, Acc: 94.13
saving best checkpoint at epoch: 55, Acc: 94.16
saving best checkpoint at epoch: 57, Acc: 94.17
EPOCH 60. Progress: 60.0%.
Train loss: 0.0003. Train Acc: 94.3050, Test loss: 0.0003. Test Acc: 94.2600. Time/epoch: 1.5478
saving best checkpoint at epoch: 60, Acc: 94.26
saving best checkpoint at epoch: 61, Acc: 94.3
saving best checkpoint at epoch: 62, Acc: 94.31
saving best checkpoint at epoch: 63, Acc: 94.38
saving best checkpoint at epoch: 65, Acc: 94.44
saving best checkpoint at epoch: 66, Acc: 94.47
saving best checkpoint at epoch: 67, Acc: 94.57
EPOCH 70. Progress: 70.0%.
Train loss: 0.0003. Train Acc: 94.7000, Test loss: 0.0003. Test Acc: 94.5800. Time/epoch: 1.5463
saving best checkpoint at epoch: 70, Acc: 94.58
saving best checkpoint at epoch: 71, Acc: 94.64
saving best checkpoint at epoch: 73, Acc: 94.77
saving best checkpoint at epoch: 75, Acc: 94.9
saving best checkpoint at epoch: 77, Acc: 94.93
saving best checkpoint at epoch: 78, Acc: 94.95
EPOCH 80. Progress: 80.0%.
Train loss: 0.0002. Train Acc: 95.0325, Test loss: 0.0003. Test Acc: 94.8800. Time/epoch: 1.5405
saving best checkpoint at epoch: 81, Acc: 95.02
saving best checkpoint at epoch: 82, Acc: 95.04
saving best checkpoint at epoch: 84, Acc: 95.07
saving best checkpoint at epoch: 87, Acc: 95.28
EPOCH 90. Progress: 90.0%.
Train loss: 0.0002. Train Acc: 95.3325, Test loss: 0.0002. Test Acc: 95.2800. Time/epoch: 1.6971
saving best checkpoint at epoch: 92, Acc: 95.36
saving best checkpoint at epoch: 93, Acc: 95.41
saving best checkpoint at epoch: 94, Acc: 95.44
saving best checkpoint at epoch: 98, Acc: 95.5
EPOCH 100. Progress: 100.0%.
Train loss: 0.0002. Train Acc: 95.6425, Test loss: 0.0002. Test Acc: 95.4200. Time/epoch: 1.5519
Run history:
Accuracy/train | ▁▅▇▇▇▇▇▇▇▇██████████████████████████████ |
Accuracy/val | ▁▅▇▇▇▇▇▇▇███████████████████████████████ |
Loss/train | █▅▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▅▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 95.6425 |
Accuracy/val | 95.42 |
Loss/train | 0.00022 |
Loss/val | 0.00023 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_104759-ep1a94tg/logs
wandb: Agent Starting Run: zabuo6zp with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 1e-05
wandb: optimizer: adam
wandb: weight_decay: 0.005
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_105058-zabuo6zp
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0028. Train Acc: 44.7750, Test loss: 0.0029. Test Acc: 45.3100. Time/epoch: 1.8260
saving best checkpoint at epoch: 0, Acc: 45.31
saving best checkpoint at epoch: 1, Acc: 75.0
saving best checkpoint at epoch: 2, Acc: 77.6
saving best checkpoint at epoch: 3, Acc: 79.6
saving best checkpoint at epoch: 4, Acc: 81.35
saving best checkpoint at epoch: 5, Acc: 83.25
saving best checkpoint at epoch: 6, Acc: 84.95
saving best checkpoint at epoch: 7, Acc: 86.6
saving best checkpoint at epoch: 8, Acc: 87.62
saving best checkpoint at epoch: 9, Acc: 87.87
EPOCH 10. Progress: 10.0%.
Train loss: 0.0005. Train Acc: 88.7275, Test loss: 0.0006. Test Acc: 88.6400. Time/epoch: 1.6862
saving best checkpoint at epoch: 10, Acc: 88.64
saving best checkpoint at epoch: 11, Acc: 89.03
saving best checkpoint at epoch: 12, Acc: 89.43
saving best checkpoint at epoch: 13, Acc: 89.86
saving best checkpoint at epoch: 14, Acc: 90.1
saving best checkpoint at epoch: 15, Acc: 90.42
saving best checkpoint at epoch: 16, Acc: 90.83
saving best checkpoint at epoch: 17, Acc: 91.12
saving best checkpoint at epoch: 18, Acc: 91.49
saving best checkpoint at epoch: 19, Acc: 91.58
EPOCH 20. Progress: 20.0%.
Train loss: 0.0004. Train Acc: 92.0600, Test loss: 0.0004. Test Acc: 91.8800. Time/epoch: 1.5467
saving best checkpoint at epoch: 20, Acc: 91.88
saving best checkpoint at epoch: 21, Acc: 92.08
saving best checkpoint at epoch: 22, Acc: 92.3
saving best checkpoint at epoch: 23, Acc: 92.59
saving best checkpoint at epoch: 24, Acc: 92.62
saving best checkpoint at epoch: 25, Acc: 93.03
saving best checkpoint at epoch: 26, Acc: 93.19
saving best checkpoint at epoch: 27, Acc: 93.3
saving best checkpoint at epoch: 28, Acc: 93.37
saving best checkpoint at epoch: 29, Acc: 93.62
EPOCH 30. Progress: 30.0%.
Train loss: 0.0003. Train Acc: 93.6075, Test loss: 0.0003. Test Acc: 93.8000. Time/epoch: 1.6839
saving best checkpoint at epoch: 30, Acc: 93.8
saving best checkpoint at epoch: 31, Acc: 94.12
saving best checkpoint at epoch: 32, Acc: 94.21
saving best checkpoint at epoch: 34, Acc: 94.28
saving best checkpoint at epoch: 36, Acc: 94.45
saving best checkpoint at epoch: 37, Acc: 94.58
EPOCH 40. Progress: 40.0%.
Train loss: 0.0003. Train Acc: 94.4975, Test loss: 0.0003. Test Acc: 94.3800. Time/epoch: 1.5375
saving best checkpoint at epoch: 41, Acc: 94.82
saving best checkpoint at epoch: 44, Acc: 94.83
saving best checkpoint at epoch: 45, Acc: 94.89
saving best checkpoint at epoch: 47, Acc: 94.91
EPOCH 50. Progress: 50.0%.
Train loss: 0.0003. Train Acc: 95.0825, Test loss: 0.0003. Test Acc: 94.9600. Time/epoch: 1.7034
saving best checkpoint at epoch: 50, Acc: 94.96
saving best checkpoint at epoch: 51, Acc: 95.05
saving best checkpoint at epoch: 52, Acc: 95.07
saving best checkpoint at epoch: 54, Acc: 95.14
saving best checkpoint at epoch: 55, Acc: 95.2
saving best checkpoint at epoch: 57, Acc: 95.23
EPOCH 60. Progress: 60.0%.
Train loss: 0.0002. Train Acc: 95.2950, Test loss: 0.0003. Test Acc: 95.2600. Time/epoch: 1.5483
saving best checkpoint at epoch: 60, Acc: 95.26
saving best checkpoint at epoch: 61, Acc: 95.29
saving best checkpoint at epoch: 64, Acc: 95.39
saving best checkpoint at epoch: 69, Acc: 95.41
EPOCH 70. Progress: 70.0%.
Train loss: 0.0002. Train Acc: 95.5300, Test loss: 0.0003. Test Acc: 95.3400. Time/epoch: 1.5433
saving best checkpoint at epoch: 74, Acc: 95.49
saving best checkpoint at epoch: 75, Acc: 95.53
saving best checkpoint at epoch: 76, Acc: 95.67
EPOCH 80. Progress: 80.0%.
Train loss: 0.0002. Train Acc: 95.6825, Test loss: 0.0002. Test Acc: 95.5800. Time/epoch: 1.5427
saving best checkpoint at epoch: 86, Acc: 95.71
EPOCH 90. Progress: 90.0%.
Train loss: 0.0002. Train Acc: 95.8800, Test loss: 0.0002. Test Acc: 95.7200. Time/epoch: 1.5577
saving best checkpoint at epoch: 90, Acc: 95.72
saving best checkpoint at epoch: 93, Acc: 95.77
saving best checkpoint at epoch: 96, Acc: 95.84
saving best checkpoint at epoch: 98, Acc: 95.87
EPOCH 100. Progress: 100.0%.
Train loss: 0.0002. Train Acc: 96.0625, Test loss: 0.0002. Test Acc: 95.8400. Time/epoch: 1.6853
Run history:
Accuracy/train | ▁▆▆▇▇▇▇▇▇███████████████████████████████ |
Accuracy/val | ▁▅▆▇▇▇▇▇▇███████████████████████████████ |
Loss/train | █▄▃▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▄▃▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 96.0625 |
Accuracy/val | 95.84 |
Loss/train | 0.00021 |
Loss/val | 0.00023 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_105058-zabuo6zp/logs
wandb: Agent Starting Run: 8zg3wr9b with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 3e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_105357-8zg3wr9b
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0023. Train Acc: 62.2825, Test loss: 0.0023. Test Acc: 62.3800. Time/epoch: 1.6092
saving best checkpoint at epoch: 0, Acc: 62.38
saving best checkpoint at epoch: 2, Acc: 70.38
saving best checkpoint at epoch: 3, Acc: 83.82
saving best checkpoint at epoch: 4, Acc: 86.94
saving best checkpoint at epoch: 5, Acc: 88.81
saving best checkpoint at epoch: 6, Acc: 89.3
saving best checkpoint at epoch: 7, Acc: 90.12
saving best checkpoint at epoch: 8, Acc: 90.95
saving best checkpoint at epoch: 9, Acc: 91.67
EPOCH 10. Progress: 10.0%.
Train loss: 0.0004. Train Acc: 91.3325, Test loss: 0.0004. Test Acc: 91.4200. Time/epoch: 1.5628
saving best checkpoint at epoch: 11, Acc: 92.36
saving best checkpoint at epoch: 12, Acc: 92.74
saving best checkpoint at epoch: 13, Acc: 93.12
saving best checkpoint at epoch: 15, Acc: 93.58
saving best checkpoint at epoch: 17, Acc: 93.83
saving best checkpoint at epoch: 18, Acc: 93.97
saving best checkpoint at epoch: 19, Acc: 94.14
EPOCH 20. Progress: 20.0%.
Train loss: 0.0003. Train Acc: 93.9300, Test loss: 0.0003. Test Acc: 94.0000. Time/epoch: 1.6972
saving best checkpoint at epoch: 21, Acc: 94.61
saving best checkpoint at epoch: 23, Acc: 94.62
saving best checkpoint at epoch: 24, Acc: 94.72
saving best checkpoint at epoch: 25, Acc: 95.17
saving best checkpoint at epoch: 28, Acc: 95.23
EPOCH 30. Progress: 30.0%.
Train loss: 0.0002. Train Acc: 95.2850, Test loss: 0.0003. Test Acc: 95.2100. Time/epoch: 1.5434
saving best checkpoint at epoch: 32, Acc: 95.4
saving best checkpoint at epoch: 33, Acc: 95.47
saving best checkpoint at epoch: 34, Acc: 95.51
saving best checkpoint at epoch: 37, Acc: 95.52
saving best checkpoint at epoch: 39, Acc: 95.62
EPOCH 40. Progress: 40.0%.
Train loss: 0.0002. Train Acc: 95.5825, Test loss: 0.0003. Test Acc: 95.4300. Time/epoch: 1.6880
saving best checkpoint at epoch: 44, Acc: 95.72
EPOCH 50. Progress: 50.0%.
Train loss: 0.0002. Train Acc: 95.7925, Test loss: 0.0002. Test Acc: 95.5900. Time/epoch: 1.5607
saving best checkpoint at epoch: 51, Acc: 95.73
saving best checkpoint at epoch: 53, Acc: 95.87
saving best checkpoint at epoch: 56, Acc: 96.05
saving best checkpoint at epoch: 59, Acc: 96.09
EPOCH 60. Progress: 60.0%.
Train loss: 0.0002. Train Acc: 96.2175, Test loss: 0.0002. Test Acc: 95.9000. Time/epoch: 1.6921
EPOCH 70. Progress: 70.0%.
Train loss: 0.0002. Train Acc: 96.3975, Test loss: 0.0002. Test Acc: 96.1100. Time/epoch: 1.5492
saving best checkpoint at epoch: 70, Acc: 96.11
saving best checkpoint at epoch: 74, Acc: 96.17
saving best checkpoint at epoch: 76, Acc: 96.24
saving best checkpoint at epoch: 78, Acc: 96.25
EPOCH 80. Progress: 80.0%.
Train loss: 0.0002. Train Acc: 96.5800, Test loss: 0.0002. Test Acc: 96.2300. Time/epoch: 1.5520
saving best checkpoint at epoch: 81, Acc: 96.27
saving best checkpoint at epoch: 83, Acc: 96.29
saving best checkpoint at epoch: 87, Acc: 96.3
saving best checkpoint at epoch: 89, Acc: 96.31
EPOCH 90. Progress: 90.0%.
Train loss: 0.0002. Train Acc: 96.6350, Test loss: 0.0002. Test Acc: 96.4500. Time/epoch: 1.7028
saving best checkpoint at epoch: 90, Acc: 96.45
saving best checkpoint at epoch: 95, Acc: 96.56
saving best checkpoint at epoch: 96, Acc: 96.62
EPOCH 100. Progress: 100.0%.
Train loss: 0.0002. Train Acc: 96.8675, Test loss: 0.0002. Test Acc: 96.4800. Time/epoch: 1.5496
Run history:
Accuracy/train | ▁▃▆▇▇▇▇▇▇███████████████████████████████ |
Accuracy/val | ▁▃▆▇▇▇▇▇▇███████████████████████████████ |
Loss/train | █▅▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▅▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 96.8675 |
Accuracy/val | 96.48 |
Loss/train | 0.00016 |
Loss/val | 0.00019 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_105357-8zg3wr9b/logs
wandb: Sweep Agent: Waiting for job.
500 response executing GraphQL.
{"errors":[{"message":"Post \"http://anaconda2.default.svc.cluster.local/search\": read tcp 10.52.63.6:46108-\u003e10.55.247.53:80: read: connection reset by peer","path":["agentHeartbeat"]}],"data":{"agentHeartbeat":null}}
wandb: ERROR Error while calling W&B API: Post "http://anaconda2.default.svc.cluster.local/search": read tcp 10.52.63.6:46108->10.55.247.53:80: read: connection reset by peer (<Response [500]>)
wandb: Job received.
wandb: Agent Starting Run: 6hlqcbb7 with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 1e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_105722-6hlqcbb7
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0032. Train Acc: 27.5000, Test loss: 0.0032. Test Acc: 27.6300. Time/epoch: 1.7136
saving best checkpoint at epoch: 0, Acc: 27.63
saving best checkpoint at epoch: 1, Acc: 60.87
saving best checkpoint at epoch: 2, Acc: 63.82
saving best checkpoint at epoch: 3, Acc: 68.47
saving best checkpoint at epoch: 4, Acc: 73.94
saving best checkpoint at epoch: 5, Acc: 79.19
saving best checkpoint at epoch: 6, Acc: 83.79
saving best checkpoint at epoch: 7, Acc: 84.81
saving best checkpoint at epoch: 8, Acc: 85.6
saving best checkpoint at epoch: 9, Acc: 85.86
EPOCH 10. Progress: 10.0%.
Train loss: 0.0007. Train Acc: 86.3950, Test loss: 0.0007. Test Acc: 86.1800. Time/epoch: 1.6959
saving best checkpoint at epoch: 10, Acc: 86.18
saving best checkpoint at epoch: 11, Acc: 86.62
saving best checkpoint at epoch: 12, Acc: 86.94
saving best checkpoint at epoch: 13, Acc: 87.35
saving best checkpoint at epoch: 15, Acc: 87.73
saving best checkpoint at epoch: 16, Acc: 88.01
saving best checkpoint at epoch: 17, Acc: 88.36
saving best checkpoint at epoch: 18, Acc: 88.46
saving best checkpoint at epoch: 19, Acc: 88.75
EPOCH 20. Progress: 20.0%.
Train loss: 0.0005. Train Acc: 88.9800, Test loss: 0.0005. Test Acc: 89.1200. Time/epoch: 1.5546
saving best checkpoint at epoch: 20, Acc: 89.12
saving best checkpoint at epoch: 21, Acc: 89.39
saving best checkpoint at epoch: 22, Acc: 89.59
saving best checkpoint at epoch: 23, Acc: 89.91
saving best checkpoint at epoch: 24, Acc: 90.04
saving best checkpoint at epoch: 25, Acc: 90.39
saving best checkpoint at epoch: 26, Acc: 90.57
saving best checkpoint at epoch: 27, Acc: 91.01
saving best checkpoint at epoch: 28, Acc: 91.19
saving best checkpoint at epoch: 29, Acc: 91.36
EPOCH 30. Progress: 30.0%.
Train loss: 0.0004. Train Acc: 91.4800, Test loss: 0.0004. Test Acc: 91.5800. Time/epoch: 1.6980
saving best checkpoint at epoch: 30, Acc: 91.58
saving best checkpoint at epoch: 32, Acc: 91.65
saving best checkpoint at epoch: 33, Acc: 91.88
saving best checkpoint at epoch: 34, Acc: 92.0
saving best checkpoint at epoch: 35, Acc: 92.03
saving best checkpoint at epoch: 36, Acc: 92.09
saving best checkpoint at epoch: 37, Acc: 92.27
saving best checkpoint at epoch: 38, Acc: 92.39
EPOCH 40. Progress: 40.0%.
Train loss: 0.0003. Train Acc: 92.7150, Test loss: 0.0004. Test Acc: 92.5400. Time/epoch: 1.5434
saving best checkpoint at epoch: 40, Acc: 92.54
saving best checkpoint at epoch: 41, Acc: 92.6
saving best checkpoint at epoch: 42, Acc: 92.7
saving best checkpoint at epoch: 43, Acc: 92.91
saving best checkpoint at epoch: 45, Acc: 93.04
saving best checkpoint at epoch: 47, Acc: 93.1
saving best checkpoint at epoch: 49, Acc: 93.11
EPOCH 50. Progress: 50.0%.
Train loss: 0.0003. Train Acc: 93.3850, Test loss: 0.0003. Test Acc: 93.3200. Time/epoch: 1.7006
saving best checkpoint at epoch: 50, Acc: 93.32
saving best checkpoint at epoch: 53, Acc: 93.51
saving best checkpoint at epoch: 55, Acc: 93.52
saving best checkpoint at epoch: 56, Acc: 93.59
saving best checkpoint at epoch: 59, Acc: 93.82
EPOCH 60. Progress: 60.0%.
Train loss: 0.0003. Train Acc: 93.8100, Test loss: 0.0003. Test Acc: 93.8400. Time/epoch: 1.5452
saving best checkpoint at epoch: 60, Acc: 93.84
saving best checkpoint at epoch: 63, Acc: 93.9
saving best checkpoint at epoch: 64, Acc: 94.04
EPOCH 70. Progress: 70.0%.
Train loss: 0.0003. Train Acc: 94.1000, Test loss: 0.0003. Test Acc: 94.0500. Time/epoch: 1.5450
saving best checkpoint at epoch: 70, Acc: 94.05
saving best checkpoint at epoch: 72, Acc: 94.14
saving best checkpoint at epoch: 73, Acc: 94.25
saving best checkpoint at epoch: 78, Acc: 94.34
saving best checkpoint at epoch: 79, Acc: 94.47
EPOCH 80. Progress: 80.0%.
Train loss: 0.0003. Train Acc: 94.3850, Test loss: 0.0003. Test Acc: 94.3700. Time/epoch: 1.5437
saving best checkpoint at epoch: 85, Acc: 94.5
saving best checkpoint at epoch: 88, Acc: 94.54
EPOCH 90. Progress: 90.0%.
Train loss: 0.0003. Train Acc: 94.5150, Test loss: 0.0003. Test Acc: 94.3900. Time/epoch: 1.6996
saving best checkpoint at epoch: 94, Acc: 94.58
saving best checkpoint at epoch: 95, Acc: 94.61
saving best checkpoint at epoch: 98, Acc: 94.77
EPOCH 100. Progress: 100.0%.
Train loss: 0.0003. Train Acc: 94.7225, Test loss: 0.0003. Test Acc: 94.5100. Time/epoch: 1.5517
Run history:
Accuracy/train | ▁▅▆▇▇▇▇▇▇███████████████████████████████ |
Accuracy/val | ▁▅▆▇▇▇▇▇▇███████████████████████████████ |
Loss/train | █▅▃▃▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▅▃▃▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 94.7225 |
Accuracy/val | 94.51 |
Loss/train | 0.00025 |
Loss/val | 0.00026 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_105722-6hlqcbb7/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: 72b50lmo with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 1e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_110031-72b50lmo
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0028. Train Acc: 54.5275, Test loss: 0.0028. Test Acc: 54.8700. Time/epoch: 1.7153
saving best checkpoint at epoch: 0, Acc: 54.87
saving best checkpoint at epoch: 1, Acc: 72.12
saving best checkpoint at epoch: 2, Acc: 74.67
saving best checkpoint at epoch: 3, Acc: 78.22
saving best checkpoint at epoch: 4, Acc: 82.12
saving best checkpoint at epoch: 5, Acc: 83.41
saving best checkpoint at epoch: 6, Acc: 84.73
saving best checkpoint at epoch: 7, Acc: 85.61
saving best checkpoint at epoch: 8, Acc: 86.11
saving best checkpoint at epoch: 9, Acc: 86.31
EPOCH 10. Progress: 10.0%.
Train loss: 0.0006. Train Acc: 86.7925, Test loss: 0.0006. Test Acc: 86.7400. Time/epoch: 1.6951
saving best checkpoint at epoch: 10, Acc: 86.74
saving best checkpoint at epoch: 11, Acc: 86.83
saving best checkpoint at epoch: 12, Acc: 87.38
saving best checkpoint at epoch: 13, Acc: 87.71
saving best checkpoint at epoch: 14, Acc: 87.73
saving best checkpoint at epoch: 15, Acc: 88.21
saving best checkpoint at epoch: 17, Acc: 88.45
saving best checkpoint at epoch: 18, Acc: 88.54
saving best checkpoint at epoch: 19, Acc: 88.73
EPOCH 20. Progress: 20.0%.
Train loss: 0.0005. Train Acc: 89.1300, Test loss: 0.0005. Test Acc: 89.0500. Time/epoch: 1.5535
saving best checkpoint at epoch: 20, Acc: 89.05
saving best checkpoint at epoch: 21, Acc: 89.47
saving best checkpoint at epoch: 23, Acc: 89.76
saving best checkpoint at epoch: 24, Acc: 90.01
saving best checkpoint at epoch: 25, Acc: 90.09
saving best checkpoint at epoch: 26, Acc: 90.17
saving best checkpoint at epoch: 27, Acc: 90.3
saving best checkpoint at epoch: 28, Acc: 90.34
saving best checkpoint at epoch: 29, Acc: 90.55
EPOCH 30. Progress: 30.0%.
Train loss: 0.0004. Train Acc: 90.8850, Test loss: 0.0004. Test Acc: 90.7900. Time/epoch: 1.6866
saving best checkpoint at epoch: 30, Acc: 90.79
saving best checkpoint at epoch: 32, Acc: 90.93
saving best checkpoint at epoch: 33, Acc: 91.15
saving best checkpoint at epoch: 34, Acc: 91.37
saving best checkpoint at epoch: 35, Acc: 91.69
saving best checkpoint at epoch: 36, Acc: 91.78
saving best checkpoint at epoch: 37, Acc: 92.49
saving best checkpoint at epoch: 39, Acc: 92.89
EPOCH 40. Progress: 40.0%.
Train loss: 0.0003. Train Acc: 93.0525, Test loss: 0.0004. Test Acc: 93.2000. Time/epoch: 1.5409
saving best checkpoint at epoch: 40, Acc: 93.2
saving best checkpoint at epoch: 41, Acc: 93.42
saving best checkpoint at epoch: 42, Acc: 93.58
saving best checkpoint at epoch: 43, Acc: 93.75
saving best checkpoint at epoch: 44, Acc: 93.97
saving best checkpoint at epoch: 45, Acc: 94.19
saving best checkpoint at epoch: 48, Acc: 94.2
saving best checkpoint at epoch: 49, Acc: 94.28
EPOCH 50. Progress: 50.0%.
Train loss: 0.0003. Train Acc: 94.5975, Test loss: 0.0003. Test Acc: 94.4300. Time/epoch: 1.7161
saving best checkpoint at epoch: 50, Acc: 94.43
saving best checkpoint at epoch: 52, Acc: 94.5
saving best checkpoint at epoch: 53, Acc: 94.61
saving best checkpoint at epoch: 57, Acc: 94.75
saving best checkpoint at epoch: 58, Acc: 94.85
EPOCH 60. Progress: 60.0%.
Train loss: 0.0003. Train Acc: 95.0625, Test loss: 0.0003. Test Acc: 94.8000. Time/epoch: 1.5639
saving best checkpoint at epoch: 61, Acc: 94.87
saving best checkpoint at epoch: 63, Acc: 95.0
saving best checkpoint at epoch: 68, Acc: 95.04
EPOCH 70. Progress: 70.0%.
Train loss: 0.0002. Train Acc: 95.4000, Test loss: 0.0003. Test Acc: 95.1600. Time/epoch: 1.5486
saving best checkpoint at epoch: 70, Acc: 95.16
saving best checkpoint at epoch: 74, Acc: 95.22
saving best checkpoint at epoch: 78, Acc: 95.23
saving best checkpoint at epoch: 79, Acc: 95.32
EPOCH 80. Progress: 80.0%.
Train loss: 0.0002. Train Acc: 95.6475, Test loss: 0.0002. Test Acc: 95.3300. Time/epoch: 1.5561
saving best checkpoint at epoch: 80, Acc: 95.33
saving best checkpoint at epoch: 86, Acc: 95.39
saving best checkpoint at epoch: 87, Acc: 95.42
saving best checkpoint at epoch: 88, Acc: 95.48
EPOCH 90. Progress: 90.0%.
Train loss: 0.0002. Train Acc: 95.8350, Test loss: 0.0002. Test Acc: 95.5700. Time/epoch: 1.5726
saving best checkpoint at epoch: 90, Acc: 95.57
saving best checkpoint at epoch: 95, Acc: 95.67
saving best checkpoint at epoch: 99, Acc: 95.73
EPOCH 100. Progress: 100.0%.
Train loss: 0.0002. Train Acc: 96.0425, Test loss: 0.0002. Test Acc: 95.7000. Time/epoch: 1.6775
Run history:
Accuracy/train | ▁▄▆▆▆▇▇▇▇▇▇▇▇▇▇▇████████████████████████ |
Accuracy/val | ▁▄▆▆▆▇▇▇▇▇▇▇▇▇▇▇████████████████████████ |
Loss/train | █▅▃▂▂▂▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▅▃▂▂▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 96.0425 |
Accuracy/val | 95.7 |
Loss/train | 0.00021 |
Loss/val | 0.00023 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_110031-72b50lmo/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: 56vb1ox1 with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 3e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_110407-56vb1ox1
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0016. Train Acc: 73.7275, Test loss: 0.0016. Test Acc: 74.2200. Time/epoch: 1.6374
saving best checkpoint at epoch: 0, Acc: 74.22
saving best checkpoint at epoch: 1, Acc: 84.14
saving best checkpoint at epoch: 2, Acc: 87.77
saving best checkpoint at epoch: 3, Acc: 89.66
saving best checkpoint at epoch: 4, Acc: 91.03
saving best checkpoint at epoch: 5, Acc: 91.6
saving best checkpoint at epoch: 6, Acc: 91.96
saving best checkpoint at epoch: 7, Acc: 92.13
saving best checkpoint at epoch: 8, Acc: 92.63
saving best checkpoint at epoch: 9, Acc: 92.97
EPOCH 10. Progress: 10.0%.
Train loss: 0.0003. Train Acc: 92.9575, Test loss: 0.0004. Test Acc: 92.7800. Time/epoch: 1.6874
saving best checkpoint at epoch: 11, Acc: 93.12
saving best checkpoint at epoch: 12, Acc: 93.31
saving best checkpoint at epoch: 13, Acc: 93.4
saving best checkpoint at epoch: 14, Acc: 94.0
saving best checkpoint at epoch: 15, Acc: 94.02
saving best checkpoint at epoch: 16, Acc: 94.04
saving best checkpoint at epoch: 17, Acc: 94.39
saving best checkpoint at epoch: 19, Acc: 94.42
EPOCH 20. Progress: 20.0%.
Train loss: 0.0003. Train Acc: 94.7125, Test loss: 0.0003. Test Acc: 94.5600. Time/epoch: 1.5657
saving best checkpoint at epoch: 20, Acc: 94.56
saving best checkpoint at epoch: 22, Acc: 94.86
saving best checkpoint at epoch: 24, Acc: 95.07
saving best checkpoint at epoch: 25, Acc: 95.09
saving best checkpoint at epoch: 26, Acc: 95.21
saving best checkpoint at epoch: 29, Acc: 95.32
EPOCH 30. Progress: 30.0%.
Train loss: 0.0002. Train Acc: 95.3000, Test loss: 0.0003. Test Acc: 95.1800. Time/epoch: 1.6811
saving best checkpoint at epoch: 32, Acc: 95.52
saving best checkpoint at epoch: 35, Acc: 95.67
saving best checkpoint at epoch: 37, Acc: 95.86
EPOCH 40. Progress: 40.0%.
Train loss: 0.0002. Train Acc: 95.7575, Test loss: 0.0002. Test Acc: 95.8600. Time/epoch: 1.5371
saving best checkpoint at epoch: 41, Acc: 95.89
saving best checkpoint at epoch: 45, Acc: 95.98
saving best checkpoint at epoch: 49, Acc: 96.12
EPOCH 50. Progress: 50.0%.
Train loss: 0.0002. Train Acc: 96.2425, Test loss: 0.0002. Test Acc: 96.1500. Time/epoch: 1.7001
saving best checkpoint at epoch: 50, Acc: 96.15
saving best checkpoint at epoch: 59, Acc: 96.19
EPOCH 60. Progress: 60.0%.
Train loss: 0.0002. Train Acc: 96.2675, Test loss: 0.0002. Test Acc: 96.1100. Time/epoch: 1.5374
saving best checkpoint at epoch: 65, Acc: 96.26
saving best checkpoint at epoch: 66, Acc: 96.32
saving best checkpoint at epoch: 68, Acc: 96.41
EPOCH 70. Progress: 70.0%.
Train loss: 0.0002. Train Acc: 96.6325, Test loss: 0.0002. Test Acc: 96.4200. Time/epoch: 1.5444
saving best checkpoint at epoch: 70, Acc: 96.42
saving best checkpoint at epoch: 74, Acc: 96.52
EPOCH 80. Progress: 80.0%.
Train loss: 0.0002. Train Acc: 96.7250, Test loss: 0.0002. Test Acc: 96.6400. Time/epoch: 1.5400
saving best checkpoint at epoch: 80, Acc: 96.64
saving best checkpoint at epoch: 88, Acc: 96.72
saving best checkpoint at epoch: 89, Acc: 96.73
EPOCH 90. Progress: 90.0%.
Train loss: 0.0002. Train Acc: 96.8575, Test loss: 0.0002. Test Acc: 96.5500. Time/epoch: 1.5509
EPOCH 100. Progress: 100.0%.
Train loss: 0.0002. Train Acc: 96.8675, Test loss: 0.0002. Test Acc: 96.5500. Time/epoch: 1.7090
Run history:
Accuracy/train | ▁▅▆▇▇▇▇▇▇▇▇▇▇███████████████████████████ |
Accuracy/val | ▁▅▆▇▇▇▇▇▇▇▇▇█████▇██████████████████████ |
Loss/train | █▃▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▃▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 96.8675 |
Accuracy/val | 96.55 |
Loss/train | 0.00016 |
Loss/val | 0.00019 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_110407-56vb1ox1/logs
wandb: Agent Starting Run: fku8awut with config:
wandb: batch_size: 128
wandb: epochs: 100
wandb: learning_rate: 1e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_110707-fku8awut
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0067. Train Acc: 71.5550, Test loss: 0.0067. Test Acc: 71.4200. Time/epoch: 2.1993
saving best checkpoint at epoch: 0, Acc: 71.42
saving best checkpoint at epoch: 1, Acc: 82.43
saving best checkpoint at epoch: 2, Acc: 86.03
saving best checkpoint at epoch: 3, Acc: 87.63
saving best checkpoint at epoch: 4, Acc: 88.75
saving best checkpoint at epoch: 5, Acc: 89.82
saving best checkpoint at epoch: 6, Acc: 90.3
saving best checkpoint at epoch: 7, Acc: 91.4
saving best checkpoint at epoch: 8, Acc: 91.91
saving best checkpoint at epoch: 9, Acc: 92.25
EPOCH 10. Progress: 10.0%.
Train loss: 0.0015. Train Acc: 92.2325, Test loss: 0.0016. Test Acc: 92.0700. Time/epoch: 2.0358
saving best checkpoint at epoch: 11, Acc: 92.84
saving best checkpoint at epoch: 12, Acc: 93.05
saving best checkpoint at epoch: 13, Acc: 93.22
saving best checkpoint at epoch: 14, Acc: 93.49
saving best checkpoint at epoch: 16, Acc: 93.58
saving best checkpoint at epoch: 18, Acc: 93.93
saving best checkpoint at epoch: 19, Acc: 93.95
EPOCH 20. Progress: 20.0%.
Train loss: 0.0012. Train Acc: 94.3050, Test loss: 0.0012. Test Acc: 94.1700. Time/epoch: 2.1656
saving best checkpoint at epoch: 20, Acc: 94.17
saving best checkpoint at epoch: 21, Acc: 94.2
saving best checkpoint at epoch: 22, Acc: 94.49
saving best checkpoint at epoch: 26, Acc: 94.57
saving best checkpoint at epoch: 27, Acc: 94.66
saving best checkpoint at epoch: 28, Acc: 94.87
saving best checkpoint at epoch: 29, Acc: 94.91
EPOCH 30. Progress: 30.0%.
Train loss: 0.0010. Train Acc: 95.0800, Test loss: 0.0011. Test Acc: 94.9200. Time/epoch: 2.1659
saving best checkpoint at epoch: 30, Acc: 94.92
saving best checkpoint at epoch: 32, Acc: 95.09
saving best checkpoint at epoch: 35, Acc: 95.16
saving best checkpoint at epoch: 36, Acc: 95.25
saving best checkpoint at epoch: 37, Acc: 95.27
EPOCH 40. Progress: 40.0%.
Train loss: 0.0009. Train Acc: 95.4500, Test loss: 0.0010. Test Acc: 95.1800. Time/epoch: 2.1656
saving best checkpoint at epoch: 42, Acc: 95.33
saving best checkpoint at epoch: 44, Acc: 95.38
saving best checkpoint at epoch: 47, Acc: 95.53
EPOCH 50. Progress: 50.0%.
Train loss: 0.0009. Train Acc: 95.7500, Test loss: 0.0010. Test Acc: 95.5900. Time/epoch: 2.1695
saving best checkpoint at epoch: 50, Acc: 95.59
saving best checkpoint at epoch: 55, Acc: 95.63
saving best checkpoint at epoch: 56, Acc: 95.65
saving best checkpoint at epoch: 57, Acc: 95.66
EPOCH 60. Progress: 60.0%.
Train loss: 0.0008. Train Acc: 96.0200, Test loss: 0.0009. Test Acc: 95.7100. Time/epoch: 2.1954
saving best checkpoint at epoch: 60, Acc: 95.71
saving best checkpoint at epoch: 62, Acc: 95.77
saving best checkpoint at epoch: 67, Acc: 95.84
EPOCH 70. Progress: 70.0%.
Train loss: 0.0008. Train Acc: 96.1300, Test loss: 0.0009. Test Acc: 95.8700. Time/epoch: 2.1853
saving best checkpoint at epoch: 70, Acc: 95.87
saving best checkpoint at epoch: 72, Acc: 95.92
saving best checkpoint at epoch: 74, Acc: 95.98
EPOCH 80. Progress: 80.0%.
Train loss: 0.0008. Train Acc: 96.1700, Test loss: 0.0009. Test Acc: 95.8600. Time/epoch: 2.1745
saving best checkpoint at epoch: 83, Acc: 96.02
saving best checkpoint at epoch: 86, Acc: 96.2
EPOCH 90. Progress: 90.0%.
Train loss: 0.0007. Train Acc: 96.4350, Test loss: 0.0009. Test Acc: 96.0700. Time/epoch: 2.1752
saving best checkpoint at epoch: 96, Acc: 96.25
EPOCH 100. Progress: 100.0%.
Train loss: 0.0007. Train Acc: 96.4725, Test loss: 0.0008. Test Acc: 96.2000. Time/epoch: 2.1812
Run history:
Accuracy/train | ▁▅▆▇▇▇▇▇▇▇▇█████████████████████████████ |
Accuracy/val | ▁▅▆▇▇▇▇▇▇█▇█████████████████████████████ |
Loss/train | █▄▃▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▄▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 96.4725 |
Accuracy/val | 96.2 |
Loss/train | 0.00071 |
Loss/val | 0.00081 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_110707-fku8awut/logs
wandb: Agent Starting Run: hpywdqc7 with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 3e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_111101-hpywdqc7
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0013. Train Acc: 77.2050, Test loss: 0.0013. Test Acc: 77.8200. Time/epoch: 1.5673
saving best checkpoint at epoch: 0, Acc: 77.82
saving best checkpoint at epoch: 1, Acc: 86.93
saving best checkpoint at epoch: 2, Acc: 88.67
saving best checkpoint at epoch: 3, Acc: 90.39
saving best checkpoint at epoch: 4, Acc: 91.36
saving best checkpoint at epoch: 5, Acc: 91.42
saving best checkpoint at epoch: 6, Acc: 91.79
saving best checkpoint at epoch: 7, Acc: 91.83
saving best checkpoint at epoch: 8, Acc: 92.33
saving best checkpoint at epoch: 9, Acc: 92.68
EPOCH 10. Progress: 10.0%.
Train loss: 0.0003. Train Acc: 93.0575, Test loss: 0.0004. Test Acc: 92.8300. Time/epoch: 1.5820
saving best checkpoint at epoch: 10, Acc: 92.83
saving best checkpoint at epoch: 12, Acc: 93.12
saving best checkpoint at epoch: 13, Acc: 93.18
saving best checkpoint at epoch: 14, Acc: 93.23
saving best checkpoint at epoch: 15, Acc: 93.35
saving best checkpoint at epoch: 17, Acc: 93.43
saving best checkpoint at epoch: 18, Acc: 93.58
saving best checkpoint at epoch: 19, Acc: 93.72
EPOCH 20. Progress: 20.0%.
Train loss: 0.0003. Train Acc: 93.8725, Test loss: 0.0003. Test Acc: 93.6800. Time/epoch: 1.6931
saving best checkpoint at epoch: 21, Acc: 94.01
saving best checkpoint at epoch: 23, Acc: 94.21
saving best checkpoint at epoch: 24, Acc: 94.23
saving best checkpoint at epoch: 25, Acc: 94.32
saving best checkpoint at epoch: 26, Acc: 94.56
saving best checkpoint at epoch: 27, Acc: 94.6
saving best checkpoint at epoch: 28, Acc: 94.73
saving best checkpoint at epoch: 29, Acc: 94.75
EPOCH 30. Progress: 30.0%.
Train loss: 0.0002. Train Acc: 95.2750, Test loss: 0.0003. Test Acc: 94.8100. Time/epoch: 1.5527
saving best checkpoint at epoch: 30, Acc: 94.81
saving best checkpoint at epoch: 32, Acc: 95.16
saving best checkpoint at epoch: 34, Acc: 95.23
saving best checkpoint at epoch: 35, Acc: 95.27
saving best checkpoint at epoch: 37, Acc: 95.34
EPOCH 40. Progress: 40.0%.
Train loss: 0.0002. Train Acc: 95.7825, Test loss: 0.0002. Test Acc: 95.5100. Time/epoch: 1.6911
saving best checkpoint at epoch: 40, Acc: 95.51
saving best checkpoint at epoch: 43, Acc: 95.55
saving best checkpoint at epoch: 44, Acc: 95.66
saving best checkpoint at epoch: 48, Acc: 95.8
saving best checkpoint at epoch: 49, Acc: 95.82
EPOCH 50. Progress: 50.0%.
Train loss: 0.0002. Train Acc: 96.2400, Test loss: 0.0002. Test Acc: 95.7600. Time/epoch: 1.5508
saving best checkpoint at epoch: 51, Acc: 95.85
saving best checkpoint at epoch: 53, Acc: 95.92
saving best checkpoint at epoch: 57, Acc: 95.94
saving best checkpoint at epoch: 59, Acc: 96.08
EPOCH 60. Progress: 60.0%.
Train loss: 0.0002. Train Acc: 96.2475, Test loss: 0.0002. Test Acc: 95.7100. Time/epoch: 1.6845
saving best checkpoint at epoch: 62, Acc: 96.09
saving best checkpoint at epoch: 65, Acc: 96.12
saving best checkpoint at epoch: 67, Acc: 96.18
saving best checkpoint at epoch: 68, Acc: 96.28
EPOCH 70. Progress: 70.0%.
Train loss: 0.0002. Train Acc: 96.6050, Test loss: 0.0002. Test Acc: 96.2500. Time/epoch: 1.5486
saving best checkpoint at epoch: 71, Acc: 96.36
saving best checkpoint at epoch: 74, Acc: 96.41
saving best checkpoint at epoch: 77, Acc: 96.43
EPOCH 80. Progress: 80.0%.
Train loss: 0.0002. Train Acc: 96.8375, Test loss: 0.0002. Test Acc: 96.4100. Time/epoch: 1.5519
saving best checkpoint at epoch: 81, Acc: 96.52
saving best checkpoint at epoch: 85, Acc: 96.57
EPOCH 90. Progress: 90.0%.
Train loss: 0.0002. Train Acc: 97.0425, Test loss: 0.0002. Test Acc: 96.5200. Time/epoch: 1.5347
saving best checkpoint at epoch: 92, Acc: 96.58
saving best checkpoint at epoch: 96, Acc: 96.63
EPOCH 100. Progress: 100.0%.
Train loss: 0.0002. Train Acc: 97.0075, Test loss: 0.0002. Test Acc: 96.4200. Time/epoch: 1.5524
Run history:
Accuracy/train | ▁▅▆▆▇▇▇▇▇▇▇▇▇▇▇▇████████████████████████ |
Accuracy/val | ▁▅▆▆▇▇▇▇▇▇▇▇▇▇█▇████████████████████████ |
Loss/train | █▄▃▂▂▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▃▂▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 97.0075 |
Accuracy/val | 96.42 |
Loss/train | 0.00016 |
Loss/val | 0.00019 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_111101-hpywdqc7/logs
wandb: Agent Starting Run: 7y29dvnq with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 1e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_111359-7y29dvnq
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0028. Train Acc: 52.1700, Test loss: 0.0028. Test Acc: 52.3300. Time/epoch: 1.7185
saving best checkpoint at epoch: 0, Acc: 52.33
saving best checkpoint at epoch: 1, Acc: 73.3
saving best checkpoint at epoch: 2, Acc: 79.67
saving best checkpoint at epoch: 3, Acc: 82.34
saving best checkpoint at epoch: 4, Acc: 84.09
saving best checkpoint at epoch: 5, Acc: 85.16
saving best checkpoint at epoch: 6, Acc: 86.35
saving best checkpoint at epoch: 7, Acc: 87.03
saving best checkpoint at epoch: 8, Acc: 87.66
saving best checkpoint at epoch: 9, Acc: 87.97
EPOCH 10. Progress: 10.0%.
Train loss: 0.0006. Train Acc: 87.9325, Test loss: 0.0006. Test Acc: 88.1700. Time/epoch: 1.6912
saving best checkpoint at epoch: 10, Acc: 88.17
saving best checkpoint at epoch: 11, Acc: 88.7
saving best checkpoint at epoch: 12, Acc: 88.92
saving best checkpoint at epoch: 13, Acc: 89.15
saving best checkpoint at epoch: 14, Acc: 89.4
saving best checkpoint at epoch: 15, Acc: 89.67
saving best checkpoint at epoch: 17, Acc: 89.96
saving best checkpoint at epoch: 18, Acc: 90.08
saving best checkpoint at epoch: 19, Acc: 90.42
EPOCH 20. Progress: 20.0%.
Train loss: 0.0004. Train Acc: 90.5025, Test loss: 0.0005. Test Acc: 90.4200. Time/epoch: 1.5442
saving best checkpoint at epoch: 21, Acc: 90.77
saving best checkpoint at epoch: 22, Acc: 90.91
saving best checkpoint at epoch: 23, Acc: 90.95
saving best checkpoint at epoch: 24, Acc: 91.35
saving best checkpoint at epoch: 25, Acc: 91.36
saving best checkpoint at epoch: 26, Acc: 91.58
saving best checkpoint at epoch: 27, Acc: 91.81
saving best checkpoint at epoch: 28, Acc: 91.83
saving best checkpoint at epoch: 29, Acc: 92.01
EPOCH 30. Progress: 30.0%.
Train loss: 0.0004. Train Acc: 92.3950, Test loss: 0.0004. Test Acc: 92.2000. Time/epoch: 1.6859
saving best checkpoint at epoch: 30, Acc: 92.2
saving best checkpoint at epoch: 31, Acc: 92.61
saving best checkpoint at epoch: 33, Acc: 92.83
saving best checkpoint at epoch: 35, Acc: 93.06
saving best checkpoint at epoch: 36, Acc: 93.13
saving best checkpoint at epoch: 37, Acc: 93.39
saving best checkpoint at epoch: 39, Acc: 93.61
EPOCH 40. Progress: 40.0%.
Train loss: 0.0003. Train Acc: 93.6300, Test loss: 0.0003. Test Acc: 93.4200. Time/epoch: 1.5401
saving best checkpoint at epoch: 41, Acc: 93.67
saving best checkpoint at epoch: 42, Acc: 93.72
saving best checkpoint at epoch: 43, Acc: 93.76
saving best checkpoint at epoch: 45, Acc: 93.79
saving best checkpoint at epoch: 47, Acc: 93.82
saving best checkpoint at epoch: 48, Acc: 93.91
saving best checkpoint at epoch: 49, Acc: 93.93
EPOCH 50. Progress: 50.0%.
Train loss: 0.0003. Train Acc: 94.1125, Test loss: 0.0003. Test Acc: 93.9400. Time/epoch: 1.6804
saving best checkpoint at epoch: 50, Acc: 93.94
saving best checkpoint at epoch: 51, Acc: 94.03
saving best checkpoint at epoch: 52, Acc: 94.08
saving best checkpoint at epoch: 53, Acc: 94.17
saving best checkpoint at epoch: 55, Acc: 94.18
saving best checkpoint at epoch: 56, Acc: 94.28
saving best checkpoint at epoch: 58, Acc: 94.29
saving best checkpoint at epoch: 59, Acc: 94.39
EPOCH 60. Progress: 60.0%.
Train loss: 0.0003. Train Acc: 94.4850, Test loss: 0.0003. Test Acc: 94.4000. Time/epoch: 1.5317
saving best checkpoint at epoch: 60, Acc: 94.4
saving best checkpoint at epoch: 61, Acc: 94.48
saving best checkpoint at epoch: 62, Acc: 94.55
saving best checkpoint at epoch: 66, Acc: 94.63
EPOCH 70. Progress: 70.0%.
Train loss: 0.0003. Train Acc: 94.8925, Test loss: 0.0003. Test Acc: 94.6800. Time/epoch: 1.5443
saving best checkpoint at epoch: 70, Acc: 94.68
saving best checkpoint at epoch: 72, Acc: 94.79
saving best checkpoint at epoch: 75, Acc: 94.82
saving best checkpoint at epoch: 76, Acc: 94.86
saving best checkpoint at epoch: 79, Acc: 94.87
EPOCH 80. Progress: 80.0%.
Train loss: 0.0002. Train Acc: 95.1350, Test loss: 0.0003. Test Acc: 94.8200. Time/epoch: 1.5417
saving best checkpoint at epoch: 82, Acc: 94.92
saving best checkpoint at epoch: 83, Acc: 95.03
saving best checkpoint at epoch: 89, Acc: 95.13
EPOCH 90. Progress: 90.0%.
Train loss: 0.0002. Train Acc: 95.1825, Test loss: 0.0003. Test Acc: 94.8900. Time/epoch: 1.5541
saving best checkpoint at epoch: 93, Acc: 95.19
saving best checkpoint at epoch: 99, Acc: 95.26
EPOCH 100. Progress: 100.0%.
Train loss: 0.0002. Train Acc: 95.5725, Test loss: 0.0003. Test Acc: 95.2700. Time/epoch: 1.6845
saving best checkpoint at epoch: 100, Acc: 95.27
Run history:
Accuracy/train | ▁▅▆▇▇▇▇▇▇▇▇▇▇███████████████████████████ |
Accuracy/val | ▁▅▆▇▇▇▇▇▇▇▇▇▇███████████████████████████ |
Loss/train | █▄▃▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▄▃▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 95.5725 |
Accuracy/val | 95.27 |
Loss/train | 0.00023 |
Loss/val | 0.00025 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_111359-7y29dvnq/logs
wandb: Agent Starting Run: kzpcou4q with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 3e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_111658-kzpcou4q
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0023. Train Acc: 74.3575, Test loss: 0.0024. Test Acc: 74.7700. Time/epoch: 1.5588
saving best checkpoint at epoch: 0, Acc: 74.77
saving best checkpoint at epoch: 1, Acc: 80.79
saving best checkpoint at epoch: 2, Acc: 84.98
saving best checkpoint at epoch: 3, Acc: 87.6
saving best checkpoint at epoch: 4, Acc: 89.37
saving best checkpoint at epoch: 5, Acc: 90.3
saving best checkpoint at epoch: 6, Acc: 90.92
saving best checkpoint at epoch: 7, Acc: 91.53
saving best checkpoint at epoch: 8, Acc: 91.96
saving best checkpoint at epoch: 9, Acc: 92.34
EPOCH 10. Progress: 10.0%.
Train loss: 0.0004. Train Acc: 92.6275, Test loss: 0.0004. Test Acc: 92.4500. Time/epoch: 1.5460
saving best checkpoint at epoch: 10, Acc: 92.45
saving best checkpoint at epoch: 11, Acc: 93.0
saving best checkpoint at epoch: 12, Acc: 93.51
saving best checkpoint at epoch: 14, Acc: 93.73
saving best checkpoint at epoch: 15, Acc: 93.79
saving best checkpoint at epoch: 17, Acc: 93.91
saving best checkpoint at epoch: 18, Acc: 94.14
saving best checkpoint at epoch: 19, Acc: 94.31
EPOCH 20. Progress: 20.0%.
Train loss: 0.0003. Train Acc: 94.2775, Test loss: 0.0003. Test Acc: 94.4200. Time/epoch: 1.6847
saving best checkpoint at epoch: 20, Acc: 94.42
saving best checkpoint at epoch: 23, Acc: 94.5
saving best checkpoint at epoch: 24, Acc: 94.62
saving best checkpoint at epoch: 25, Acc: 94.67
saving best checkpoint at epoch: 26, Acc: 94.76
saving best checkpoint at epoch: 29, Acc: 94.78
EPOCH 30. Progress: 30.0%.
Train loss: 0.0003. Train Acc: 94.4250, Test loss: 0.0003. Test Acc: 94.6300. Time/epoch: 1.5516
saving best checkpoint at epoch: 31, Acc: 94.91
saving best checkpoint at epoch: 32, Acc: 94.98
saving best checkpoint at epoch: 33, Acc: 95.0
saving best checkpoint at epoch: 34, Acc: 95.16
saving best checkpoint at epoch: 38, Acc: 95.39
EPOCH 40. Progress: 40.0%.
Train loss: 0.0002. Train Acc: 95.4675, Test loss: 0.0002. Test Acc: 95.2200. Time/epoch: 1.6872
saving best checkpoint at epoch: 44, Acc: 95.44
saving best checkpoint at epoch: 46, Acc: 95.64
EPOCH 50. Progress: 50.0%.
Train loss: 0.0002. Train Acc: 95.6625, Test loss: 0.0002. Test Acc: 95.4500. Time/epoch: 1.5611
saving best checkpoint at epoch: 51, Acc: 95.69
saving best checkpoint at epoch: 53, Acc: 95.78
saving best checkpoint at epoch: 55, Acc: 95.86
EPOCH 60. Progress: 60.0%.
Train loss: 0.0002. Train Acc: 96.1950, Test loss: 0.0002. Test Acc: 95.8500. Time/epoch: 1.6812
saving best checkpoint at epoch: 65, Acc: 95.95
saving best checkpoint at epoch: 67, Acc: 96.0
saving best checkpoint at epoch: 68, Acc: 96.03
EPOCH 70. Progress: 70.0%.
Train loss: 0.0002. Train Acc: 96.4625, Test loss: 0.0002. Test Acc: 95.9000. Time/epoch: 1.5452
saving best checkpoint at epoch: 71, Acc: 96.08
saving best checkpoint at epoch: 76, Acc: 96.1
saving best checkpoint at epoch: 77, Acc: 96.18
EPOCH 80. Progress: 80.0%.
Train loss: 0.0002. Train Acc: 96.5350, Test loss: 0.0002. Test Acc: 96.1900. Time/epoch: 1.6792
saving best checkpoint at epoch: 80, Acc: 96.19
saving best checkpoint at epoch: 83, Acc: 96.21
saving best checkpoint at epoch: 84, Acc: 96.34
EPOCH 90. Progress: 90.0%.
Train loss: 0.0002. Train Acc: 96.5550, Test loss: 0.0002. Test Acc: 96.2200. Time/epoch: 1.5554
saving best checkpoint at epoch: 96, Acc: 96.36
saving best checkpoint at epoch: 97, Acc: 96.41
EPOCH 100. Progress: 100.0%.
Train loss: 0.0002. Train Acc: 96.8675, Test loss: 0.0002. Test Acc: 96.3900. Time/epoch: 1.5482
Run history:
Accuracy/train | ▁▄▆▆▇▇▇▇▇▇▇▇▇▇▇██▇██████████████████████ |
Accuracy/val | ▁▄▆▆▇▇▇▇▇▇▇▇▇███████████████████████████ |
Loss/train | █▃▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▃▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 96.8675 |
Accuracy/val | 96.39 |
Loss/train | 0.00016 |
Loss/val | 0.00019 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_111658-kzpcou4q/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: nso6p69b with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_112006-nso6p69b
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0004. Train Acc: 92.7300, Test loss: 0.0004. Test Acc: 92.6500. Time/epoch: 1.7310
saving best checkpoint at epoch: 0, Acc: 92.65
saving best checkpoint at epoch: 1, Acc: 93.12
saving best checkpoint at epoch: 2, Acc: 94.45
saving best checkpoint at epoch: 4, Acc: 95.02
saving best checkpoint at epoch: 5, Acc: 95.13
saving best checkpoint at epoch: 6, Acc: 95.63
saving best checkpoint at epoch: 7, Acc: 95.66
saving best checkpoint at epoch: 8, Acc: 95.9
EPOCH 10. Progress: 10.0%.
Train loss: 0.0002. Train Acc: 96.2250, Test loss: 0.0002. Test Acc: 95.7800. Time/epoch: 1.5495
saving best checkpoint at epoch: 11, Acc: 95.98
saving best checkpoint at epoch: 12, Acc: 96.36
saving best checkpoint at epoch: 15, Acc: 96.65
EPOCH 20. Progress: 20.0%.
Train loss: 0.0001. Train Acc: 97.1975, Test loss: 0.0002. Test Acc: 96.5600. Time/epoch: 1.6899
saving best checkpoint at epoch: 22, Acc: 96.73
saving best checkpoint at epoch: 28, Acc: 96.8
EPOCH 30. Progress: 30.0%.
Train loss: 0.0001. Train Acc: 97.4850, Test loss: 0.0002. Test Acc: 96.7200. Time/epoch: 1.5552
saving best checkpoint at epoch: 31, Acc: 97.02
saving best checkpoint at epoch: 32, Acc: 97.06
EPOCH 40. Progress: 40.0%.
Train loss: 0.0001. Train Acc: 97.2125, Test loss: 0.0002. Test Acc: 96.4500. Time/epoch: 1.6810
saving best checkpoint at epoch: 45, Acc: 97.17
saving best checkpoint at epoch: 48, Acc: 97.23
EPOCH 50. Progress: 50.0%.
Train loss: 0.0001. Train Acc: 97.5950, Test loss: 0.0002. Test Acc: 96.8800. Time/epoch: 1.5647
saving best checkpoint at epoch: 51, Acc: 97.5
EPOCH 60. Progress: 60.0%.
Train loss: 0.0001. Train Acc: 98.5125, Test loss: 0.0002. Test Acc: 97.4700. Time/epoch: 1.6859
saving best checkpoint at epoch: 64, Acc: 97.56
EPOCH 70. Progress: 70.0%.
Train loss: 0.0001. Train Acc: 98.3700, Test loss: 0.0002. Test Acc: 97.1100. Time/epoch: 1.5497
saving best checkpoint at epoch: 71, Acc: 97.63
saving best checkpoint at epoch: 76, Acc: 97.73
EPOCH 80. Progress: 80.0%.
Train loss: 0.0001. Train Acc: 98.7100, Test loss: 0.0002. Test Acc: 97.4800. Time/epoch: 1.6767
EPOCH 90. Progress: 90.0%.
Train loss: 0.0001. Train Acc: 99.0100, Test loss: 0.0002. Test Acc: 97.7000. Time/epoch: 1.5429
saving best checkpoint at epoch: 93, Acc: 97.79
EPOCH 100. Progress: 100.0%.
Train loss: 0.0001. Train Acc: 98.1525, Test loss: 0.0003. Test Acc: 96.4600. Time/epoch: 1.5475
Run history:
Accuracy/train | ▁▃▄▄▅▅▆▅▆▅▅▆▆▆▆▆▆▆▆▇▇▇▇▆▇▇▇██▇██▇▇▇███▇▇ |
Accuracy/val | ▁▃▄▅▅▆▇▆▆▅▆▇▇▆▆▇▇▇▆▇█▇▇▆▇█▇██▇██▇▇▇███▆▆ |
Loss/train | █▆▅▄▄▄▃▄▃▄▄▃▃▃▃▃▃▃▃▂▂▂▂▃▂▂▂▂▂▂▁▁▂▂▁▁▁▁▂▂ |
Loss/val | █▆▄▄▃▃▂▃▂▃▃▂▂▂▂▂▂▂▃▁▁▁▂▃▂▁▂▁▁▂▁▂▃▃▃▃▂▂▄▄ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.1525 |
Accuracy/val | 96.46 |
Loss/train | 9e-05 |
Loss/val | 0.00025 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_112006-nso6p69b/logs
wandb: Agent Starting Run: 6wn27ev3 with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_112306-6wn27ev3
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0004. Train Acc: 90.5625, Test loss: 0.0004. Test Acc: 90.6000. Time/epoch: 1.6995
saving best checkpoint at epoch: 0, Acc: 90.6
saving best checkpoint at epoch: 1, Acc: 91.8
saving best checkpoint at epoch: 2, Acc: 93.86
saving best checkpoint at epoch: 4, Acc: 94.74
saving best checkpoint at epoch: 5, Acc: 94.94
saving best checkpoint at epoch: 7, Acc: 95.17
saving best checkpoint at epoch: 8, Acc: 95.41
EPOCH 10. Progress: 10.0%.
Train loss: 0.0002. Train Acc: 96.3775, Test loss: 0.0002. Test Acc: 95.8100. Time/epoch: 1.5637
saving best checkpoint at epoch: 10, Acc: 95.81
saving best checkpoint at epoch: 11, Acc: 96.01
saving best checkpoint at epoch: 12, Acc: 96.05
saving best checkpoint at epoch: 13, Acc: 96.06
saving best checkpoint at epoch: 14, Acc: 96.27
saving best checkpoint at epoch: 15, Acc: 96.51
saving best checkpoint at epoch: 18, Acc: 96.66
EPOCH 20. Progress: 20.0%.
Train loss: 0.0003. Train Acc: 94.8825, Test loss: 0.0003. Test Acc: 94.6200. Time/epoch: 1.6861
saving best checkpoint at epoch: 22, Acc: 96.73
saving best checkpoint at epoch: 23, Acc: 96.96
saving best checkpoint at epoch: 25, Acc: 97.24
EPOCH 30. Progress: 30.0%.
Train loss: 0.0002. Train Acc: 96.3625, Test loss: 0.0002. Test Acc: 96.1200. Time/epoch: 1.5534
saving best checkpoint at epoch: 38, Acc: 97.44
EPOCH 40. Progress: 40.0%.
Train loss: 0.0001. Train Acc: 97.3425, Test loss: 0.0002. Test Acc: 96.7600. Time/epoch: 1.6890
saving best checkpoint at epoch: 41, Acc: 97.61
saving best checkpoint at epoch: 45, Acc: 97.66
EPOCH 50. Progress: 50.0%.
Train loss: 0.0001. Train Acc: 98.2225, Test loss: 0.0001. Test Acc: 97.5100. Time/epoch: 1.5652
saving best checkpoint at epoch: 57, Acc: 97.69
saving best checkpoint at epoch: 59, Acc: 97.81
EPOCH 60. Progress: 60.0%.
Train loss: 0.0001. Train Acc: 98.6450, Test loss: 0.0001. Test Acc: 97.5300. Time/epoch: 1.6991
EPOCH 70. Progress: 70.0%.
Train loss: 0.0001. Train Acc: 98.6975, Test loss: 0.0001. Test Acc: 97.5600. Time/epoch: 1.5375
EPOCH 80. Progress: 80.0%.
Train loss: 0.0001. Train Acc: 98.5425, Test loss: 0.0001. Test Acc: 97.4900. Time/epoch: 1.6952
saving best checkpoint at epoch: 81, Acc: 97.97
EPOCH 90. Progress: 90.0%.
Train loss: 0.0002. Train Acc: 96.5300, Test loss: 0.0003. Test Acc: 95.8000. Time/epoch: 1.5501
saving best checkpoint at epoch: 93, Acc: 98.04
EPOCH 100. Progress: 100.0%.
Train loss: 0.0000. Train Acc: 99.0925, Test loss: 0.0001. Test Acc: 97.9200. Time/epoch: 1.5553
Run history:
Accuracy/train | ▁▄▄▅▆▆▆▄▅▇▇▇▆▆▇▇▇▇▇▇▇▇▇▇▆▇▇█▇▇▇███▆███▇█ |
Accuracy/val | ▁▄▅▅▆▆▇▅▅▇▇▇▆▆▇██▇▇▇▇█▇▇▇▇▇██▇▇███▆█▇█▇█ |
Loss/train | █▅▅▄▄▄▃▅▅▃▂▂▃▄▂▂▂▂▂▂▂▂▂▃▂▂▂▁▂▂▂▁▁▁▃▁▂▁▁▁ |
Loss/val | █▅▄▄▃▃▂▅▄▂▂▂▃▃▂▁▁▂▂▂▂▁▂▂▂▂▃▁▂▂▂▁▁▁▃▁▂▂▂▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 99.0925 |
Accuracy/val | 97.92 |
Loss/train | 5e-05 |
Loss/val | 0.00014 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_112306-6wn27ev3/logs
wandb: Agent Starting Run: lwhnokhf with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 3e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_112603-lwhnokhf
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0017. Train Acc: 70.1950, Test loss: 0.0017. Test Acc: 70.5800. Time/epoch: 1.7054
saving best checkpoint at epoch: 0, Acc: 70.58
saving best checkpoint at epoch: 1, Acc: 83.69
saving best checkpoint at epoch: 2, Acc: 88.34
saving best checkpoint at epoch: 3, Acc: 89.76
saving best checkpoint at epoch: 4, Acc: 90.66
saving best checkpoint at epoch: 5, Acc: 91.08
saving best checkpoint at epoch: 6, Acc: 91.43
saving best checkpoint at epoch: 7, Acc: 91.81
saving best checkpoint at epoch: 8, Acc: 92.42
saving best checkpoint at epoch: 9, Acc: 92.98
EPOCH 10. Progress: 10.0%.
Train loss: 0.0003. Train Acc: 93.2650, Test loss: 0.0004. Test Acc: 93.3600. Time/epoch: 1.5644
saving best checkpoint at epoch: 10, Acc: 93.36
saving best checkpoint at epoch: 11, Acc: 94.0
saving best checkpoint at epoch: 14, Acc: 94.53
saving best checkpoint at epoch: 16, Acc: 95.06
saving best checkpoint at epoch: 17, Acc: 95.11
saving best checkpoint at epoch: 18, Acc: 95.29
EPOCH 20. Progress: 20.0%.
Train loss: 0.0002. Train Acc: 95.6125, Test loss: 0.0003. Test Acc: 95.6500. Time/epoch: 1.6869
saving best checkpoint at epoch: 20, Acc: 95.65
saving best checkpoint at epoch: 23, Acc: 95.66
saving best checkpoint at epoch: 24, Acc: 95.75
saving best checkpoint at epoch: 25, Acc: 95.82
saving best checkpoint at epoch: 26, Acc: 95.94
saving best checkpoint at epoch: 27, Acc: 96.0
saving best checkpoint at epoch: 28, Acc: 96.1
EPOCH 30. Progress: 30.0%.
Train loss: 0.0002. Train Acc: 96.0875, Test loss: 0.0002. Test Acc: 96.0700. Time/epoch: 1.5542
saving best checkpoint at epoch: 34, Acc: 96.3
saving best checkpoint at epoch: 37, Acc: 96.35
EPOCH 40. Progress: 40.0%.
Train loss: 0.0002. Train Acc: 96.6200, Test loss: 0.0002. Test Acc: 96.3300. Time/epoch: 1.6839
saving best checkpoint at epoch: 42, Acc: 96.48
saving best checkpoint at epoch: 49, Acc: 96.51
EPOCH 50. Progress: 50.0%.
Train loss: 0.0002. Train Acc: 96.5325, Test loss: 0.0002. Test Acc: 96.3800. Time/epoch: 1.5649
saving best checkpoint at epoch: 51, Acc: 96.67
saving best checkpoint at epoch: 58, Acc: 96.68
saving best checkpoint at epoch: 59, Acc: 96.77
EPOCH 60. Progress: 60.0%.
Train loss: 0.0002. Train Acc: 97.1075, Test loss: 0.0002. Test Acc: 96.6100. Time/epoch: 1.6875
saving best checkpoint at epoch: 61, Acc: 96.82
saving best checkpoint at epoch: 63, Acc: 96.83
saving best checkpoint at epoch: 64, Acc: 96.92
saving best checkpoint at epoch: 66, Acc: 96.95
saving best checkpoint at epoch: 69, Acc: 96.98
EPOCH 70. Progress: 70.0%.
Train loss: 0.0001. Train Acc: 97.2900, Test loss: 0.0002. Test Acc: 96.9000. Time/epoch: 1.5406
saving best checkpoint at epoch: 72, Acc: 97.03
saving best checkpoint at epoch: 77, Acc: 97.12
EPOCH 80. Progress: 80.0%.
Train loss: 0.0001. Train Acc: 97.4675, Test loss: 0.0002. Test Acc: 97.0800. Time/epoch: 1.6812
saving best checkpoint at epoch: 82, Acc: 97.14
EPOCH 90. Progress: 90.0%.
Train loss: 0.0001. Train Acc: 97.5250, Test loss: 0.0002. Test Acc: 96.9200. Time/epoch: 1.5510
saving best checkpoint at epoch: 94, Acc: 97.22
saving best checkpoint at epoch: 95, Acc: 97.29
EPOCH 100. Progress: 100.0%.
Train loss: 0.0001. Train Acc: 97.4550, Test loss: 0.0002. Test Acc: 96.6900. Time/epoch: 1.6926
Run history:
Accuracy/train | ▁▆▆▆▇▇▇▇▇███████████████████████████████ |
Accuracy/val | ▁▆▆▇▇▇▇▇████████████████████████████████ |
Loss/train | █▃▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▃▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 97.455 |
Accuracy/val | 96.69 |
Loss/train | 0.00014 |
Loss/val | 0.00017 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_112603-lwhnokhf/logs
wandb: Agent Starting Run: nxmjjnle with config:
wandb: batch_size: 128
wandb: epochs: 100
wandb: learning_rate: 1e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_112902-nxmjjnle
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0048. Train Acc: 77.7950, Test loss: 0.0048. Test Acc: 77.8900. Time/epoch: 2.2228
saving best checkpoint at epoch: 0, Acc: 77.89
saving best checkpoint at epoch: 1, Acc: 86.26
saving best checkpoint at epoch: 2, Acc: 88.27
saving best checkpoint at epoch: 3, Acc: 90.18
saving best checkpoint at epoch: 4, Acc: 90.72
saving best checkpoint at epoch: 5, Acc: 91.31
saving best checkpoint at epoch: 6, Acc: 91.46
saving best checkpoint at epoch: 7, Acc: 91.94
saving best checkpoint at epoch: 8, Acc: 92.4
EPOCH 10. Progress: 10.0%.
Train loss: 0.0014. Train Acc: 92.7650, Test loss: 0.0014. Test Acc: 92.8400. Time/epoch: 2.0406
saving best checkpoint at epoch: 10, Acc: 92.84
saving best checkpoint at epoch: 11, Acc: 92.94
saving best checkpoint at epoch: 12, Acc: 93.0
saving best checkpoint at epoch: 13, Acc: 93.3
saving best checkpoint at epoch: 14, Acc: 93.62
saving best checkpoint at epoch: 15, Acc: 93.71
saving best checkpoint at epoch: 16, Acc: 93.85
saving best checkpoint at epoch: 18, Acc: 93.94
EPOCH 20. Progress: 20.0%.
Train loss: 0.0012. Train Acc: 93.8000, Test loss: 0.0012. Test Acc: 93.9800. Time/epoch: 2.0324
saving best checkpoint at epoch: 20, Acc: 93.98
saving best checkpoint at epoch: 21, Acc: 94.19
saving best checkpoint at epoch: 22, Acc: 94.22
saving best checkpoint at epoch: 24, Acc: 94.24
saving best checkpoint at epoch: 25, Acc: 94.36
saving best checkpoint at epoch: 27, Acc: 94.38
saving best checkpoint at epoch: 28, Acc: 94.54
saving best checkpoint at epoch: 29, Acc: 94.6
EPOCH 30. Progress: 30.0%.
Train loss: 0.0010. Train Acc: 94.5650, Test loss: 0.0011. Test Acc: 94.4500. Time/epoch: 2.0292
saving best checkpoint at epoch: 32, Acc: 94.71
saving best checkpoint at epoch: 34, Acc: 94.85
saving best checkpoint at epoch: 35, Acc: 94.87
EPOCH 40. Progress: 40.0%.
Train loss: 0.0010. Train Acc: 94.8700, Test loss: 0.0011. Test Acc: 94.6800. Time/epoch: 2.1745
saving best checkpoint at epoch: 41, Acc: 94.95
saving best checkpoint at epoch: 43, Acc: 94.96
saving best checkpoint at epoch: 44, Acc: 95.08
saving best checkpoint at epoch: 46, Acc: 95.12
saving best checkpoint at epoch: 47, Acc: 95.19
EPOCH 50. Progress: 50.0%.
Train loss: 0.0009. Train Acc: 95.3225, Test loss: 0.0010. Test Acc: 95.1500. Time/epoch: 2.1725
saving best checkpoint at epoch: 51, Acc: 95.22
saving best checkpoint at epoch: 53, Acc: 95.25
saving best checkpoint at epoch: 55, Acc: 95.33
saving best checkpoint at epoch: 56, Acc: 95.43
saving best checkpoint at epoch: 58, Acc: 95.48
EPOCH 60. Progress: 60.0%.
Train loss: 0.0009. Train Acc: 95.6725, Test loss: 0.0009. Test Acc: 95.4300. Time/epoch: 2.0500
saving best checkpoint at epoch: 62, Acc: 95.5
saving best checkpoint at epoch: 63, Acc: 95.55
saving best checkpoint at epoch: 68, Acc: 95.56
saving best checkpoint at epoch: 69, Acc: 95.59
EPOCH 70. Progress: 70.0%.
Train loss: 0.0008. Train Acc: 95.7775, Test loss: 0.0009. Test Acc: 95.6000. Time/epoch: 2.1815
saving best checkpoint at epoch: 70, Acc: 95.6
saving best checkpoint at epoch: 71, Acc: 95.61
saving best checkpoint at epoch: 74, Acc: 95.65
saving best checkpoint at epoch: 79, Acc: 95.7
EPOCH 80. Progress: 80.0%.
Train loss: 0.0008. Train Acc: 95.9700, Test loss: 0.0009. Test Acc: 95.6700. Time/epoch: 2.1883
saving best checkpoint at epoch: 81, Acc: 95.79
saving best checkpoint at epoch: 84, Acc: 95.86
EPOCH 90. Progress: 90.0%.
Train loss: 0.0008. Train Acc: 96.0900, Test loss: 0.0009. Test Acc: 95.8600. Time/epoch: 2.1885
saving best checkpoint at epoch: 91, Acc: 95.91
saving best checkpoint at epoch: 94, Acc: 95.94
saving best checkpoint at epoch: 95, Acc: 95.98
saving best checkpoint at epoch: 98, Acc: 96.0
EPOCH 100. Progress: 100.0%.
Train loss: 0.0007. Train Acc: 96.3375, Test loss: 0.0008. Test Acc: 95.9400. Time/epoch: 2.1984
Run history:
Accuracy/train | ▁▅▆▆▇▇▇▇▇▇▇▇▇▇▇▇████████████████████████ |
Accuracy/val | ▁▅▆▆▇▇▇▇▇▇▇▇▇▇██████████████████████████ |
Loss/train | █▄▃▂▂▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▄▃▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 96.3375 |
Accuracy/val | 95.94 |
Loss/train | 0.00073 |
Loss/val | 0.00082 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_112902-nxmjjnle/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: 89ljl1lj with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 1e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_113304-89ljl1lj
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0042. Train Acc: 24.0875, Test loss: 0.0043. Test Acc: 24.5400. Time/epoch: 1.5998
saving best checkpoint at epoch: 0, Acc: 24.54
saving best checkpoint at epoch: 1, Acc: 51.54
saving best checkpoint at epoch: 2, Acc: 70.76
saving best checkpoint at epoch: 3, Acc: 75.35
saving best checkpoint at epoch: 4, Acc: 79.33
saving best checkpoint at epoch: 5, Acc: 82.16
saving best checkpoint at epoch: 6, Acc: 83.95
saving best checkpoint at epoch: 7, Acc: 85.36
saving best checkpoint at epoch: 8, Acc: 86.82
saving best checkpoint at epoch: 9, Acc: 88.09
EPOCH 10. Progress: 10.0%.
Train loss: 0.0006. Train Acc: 88.6925, Test loss: 0.0007. Test Acc: 88.5700. Time/epoch: 1.5446
saving best checkpoint at epoch: 10, Acc: 88.57
saving best checkpoint at epoch: 11, Acc: 89.2
saving best checkpoint at epoch: 12, Acc: 90.04
saving best checkpoint at epoch: 13, Acc: 90.16
saving best checkpoint at epoch: 14, Acc: 90.47
saving best checkpoint at epoch: 15, Acc: 90.9
saving best checkpoint at epoch: 16, Acc: 91.03
saving best checkpoint at epoch: 17, Acc: 91.45
saving best checkpoint at epoch: 18, Acc: 91.68
saving best checkpoint at epoch: 19, Acc: 91.76
EPOCH 20. Progress: 20.0%.
Train loss: 0.0004. Train Acc: 92.0350, Test loss: 0.0004. Test Acc: 92.0100. Time/epoch: 1.5407
saving best checkpoint at epoch: 20, Acc: 92.01
saving best checkpoint at epoch: 21, Acc: 92.34
saving best checkpoint at epoch: 22, Acc: 92.53
saving best checkpoint at epoch: 24, Acc: 92.56
saving best checkpoint at epoch: 25, Acc: 92.58
saving best checkpoint at epoch: 26, Acc: 92.74
saving best checkpoint at epoch: 27, Acc: 92.88
saving best checkpoint at epoch: 28, Acc: 92.97
EPOCH 30. Progress: 30.0%.
Train loss: 0.0003. Train Acc: 93.2075, Test loss: 0.0004. Test Acc: 93.0200. Time/epoch: 1.5433
saving best checkpoint at epoch: 30, Acc: 93.02
saving best checkpoint at epoch: 31, Acc: 93.05
saving best checkpoint at epoch: 33, Acc: 93.1
saving best checkpoint at epoch: 34, Acc: 93.2
saving best checkpoint at epoch: 35, Acc: 93.28
saving best checkpoint at epoch: 37, Acc: 93.31
saving best checkpoint at epoch: 38, Acc: 93.45
saving best checkpoint at epoch: 39, Acc: 93.68
EPOCH 40. Progress: 40.0%.
Train loss: 0.0003. Train Acc: 93.9150, Test loss: 0.0003. Test Acc: 93.8100. Time/epoch: 1.6855
saving best checkpoint at epoch: 40, Acc: 93.81
saving best checkpoint at epoch: 41, Acc: 93.85
saving best checkpoint at epoch: 42, Acc: 93.9
saving best checkpoint at epoch: 44, Acc: 94.0
saving best checkpoint at epoch: 47, Acc: 94.11
saving best checkpoint at epoch: 48, Acc: 94.13
saving best checkpoint at epoch: 49, Acc: 94.18
EPOCH 50. Progress: 50.0%.
Train loss: 0.0003. Train Acc: 94.3875, Test loss: 0.0003. Test Acc: 94.2400. Time/epoch: 1.5570
saving best checkpoint at epoch: 50, Acc: 94.24
saving best checkpoint at epoch: 52, Acc: 94.35
saving best checkpoint at epoch: 53, Acc: 94.38
saving best checkpoint at epoch: 55, Acc: 94.47
saving best checkpoint at epoch: 58, Acc: 94.5
EPOCH 60. Progress: 60.0%.
Train loss: 0.0003. Train Acc: 94.6850, Test loss: 0.0003. Test Acc: 94.4300. Time/epoch: 1.5400
saving best checkpoint at epoch: 61, Acc: 94.6
saving best checkpoint at epoch: 66, Acc: 94.62
saving best checkpoint at epoch: 67, Acc: 94.7
saving best checkpoint at epoch: 69, Acc: 94.85
EPOCH 70. Progress: 70.0%.
Train loss: 0.0002. Train Acc: 95.0875, Test loss: 0.0003. Test Acc: 94.9400. Time/epoch: 1.6995
saving best checkpoint at epoch: 70, Acc: 94.94
saving best checkpoint at epoch: 74, Acc: 94.96
saving best checkpoint at epoch: 79, Acc: 95.0
EPOCH 80. Progress: 80.0%.
Train loss: 0.0002. Train Acc: 95.2850, Test loss: 0.0003. Test Acc: 94.9500. Time/epoch: 1.5508
saving best checkpoint at epoch: 81, Acc: 95.13
saving best checkpoint at epoch: 87, Acc: 95.21
saving best checkpoint at epoch: 88, Acc: 95.31
EPOCH 90. Progress: 90.0%.
Train loss: 0.0002. Train Acc: 95.4125, Test loss: 0.0002. Test Acc: 95.1700. Time/epoch: 1.5511
saving best checkpoint at epoch: 91, Acc: 95.36
saving best checkpoint at epoch: 95, Acc: 95.38
saving best checkpoint at epoch: 97, Acc: 95.45
EPOCH 100. Progress: 100.0%.
Train loss: 0.0002. Train Acc: 95.6550, Test loss: 0.0002. Test Acc: 95.4400. Time/epoch: 1.5432
Run history:
Accuracy/train | ▁▆▇▇▇▇██████████████████████████████████ |
Accuracy/val | ▁▆▇▇▇▇██████████████████████████████████ |
Loss/train | █▅▃▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▅▃▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 95.655 |
Accuracy/val | 95.44 |
Loss/train | 0.00021 |
Loss/val | 0.00024 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_113304-89ljl1lj/logs
wandb: Agent Starting Run: 65z2fmi0 with config:
wandb: batch_size: 128
wandb: epochs: 100
wandb: learning_rate: 1e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_113604-65z2fmi0
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0052. Train Acc: 75.1550, Test loss: 0.0052. Test Acc: 74.8100. Time/epoch: 2.2607
saving best checkpoint at epoch: 0, Acc: 74.81
saving best checkpoint at epoch: 1, Acc: 84.52
saving best checkpoint at epoch: 2, Acc: 87.27
saving best checkpoint at epoch: 3, Acc: 89.21
saving best checkpoint at epoch: 4, Acc: 89.81
saving best checkpoint at epoch: 5, Acc: 91.0
saving best checkpoint at epoch: 6, Acc: 91.26
saving best checkpoint at epoch: 7, Acc: 91.39
saving best checkpoint at epoch: 8, Acc: 92.05
saving best checkpoint at epoch: 9, Acc: 92.49
EPOCH 10. Progress: 10.0%.
Train loss: 0.0014. Train Acc: 92.8650, Test loss: 0.0014. Test Acc: 92.9000. Time/epoch: 2.2024
saving best checkpoint at epoch: 10, Acc: 92.9
saving best checkpoint at epoch: 11, Acc: 93.2
saving best checkpoint at epoch: 12, Acc: 93.57
saving best checkpoint at epoch: 13, Acc: 93.81
saving best checkpoint at epoch: 15, Acc: 94.2
saving best checkpoint at epoch: 17, Acc: 94.45
saving best checkpoint at epoch: 18, Acc: 94.71
saving best checkpoint at epoch: 19, Acc: 94.9
EPOCH 20. Progress: 20.0%.
Train loss: 0.0010. Train Acc: 94.8750, Test loss: 0.0011. Test Acc: 94.7800. Time/epoch: 2.0395
saving best checkpoint at epoch: 21, Acc: 94.92
saving best checkpoint at epoch: 22, Acc: 95.09
saving best checkpoint at epoch: 23, Acc: 95.51
saving best checkpoint at epoch: 28, Acc: 95.58
EPOCH 30. Progress: 30.0%.
Train loss: 0.0009. Train Acc: 95.8050, Test loss: 0.0010. Test Acc: 95.7800. Time/epoch: 2.0350
saving best checkpoint at epoch: 30, Acc: 95.78
saving best checkpoint at epoch: 31, Acc: 95.88
saving best checkpoint at epoch: 33, Acc: 95.98
saving best checkpoint at epoch: 36, Acc: 96.01
saving best checkpoint at epoch: 37, Acc: 96.07
EPOCH 40. Progress: 40.0%.
Train loss: 0.0008. Train Acc: 96.1600, Test loss: 0.0009. Test Acc: 96.0800. Time/epoch: 2.1717
saving best checkpoint at epoch: 40, Acc: 96.08
saving best checkpoint at epoch: 41, Acc: 96.15
saving best checkpoint at epoch: 42, Acc: 96.27
saving best checkpoint at epoch: 43, Acc: 96.35
saving best checkpoint at epoch: 47, Acc: 96.41
EPOCH 50. Progress: 50.0%.
Train loss: 0.0007. Train Acc: 96.6100, Test loss: 0.0008. Test Acc: 96.4000. Time/epoch: 2.1712
saving best checkpoint at epoch: 51, Acc: 96.47
saving best checkpoint at epoch: 53, Acc: 96.51
saving best checkpoint at epoch: 54, Acc: 96.56
saving best checkpoint at epoch: 56, Acc: 96.61
EPOCH 60. Progress: 60.0%.
Train loss: 0.0007. Train Acc: 96.8450, Test loss: 0.0008. Test Acc: 96.6400. Time/epoch: 2.1877
saving best checkpoint at epoch: 60, Acc: 96.64
saving best checkpoint at epoch: 61, Acc: 96.7
saving best checkpoint at epoch: 65, Acc: 96.79
EPOCH 70. Progress: 70.0%.
Train loss: 0.0006. Train Acc: 97.0100, Test loss: 0.0007. Test Acc: 96.7000. Time/epoch: 2.1843
saving best checkpoint at epoch: 73, Acc: 96.86
saving best checkpoint at epoch: 74, Acc: 96.87
saving best checkpoint at epoch: 76, Acc: 96.89
saving best checkpoint at epoch: 78, Acc: 96.92
EPOCH 80. Progress: 80.0%.
Train loss: 0.0006. Train Acc: 97.2650, Test loss: 0.0007. Test Acc: 96.8300. Time/epoch: 2.1802
saving best checkpoint at epoch: 83, Acc: 97.02
EPOCH 90. Progress: 90.0%.
Train loss: 0.0006. Train Acc: 97.3550, Test loss: 0.0007. Test Acc: 97.0800. Time/epoch: 2.1789
saving best checkpoint at epoch: 90, Acc: 97.08
saving best checkpoint at epoch: 93, Acc: 97.12
EPOCH 100. Progress: 100.0%.
Train loss: 0.0006. Train Acc: 97.2375, Test loss: 0.0007. Test Acc: 96.9000. Time/epoch: 2.1800
Run history:
Accuracy/train | ▁▅▆▆▇▇▇▇▇▇▇▇▇███████████████████████████ |
Accuracy/val | ▁▅▆▆▇▇▇▇▇█▇█████████████████████████████ |
Loss/train | █▄▃▃▂▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▃▃▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 97.2375 |
Accuracy/val | 96.9 |
Loss/train | 0.00058 |
Loss/val | 0.00068 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_113604-65z2fmi0/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: hbrimc3e with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 3e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_114007-hbrimc3e
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0022. Train Acc: 74.7175, Test loss: 0.0023. Test Acc: 74.6600. Time/epoch: 1.7167
saving best checkpoint at epoch: 0, Acc: 74.66
saving best checkpoint at epoch: 1, Acc: 81.22
saving best checkpoint at epoch: 2, Acc: 86.62
saving best checkpoint at epoch: 3, Acc: 88.51
saving best checkpoint at epoch: 4, Acc: 89.79
saving best checkpoint at epoch: 5, Acc: 90.94
saving best checkpoint at epoch: 6, Acc: 91.5
saving best checkpoint at epoch: 7, Acc: 92.36
saving best checkpoint at epoch: 8, Acc: 92.77
EPOCH 10. Progress: 10.0%.
Train loss: 0.0003. Train Acc: 92.9475, Test loss: 0.0004. Test Acc: 92.9700. Time/epoch: 1.5382
saving best checkpoint at epoch: 10, Acc: 92.97
saving best checkpoint at epoch: 11, Acc: 93.22
saving best checkpoint at epoch: 12, Acc: 93.39
saving best checkpoint at epoch: 13, Acc: 93.42
saving best checkpoint at epoch: 14, Acc: 93.54
saving best checkpoint at epoch: 15, Acc: 93.76
saving best checkpoint at epoch: 16, Acc: 93.9
saving best checkpoint at epoch: 18, Acc: 94.26
saving best checkpoint at epoch: 19, Acc: 94.28
EPOCH 20. Progress: 20.0%.
Train loss: 0.0003. Train Acc: 94.3200, Test loss: 0.0003. Test Acc: 94.3300. Time/epoch: 1.6885
saving best checkpoint at epoch: 20, Acc: 94.33
saving best checkpoint at epoch: 21, Acc: 94.41
saving best checkpoint at epoch: 25, Acc: 94.43
saving best checkpoint at epoch: 26, Acc: 94.74
EPOCH 30. Progress: 30.0%.
Train loss: 0.0003. Train Acc: 94.8250, Test loss: 0.0003. Test Acc: 94.5800. Time/epoch: 1.5347
saving best checkpoint at epoch: 31, Acc: 94.88
saving best checkpoint at epoch: 36, Acc: 94.93
saving best checkpoint at epoch: 37, Acc: 94.96
saving best checkpoint at epoch: 38, Acc: 95.18
EPOCH 40. Progress: 40.0%.
Train loss: 0.0002. Train Acc: 95.4675, Test loss: 0.0002. Test Acc: 95.2700. Time/epoch: 1.5416
saving best checkpoint at epoch: 40, Acc: 95.27
saving best checkpoint at epoch: 41, Acc: 95.31
saving best checkpoint at epoch: 42, Acc: 95.36
saving best checkpoint at epoch: 43, Acc: 95.47
saving best checkpoint at epoch: 49, Acc: 95.57
EPOCH 50. Progress: 50.0%.
Train loss: 0.0002. Train Acc: 95.8625, Test loss: 0.0002. Test Acc: 95.5800. Time/epoch: 1.5534
saving best checkpoint at epoch: 50, Acc: 95.58
saving best checkpoint at epoch: 55, Acc: 95.63
saving best checkpoint at epoch: 58, Acc: 95.65
EPOCH 60. Progress: 60.0%.
Train loss: 0.0002. Train Acc: 96.0825, Test loss: 0.0002. Test Acc: 95.7800. Time/epoch: 1.6938
saving best checkpoint at epoch: 60, Acc: 95.78
saving best checkpoint at epoch: 62, Acc: 95.84
saving best checkpoint at epoch: 65, Acc: 95.95
saving best checkpoint at epoch: 68, Acc: 95.97
EPOCH 70. Progress: 70.0%.
Train loss: 0.0002. Train Acc: 96.3300, Test loss: 0.0002. Test Acc: 95.9100. Time/epoch: 1.5549
saving best checkpoint at epoch: 71, Acc: 96.01
saving best checkpoint at epoch: 74, Acc: 96.12
saving best checkpoint at epoch: 77, Acc: 96.16
EPOCH 80. Progress: 80.0%.
Train loss: 0.0002. Train Acc: 96.4650, Test loss: 0.0002. Test Acc: 96.0200. Time/epoch: 1.5462
saving best checkpoint at epoch: 84, Acc: 96.29
EPOCH 90. Progress: 90.0%.
Train loss: 0.0002. Train Acc: 96.6250, Test loss: 0.0002. Test Acc: 96.1100. Time/epoch: 1.6813
saving best checkpoint at epoch: 93, Acc: 96.36
EPOCH 100. Progress: 100.0%.
Train loss: 0.0002. Train Acc: 96.8975, Test loss: 0.0002. Test Acc: 96.3600. Time/epoch: 1.5675
Run history:
Accuracy/train | ▁▅▆▆▇▇▇▇▇▇▇▇▇▇▇█████████████████████████ |
Accuracy/val | ▁▅▆▇▇▇▇▇▇▇▇▇▇▇██████████████████████████ |
Loss/train | █▃▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▃▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 96.8975 |
Accuracy/val | 96.36 |
Loss/train | 0.00016 |
Loss/val | 0.00018 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_114007-hbrimc3e/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: 2hwteiti with config:
wandb: batch_size: 128
wandb: epochs: 100
wandb: learning_rate: 1e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_114333-2hwteiti
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0037. Train Acc: 83.4850, Test loss: 0.0038. Test Acc: 82.9700. Time/epoch: 2.2066
saving best checkpoint at epoch: 0, Acc: 82.97
saving best checkpoint at epoch: 1, Acc: 86.42
saving best checkpoint at epoch: 2, Acc: 88.52
saving best checkpoint at epoch: 3, Acc: 90.46
saving best checkpoint at epoch: 4, Acc: 91.47
saving best checkpoint at epoch: 5, Acc: 92.1
saving best checkpoint at epoch: 6, Acc: 92.33
saving best checkpoint at epoch: 7, Acc: 93.0
saving best checkpoint at epoch: 8, Acc: 93.36
saving best checkpoint at epoch: 9, Acc: 93.69
EPOCH 10. Progress: 10.0%.
Train loss: 0.0012. Train Acc: 93.7950, Test loss: 0.0013. Test Acc: 93.6300. Time/epoch: 2.1826
saving best checkpoint at epoch: 11, Acc: 93.88
saving best checkpoint at epoch: 12, Acc: 94.11
saving best checkpoint at epoch: 14, Acc: 94.25
saving best checkpoint at epoch: 15, Acc: 94.26
saving best checkpoint at epoch: 16, Acc: 94.43
saving best checkpoint at epoch: 18, Acc: 94.56
EPOCH 20. Progress: 20.0%.
Train loss: 0.0010. Train Acc: 94.9325, Test loss: 0.0011. Test Acc: 94.7300. Time/epoch: 2.1813
saving best checkpoint at epoch: 20, Acc: 94.73
saving best checkpoint at epoch: 23, Acc: 94.88
saving best checkpoint at epoch: 25, Acc: 95.04
saving best checkpoint at epoch: 26, Acc: 95.07
saving best checkpoint at epoch: 27, Acc: 95.13
EPOCH 30. Progress: 30.0%.
Train loss: 0.0009. Train Acc: 95.3350, Test loss: 0.0010. Test Acc: 95.2500. Time/epoch: 2.1791
saving best checkpoint at epoch: 30, Acc: 95.25
saving best checkpoint at epoch: 34, Acc: 95.31
saving best checkpoint at epoch: 37, Acc: 95.37
EPOCH 40. Progress: 40.0%.
Train loss: 0.0009. Train Acc: 95.7150, Test loss: 0.0010. Test Acc: 95.4500. Time/epoch: 2.1803
saving best checkpoint at epoch: 40, Acc: 95.45
saving best checkpoint at epoch: 41, Acc: 95.49
saving best checkpoint at epoch: 42, Acc: 95.57
saving best checkpoint at epoch: 44, Acc: 95.59
saving best checkpoint at epoch: 45, Acc: 95.61
saving best checkpoint at epoch: 48, Acc: 95.69
EPOCH 50. Progress: 50.0%.
Train loss: 0.0008. Train Acc: 95.8875, Test loss: 0.0009. Test Acc: 95.5800. Time/epoch: 2.1753
saving best checkpoint at epoch: 53, Acc: 95.82
saving best checkpoint at epoch: 54, Acc: 95.83
saving best checkpoint at epoch: 56, Acc: 95.92
EPOCH 60. Progress: 60.0%.
Train loss: 0.0008. Train Acc: 96.1975, Test loss: 0.0009. Test Acc: 95.8900. Time/epoch: 2.2064
saving best checkpoint at epoch: 61, Acc: 95.94
saving best checkpoint at epoch: 66, Acc: 96.06
saving best checkpoint at epoch: 69, Acc: 96.17
EPOCH 70. Progress: 70.0%.
Train loss: 0.0007. Train Acc: 96.4950, Test loss: 0.0008. Test Acc: 96.1600. Time/epoch: 2.1930
saving best checkpoint at epoch: 75, Acc: 96.21
saving best checkpoint at epoch: 79, Acc: 96.32
EPOCH 80. Progress: 80.0%.
Train loss: 0.0007. Train Acc: 96.6250, Test loss: 0.0008. Test Acc: 96.3200. Time/epoch: 2.0398
saving best checkpoint at epoch: 83, Acc: 96.33
saving best checkpoint at epoch: 88, Acc: 96.49
EPOCH 90. Progress: 90.0%.
Train loss: 0.0007. Train Acc: 96.7900, Test loss: 0.0008. Test Acc: 96.3500. Time/epoch: 2.1816
saving best checkpoint at epoch: 93, Acc: 96.53
saving best checkpoint at epoch: 95, Acc: 96.56
EPOCH 100. Progress: 100.0%.
Train loss: 0.0006. Train Acc: 97.0050, Test loss: 0.0008. Test Acc: 96.5000. Time/epoch: 2.1892
Run history:
Accuracy/train | ▁▄▆▆▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇███████████████████ |
Accuracy/val | ▁▄▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇█████████████████████ |
Loss/train | █▄▃▃▂▂▂▂▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▄▃▃▂▂▂▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 97.005 |
Accuracy/val | 96.5 |
Loss/train | 0.00063 |
Loss/val | 0.00077 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_114333-2hwteiti/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: 5n56vdas with config:
wandb: batch_size: 128
wandb: epochs: 100
wandb: learning_rate: 1e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_114748-5n56vdas
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0059. Train Acc: 80.4600, Test loss: 0.0060. Test Acc: 80.2000. Time/epoch: 2.2290
saving best checkpoint at epoch: 0, Acc: 80.2
saving best checkpoint at epoch: 1, Acc: 85.18
saving best checkpoint at epoch: 2, Acc: 86.77
saving best checkpoint at epoch: 3, Acc: 87.11
saving best checkpoint at epoch: 4, Acc: 88.01
saving best checkpoint at epoch: 5, Acc: 88.54
saving best checkpoint at epoch: 6, Acc: 89.2
saving best checkpoint at epoch: 7, Acc: 89.7
saving best checkpoint at epoch: 8, Acc: 90.1
saving best checkpoint at epoch: 9, Acc: 90.15
EPOCH 10. Progress: 10.0%.
Train loss: 0.0017. Train Acc: 90.5350, Test loss: 0.0017. Test Acc: 90.6100. Time/epoch: 2.2001
saving best checkpoint at epoch: 10, Acc: 90.61
saving best checkpoint at epoch: 11, Acc: 90.96
saving best checkpoint at epoch: 12, Acc: 91.17
saving best checkpoint at epoch: 13, Acc: 91.55
saving best checkpoint at epoch: 15, Acc: 91.6
saving best checkpoint at epoch: 16, Acc: 91.67
saving best checkpoint at epoch: 17, Acc: 91.97
saving best checkpoint at epoch: 19, Acc: 92.11
EPOCH 20. Progress: 20.0%.
Train loss: 0.0014. Train Acc: 92.0225, Test loss: 0.0015. Test Acc: 92.1000. Time/epoch: 2.1775
saving best checkpoint at epoch: 22, Acc: 92.21
saving best checkpoint at epoch: 23, Acc: 92.36
saving best checkpoint at epoch: 24, Acc: 92.42
saving best checkpoint at epoch: 27, Acc: 92.76
saving best checkpoint at epoch: 28, Acc: 92.78
saving best checkpoint at epoch: 29, Acc: 92.9
EPOCH 30. Progress: 30.0%.
Train loss: 0.0013. Train Acc: 92.9600, Test loss: 0.0013. Test Acc: 92.8500. Time/epoch: 2.1839
saving best checkpoint at epoch: 32, Acc: 93.14
saving best checkpoint at epoch: 33, Acc: 93.32
saving best checkpoint at epoch: 37, Acc: 93.35
saving best checkpoint at epoch: 39, Acc: 93.65
EPOCH 40. Progress: 40.0%.
Train loss: 0.0012. Train Acc: 93.6125, Test loss: 0.0012. Test Acc: 93.4700. Time/epoch: 2.1837
saving best checkpoint at epoch: 41, Acc: 93.66
saving best checkpoint at epoch: 42, Acc: 93.67
saving best checkpoint at epoch: 44, Acc: 93.92
saving best checkpoint at epoch: 45, Acc: 94.03
saving best checkpoint at epoch: 47, Acc: 94.17
saving best checkpoint at epoch: 49, Acc: 94.2
EPOCH 50. Progress: 50.0%.
Train loss: 0.0011. Train Acc: 94.1275, Test loss: 0.0011. Test Acc: 94.0700. Time/epoch: 2.2040
saving best checkpoint at epoch: 51, Acc: 94.38
saving best checkpoint at epoch: 52, Acc: 94.41
saving best checkpoint at epoch: 55, Acc: 94.58
saving best checkpoint at epoch: 59, Acc: 94.75
EPOCH 60. Progress: 60.0%.
Train loss: 0.0010. Train Acc: 94.9050, Test loss: 0.0011. Test Acc: 94.8900. Time/epoch: 2.1959
saving best checkpoint at epoch: 60, Acc: 94.89
saving best checkpoint at epoch: 63, Acc: 94.99
saving best checkpoint at epoch: 65, Acc: 95.01
saving best checkpoint at epoch: 67, Acc: 95.08
EPOCH 70. Progress: 70.0%.
Train loss: 0.0009. Train Acc: 95.2050, Test loss: 0.0010. Test Acc: 95.0600. Time/epoch: 2.1889
saving best checkpoint at epoch: 71, Acc: 95.19
saving best checkpoint at epoch: 72, Acc: 95.22
saving best checkpoint at epoch: 74, Acc: 95.23
saving best checkpoint at epoch: 77, Acc: 95.34
saving best checkpoint at epoch: 79, Acc: 95.42
EPOCH 80. Progress: 80.0%.
Train loss: 0.0009. Train Acc: 95.6200, Test loss: 0.0010. Test Acc: 95.3700. Time/epoch: 2.0380
saving best checkpoint at epoch: 82, Acc: 95.47
saving best checkpoint at epoch: 85, Acc: 95.55
saving best checkpoint at epoch: 86, Acc: 95.59
EPOCH 90. Progress: 90.0%.
Train loss: 0.0008. Train Acc: 95.7850, Test loss: 0.0009. Test Acc: 95.4200. Time/epoch: 2.1806
saving best checkpoint at epoch: 92, Acc: 95.6
saving best checkpoint at epoch: 95, Acc: 95.69
saving best checkpoint at epoch: 99, Acc: 95.72
EPOCH 100. Progress: 100.0%.
Train loss: 0.0008. Train Acc: 95.9600, Test loss: 0.0009. Test Acc: 95.8000. Time/epoch: 2.2229
saving best checkpoint at epoch: 100, Acc: 95.8
Run history:
Accuracy/train | ▁▄▅▅▆▆▆▆▆▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇███████████████ |
Accuracy/val | ▁▄▅▅▆▆▆▆▆▆▆▇▇▇▇▇▇▇▇▇▇▇▇▇████████████████ |
Loss/train | █▄▃▂▂▂▂▂▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▄▃▂▂▂▂▂▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 95.96 |
Accuracy/val | 95.8 |
Loss/train | 0.00084 |
Loss/val | 0.0009 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_114748-5n56vdas/logs
wandb: Agent Starting Run: q1sio3r7 with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 1e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_115144-q1sio3r7
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0027. Train Acc: 44.4175, Test loss: 0.0027. Test Acc: 43.7000. Time/epoch: 1.5729
saving best checkpoint at epoch: 0, Acc: 43.7
saving best checkpoint at epoch: 1, Acc: 64.22
saving best checkpoint at epoch: 2, Acc: 80.43
saving best checkpoint at epoch: 3, Acc: 83.88
saving best checkpoint at epoch: 4, Acc: 85.42
saving best checkpoint at epoch: 5, Acc: 86.34
saving best checkpoint at epoch: 6, Acc: 87.03
saving best checkpoint at epoch: 7, Acc: 87.7
saving best checkpoint at epoch: 8, Acc: 88.37
saving best checkpoint at epoch: 9, Acc: 88.98
EPOCH 10. Progress: 10.0%.
Train loss: 0.0007. Train Acc: 89.6000, Test loss: 0.0007. Test Acc: 89.4800. Time/epoch: 1.6844
saving best checkpoint at epoch: 10, Acc: 89.48
saving best checkpoint at epoch: 11, Acc: 89.77
saving best checkpoint at epoch: 12, Acc: 90.51
saving best checkpoint at epoch: 13, Acc: 90.97
saving best checkpoint at epoch: 14, Acc: 91.19
saving best checkpoint at epoch: 15, Acc: 91.22
saving best checkpoint at epoch: 16, Acc: 91.71
saving best checkpoint at epoch: 17, Acc: 91.94
saving best checkpoint at epoch: 18, Acc: 92.23
saving best checkpoint at epoch: 19, Acc: 92.51
EPOCH 20. Progress: 20.0%.
Train loss: 0.0004. Train Acc: 92.5600, Test loss: 0.0004. Test Acc: 92.4900. Time/epoch: 1.5514
saving best checkpoint at epoch: 21, Acc: 92.77
saving best checkpoint at epoch: 22, Acc: 93.13
saving best checkpoint at epoch: 24, Acc: 93.19
saving best checkpoint at epoch: 25, Acc: 93.29
saving best checkpoint at epoch: 26, Acc: 93.38
saving best checkpoint at epoch: 27, Acc: 93.4
saving best checkpoint at epoch: 28, Acc: 93.45
EPOCH 30. Progress: 30.0%.
Train loss: 0.0003. Train Acc: 93.2400, Test loss: 0.0003. Test Acc: 93.4300. Time/epoch: 1.6860
saving best checkpoint at epoch: 31, Acc: 93.75
saving best checkpoint at epoch: 33, Acc: 93.8
saving best checkpoint at epoch: 34, Acc: 93.91
saving best checkpoint at epoch: 37, Acc: 94.02
EPOCH 40. Progress: 40.0%.
Train loss: 0.0003. Train Acc: 93.9200, Test loss: 0.0003. Test Acc: 93.9200. Time/epoch: 1.5416
saving best checkpoint at epoch: 41, Acc: 94.1
saving best checkpoint at epoch: 43, Acc: 94.2
saving best checkpoint at epoch: 45, Acc: 94.27
saving best checkpoint at epoch: 46, Acc: 94.33
saving best checkpoint at epoch: 47, Acc: 94.38
saving best checkpoint at epoch: 49, Acc: 94.49
EPOCH 50. Progress: 50.0%.
Train loss: 0.0003. Train Acc: 94.4425, Test loss: 0.0003. Test Acc: 94.2900. Time/epoch: 1.7196
saving best checkpoint at epoch: 52, Acc: 94.54
saving best checkpoint at epoch: 57, Acc: 94.64
EPOCH 60. Progress: 60.0%.
Train loss: 0.0003. Train Acc: 94.6550, Test loss: 0.0003. Test Acc: 94.5200. Time/epoch: 1.5481
saving best checkpoint at epoch: 62, Acc: 94.75
saving best checkpoint at epoch: 63, Acc: 94.78
saving best checkpoint at epoch: 67, Acc: 94.83
EPOCH 70. Progress: 70.0%.
Train loss: 0.0002. Train Acc: 95.1275, Test loss: 0.0003. Test Acc: 94.8800. Time/epoch: 1.5508
saving best checkpoint at epoch: 70, Acc: 94.88
saving best checkpoint at epoch: 73, Acc: 94.91
saving best checkpoint at epoch: 77, Acc: 94.97
saving best checkpoint at epoch: 78, Acc: 95.01
EPOCH 80. Progress: 80.0%.
Train loss: 0.0002. Train Acc: 95.2250, Test loss: 0.0002. Test Acc: 95.0900. Time/epoch: 1.5450
saving best checkpoint at epoch: 80, Acc: 95.09
saving best checkpoint at epoch: 83, Acc: 95.14
saving best checkpoint at epoch: 88, Acc: 95.19
EPOCH 90. Progress: 90.0%.
Train loss: 0.0002. Train Acc: 95.4175, Test loss: 0.0002. Test Acc: 95.0800. Time/epoch: 1.5519
saving best checkpoint at epoch: 93, Acc: 95.31
saving best checkpoint at epoch: 98, Acc: 95.35
EPOCH 100. Progress: 100.0%.
Train loss: 0.0002. Train Acc: 95.6300, Test loss: 0.0002. Test Acc: 95.3200. Time/epoch: 1.6873
Run history:
Accuracy/train | ▁▆▇▇▇▇▇▇████████████████████████████████ |
Accuracy/val | ▁▆▇▇▇▇▇█████████████████████████████████ |
Loss/train | █▆▃▃▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▆▃▃▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 95.63 |
Accuracy/val | 95.32 |
Loss/train | 0.00022 |
Loss/val | 0.00023 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_115144-q1sio3r7/logs
wandb: Agent Starting Run: fy142do3 with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 1e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_115444-fy142do3
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0024. Train Acc: 59.1600, Test loss: 0.0024. Test Acc: 59.5400. Time/epoch: 1.5671
saving best checkpoint at epoch: 0, Acc: 59.54
saving best checkpoint at epoch: 1, Acc: 78.64
saving best checkpoint at epoch: 2, Acc: 82.26
saving best checkpoint at epoch: 3, Acc: 83.73
saving best checkpoint at epoch: 4, Acc: 85.86
saving best checkpoint at epoch: 5, Acc: 86.8
saving best checkpoint at epoch: 6, Acc: 87.06
saving best checkpoint at epoch: 7, Acc: 87.7
saving best checkpoint at epoch: 8, Acc: 88.06
saving best checkpoint at epoch: 9, Acc: 88.22
EPOCH 10. Progress: 10.0%.
Train loss: 0.0005. Train Acc: 88.4350, Test loss: 0.0005. Test Acc: 88.4800. Time/epoch: 1.5522
saving best checkpoint at epoch: 10, Acc: 88.48
saving best checkpoint at epoch: 11, Acc: 88.61
saving best checkpoint at epoch: 12, Acc: 88.67
saving best checkpoint at epoch: 13, Acc: 88.99
saving best checkpoint at epoch: 14, Acc: 89.26
saving best checkpoint at epoch: 15, Acc: 89.88
saving best checkpoint at epoch: 16, Acc: 90.53
saving best checkpoint at epoch: 17, Acc: 91.03
saving best checkpoint at epoch: 18, Acc: 91.39
saving best checkpoint at epoch: 19, Acc: 91.69
EPOCH 20. Progress: 20.0%.
Train loss: 0.0004. Train Acc: 92.1900, Test loss: 0.0004. Test Acc: 91.9800. Time/epoch: 1.6872
saving best checkpoint at epoch: 20, Acc: 91.98
saving best checkpoint at epoch: 21, Acc: 92.17
saving best checkpoint at epoch: 22, Acc: 92.58
saving best checkpoint at epoch: 23, Acc: 92.76
saving best checkpoint at epoch: 24, Acc: 92.82
saving best checkpoint at epoch: 25, Acc: 93.06
saving best checkpoint at epoch: 26, Acc: 93.24
saving best checkpoint at epoch: 27, Acc: 93.26
saving best checkpoint at epoch: 28, Acc: 93.48
saving best checkpoint at epoch: 29, Acc: 93.57
EPOCH 30. Progress: 30.0%.
Train loss: 0.0003. Train Acc: 93.6275, Test loss: 0.0003. Test Acc: 93.6400. Time/epoch: 1.5517
saving best checkpoint at epoch: 30, Acc: 93.64
saving best checkpoint at epoch: 31, Acc: 93.85
saving best checkpoint at epoch: 32, Acc: 93.91
saving best checkpoint at epoch: 33, Acc: 93.98
saving best checkpoint at epoch: 36, Acc: 94.07
saving best checkpoint at epoch: 38, Acc: 94.31
EPOCH 40. Progress: 40.0%.
Train loss: 0.0003. Train Acc: 94.0300, Test loss: 0.0003. Test Acc: 94.2100. Time/epoch: 1.6954
saving best checkpoint at epoch: 41, Acc: 94.45
saving best checkpoint at epoch: 44, Acc: 94.5
saving best checkpoint at epoch: 45, Acc: 94.66
saving best checkpoint at epoch: 46, Acc: 94.68
saving best checkpoint at epoch: 47, Acc: 94.78
EPOCH 50. Progress: 50.0%.
Train loss: 0.0003. Train Acc: 94.5575, Test loss: 0.0003. Test Acc: 94.5800. Time/epoch: 1.5592
saving best checkpoint at epoch: 51, Acc: 94.93
saving best checkpoint at epoch: 54, Acc: 94.96
saving best checkpoint at epoch: 56, Acc: 95.0
saving best checkpoint at epoch: 57, Acc: 95.1
saving best checkpoint at epoch: 58, Acc: 95.12
EPOCH 60. Progress: 60.0%.
Train loss: 0.0002. Train Acc: 95.0225, Test loss: 0.0003. Test Acc: 95.1600. Time/epoch: 1.6906
saving best checkpoint at epoch: 60, Acc: 95.16
saving best checkpoint at epoch: 61, Acc: 95.27
saving best checkpoint at epoch: 63, Acc: 95.28
saving best checkpoint at epoch: 65, Acc: 95.34
saving best checkpoint at epoch: 66, Acc: 95.36
saving best checkpoint at epoch: 69, Acc: 95.46
EPOCH 70. Progress: 70.0%.
Train loss: 0.0002. Train Acc: 95.3225, Test loss: 0.0002. Test Acc: 95.4800. Time/epoch: 1.5453
saving best checkpoint at epoch: 70, Acc: 95.48
saving best checkpoint at epoch: 77, Acc: 95.58
saving best checkpoint at epoch: 78, Acc: 95.59
saving best checkpoint at epoch: 79, Acc: 95.66
EPOCH 80. Progress: 80.0%.
Train loss: 0.0002. Train Acc: 95.5175, Test loss: 0.0002. Test Acc: 95.4900. Time/epoch: 1.5550
saving best checkpoint at epoch: 81, Acc: 95.71
saving best checkpoint at epoch: 87, Acc: 95.79
saving best checkpoint at epoch: 88, Acc: 95.8
EPOCH 90. Progress: 90.0%.
Train loss: 0.0002. Train Acc: 95.8400, Test loss: 0.0002. Test Acc: 95.6200. Time/epoch: 1.5470
saving best checkpoint at epoch: 91, Acc: 95.9
saving best checkpoint at epoch: 96, Acc: 95.94
EPOCH 100. Progress: 100.0%.
Train loss: 0.0002. Train Acc: 96.0475, Test loss: 0.0002. Test Acc: 95.9700. Time/epoch: 1.5513
saving best checkpoint at epoch: 100, Acc: 95.97
Run history:
Accuracy/train | ▁▅▆▆▇▇▇▇▇▇▇▇████████████████████████████ |
Accuracy/val | ▁▅▆▆▇▇▇▇▇▇▇█████████████████████████████ |
Loss/train | █▄▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▄▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 96.0475 |
Accuracy/val | 95.97 |
Loss/train | 0.0002 |
Loss/val | 0.00022 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_115444-fy142do3/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: xwwa3hdt with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 3e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_115750-xwwa3hdt
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0020. Train Acc: 70.3500, Test loss: 0.0021. Test Acc: 70.4900. Time/epoch: 1.7995
saving best checkpoint at epoch: 0, Acc: 70.49
saving best checkpoint at epoch: 1, Acc: 84.16
saving best checkpoint at epoch: 2, Acc: 88.56
saving best checkpoint at epoch: 3, Acc: 88.75
saving best checkpoint at epoch: 4, Acc: 89.99
saving best checkpoint at epoch: 5, Acc: 90.92
saving best checkpoint at epoch: 6, Acc: 91.67
saving best checkpoint at epoch: 7, Acc: 91.83
saving best checkpoint at epoch: 8, Acc: 92.25
saving best checkpoint at epoch: 9, Acc: 92.5
EPOCH 10. Progress: 10.0%.
Train loss: 0.0003. Train Acc: 93.0300, Test loss: 0.0004. Test Acc: 92.5200. Time/epoch: 1.6883
saving best checkpoint at epoch: 10, Acc: 92.52
saving best checkpoint at epoch: 11, Acc: 92.72
saving best checkpoint at epoch: 12, Acc: 92.93
saving best checkpoint at epoch: 14, Acc: 93.18
saving best checkpoint at epoch: 15, Acc: 93.5
saving best checkpoint at epoch: 16, Acc: 93.66
saving best checkpoint at epoch: 17, Acc: 93.74
saving best checkpoint at epoch: 18, Acc: 93.8
saving best checkpoint at epoch: 19, Acc: 93.88
EPOCH 20. Progress: 20.0%.
Train loss: 0.0003. Train Acc: 93.8475, Test loss: 0.0003. Test Acc: 93.9300. Time/epoch: 1.5430
saving best checkpoint at epoch: 20, Acc: 93.93
saving best checkpoint at epoch: 21, Acc: 94.22
saving best checkpoint at epoch: 22, Acc: 94.3
saving best checkpoint at epoch: 23, Acc: 94.43
saving best checkpoint at epoch: 28, Acc: 94.66
EPOCH 30. Progress: 30.0%.
Train loss: 0.0003. Train Acc: 94.6900, Test loss: 0.0003. Test Acc: 94.4200. Time/epoch: 1.6902
saving best checkpoint at epoch: 32, Acc: 94.84
saving best checkpoint at epoch: 34, Acc: 94.86
saving best checkpoint at epoch: 39, Acc: 94.93
EPOCH 40. Progress: 40.0%.
Train loss: 0.0002. Train Acc: 95.3425, Test loss: 0.0003. Test Acc: 95.0700. Time/epoch: 1.5443
saving best checkpoint at epoch: 40, Acc: 95.07
saving best checkpoint at epoch: 41, Acc: 95.16
saving best checkpoint at epoch: 43, Acc: 95.27
saving best checkpoint at epoch: 47, Acc: 95.32
EPOCH 50. Progress: 50.0%.
Train loss: 0.0002. Train Acc: 95.5425, Test loss: 0.0002. Test Acc: 95.1400. Time/epoch: 1.5671
saving best checkpoint at epoch: 52, Acc: 95.42
saving best checkpoint at epoch: 54, Acc: 95.59
saving best checkpoint at epoch: 58, Acc: 95.65
EPOCH 60. Progress: 60.0%.
Train loss: 0.0002. Train Acc: 95.9150, Test loss: 0.0002. Test Acc: 95.6300. Time/epoch: 1.5515
saving best checkpoint at epoch: 62, Acc: 95.66
saving best checkpoint at epoch: 64, Acc: 95.83
saving best checkpoint at epoch: 66, Acc: 95.88
EPOCH 70. Progress: 70.0%.
Train loss: 0.0002. Train Acc: 96.2375, Test loss: 0.0002. Test Acc: 95.6600. Time/epoch: 1.5517
saving best checkpoint at epoch: 73, Acc: 96.03
EPOCH 80. Progress: 80.0%.
Train loss: 0.0002. Train Acc: 96.4450, Test loss: 0.0002. Test Acc: 95.9800. Time/epoch: 1.5488
saving best checkpoint at epoch: 81, Acc: 96.07
saving best checkpoint at epoch: 86, Acc: 96.1
EPOCH 90. Progress: 90.0%.
Train loss: 0.0002. Train Acc: 96.7575, Test loss: 0.0002. Test Acc: 96.2500. Time/epoch: 1.6915
saving best checkpoint at epoch: 90, Acc: 96.25
EPOCH 100. Progress: 100.0%.
Train loss: 0.0002. Train Acc: 96.7025, Test loss: 0.0002. Test Acc: 95.9900. Time/epoch: 1.5402
Run history:
Accuracy/train | ▁▆▇▇▇▇▇▇▇▇▇▇▇█▇█████████████████████████ |
Accuracy/val | ▁▆▇▇▇▇▇▇▇█▇█████████████████████████████ |
Loss/train | █▃▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▃▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 96.7025 |
Accuracy/val | 95.99 |
Loss/train | 0.00017 |
Loss/val | 0.0002 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_115750-xwwa3hdt/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: 85p945tx with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 3e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_120055-85p945tx
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0015. Train Acc: 73.2925, Test loss: 0.0015. Test Acc: 73.4700. Time/epoch: 1.5700
saving best checkpoint at epoch: 0, Acc: 73.47
saving best checkpoint at epoch: 1, Acc: 85.68
saving best checkpoint at epoch: 2, Acc: 89.89
saving best checkpoint at epoch: 3, Acc: 91.79
saving best checkpoint at epoch: 4, Acc: 92.32
saving best checkpoint at epoch: 5, Acc: 93.19
saving best checkpoint at epoch: 6, Acc: 93.72
saving best checkpoint at epoch: 7, Acc: 93.9
saving best checkpoint at epoch: 8, Acc: 94.1
saving best checkpoint at epoch: 9, Acc: 94.3
EPOCH 10. Progress: 10.0%.
Train loss: 0.0003. Train Acc: 94.4825, Test loss: 0.0003. Test Acc: 94.4600. Time/epoch: 1.6927
saving best checkpoint at epoch: 10, Acc: 94.46
saving best checkpoint at epoch: 13, Acc: 94.64
saving best checkpoint at epoch: 14, Acc: 94.82
saving best checkpoint at epoch: 16, Acc: 94.85
saving best checkpoint at epoch: 17, Acc: 94.96
saving best checkpoint at epoch: 18, Acc: 95.02
saving best checkpoint at epoch: 19, Acc: 95.19
EPOCH 20. Progress: 20.0%.
Train loss: 0.0002. Train Acc: 95.0475, Test loss: 0.0003. Test Acc: 94.8000. Time/epoch: 1.5506
saving best checkpoint at epoch: 23, Acc: 95.34
saving best checkpoint at epoch: 25, Acc: 95.47
EPOCH 30. Progress: 30.0%.
Train loss: 0.0002. Train Acc: 95.4700, Test loss: 0.0003. Test Acc: 95.2200. Time/epoch: 1.5551
saving best checkpoint at epoch: 32, Acc: 95.57
saving best checkpoint at epoch: 33, Acc: 95.68
saving best checkpoint at epoch: 35, Acc: 95.76
EPOCH 40. Progress: 40.0%.
Train loss: 0.0002. Train Acc: 95.8325, Test loss: 0.0002. Test Acc: 95.5100. Time/epoch: 1.5554
saving best checkpoint at epoch: 41, Acc: 95.92
saving best checkpoint at epoch: 45, Acc: 96.09
saving best checkpoint at epoch: 47, Acc: 96.21
EPOCH 50. Progress: 50.0%.
Train loss: 0.0002. Train Acc: 96.2850, Test loss: 0.0002. Test Acc: 95.8500. Time/epoch: 1.7010
saving best checkpoint at epoch: 54, Acc: 96.23
saving best checkpoint at epoch: 55, Acc: 96.33
EPOCH 60. Progress: 60.0%.
Train loss: 0.0002. Train Acc: 96.5200, Test loss: 0.0002. Test Acc: 96.0900. Time/epoch: 1.5582
saving best checkpoint at epoch: 62, Acc: 96.47
saving best checkpoint at epoch: 68, Acc: 96.51
EPOCH 70. Progress: 70.0%.
Train loss: 0.0002. Train Acc: 96.8900, Test loss: 0.0002. Test Acc: 96.3900. Time/epoch: 1.6917
saving best checkpoint at epoch: 76, Acc: 96.52
EPOCH 80. Progress: 80.0%.
Train loss: 0.0002. Train Acc: 96.9350, Test loss: 0.0002. Test Acc: 96.5000. Time/epoch: 1.5465
saving best checkpoint at epoch: 84, Acc: 96.58
saving best checkpoint at epoch: 85, Acc: 96.63
EPOCH 90. Progress: 90.0%.
Train loss: 0.0001. Train Acc: 97.1150, Test loss: 0.0002. Test Acc: 96.5800. Time/epoch: 1.7147
saving best checkpoint at epoch: 93, Acc: 96.71
saving best checkpoint at epoch: 98, Acc: 96.75
EPOCH 100. Progress: 100.0%.
Train loss: 0.0001. Train Acc: 97.2425, Test loss: 0.0002. Test Acc: 96.7800. Time/epoch: 1.5489
saving best checkpoint at epoch: 100, Acc: 96.78
Run history:
Accuracy/train | ▁▆▇▇▇▇▇▇▇▇██▇███████████████████████████ |
Accuracy/val | ▁▆▇▇▇▇▇▇▇███████████████████████████████ |
Loss/train | █▃▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▃▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 97.2425 |
Accuracy/val | 96.78 |
Loss/train | 0.00014 |
Loss/val | 0.00018 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_120055-85p945tx/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: slt84k80 with config:
wandb: batch_size: 128
wandb: epochs: 100
wandb: learning_rate: 1e-05
wandb: optimizer: adam
wandb: weight_decay: 0.005
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_120401-slt84k80
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0058. Train Acc: 72.7375, Test loss: 0.0058. Test Acc: 72.9500. Time/epoch: 2.2329
saving best checkpoint at epoch: 0, Acc: 72.95
saving best checkpoint at epoch: 1, Acc: 88.01
saving best checkpoint at epoch: 2, Acc: 90.27
saving best checkpoint at epoch: 3, Acc: 91.1
saving best checkpoint at epoch: 4, Acc: 91.73
saving best checkpoint at epoch: 5, Acc: 92.22
saving best checkpoint at epoch: 6, Acc: 92.26
saving best checkpoint at epoch: 7, Acc: 92.74
saving best checkpoint at epoch: 8, Acc: 92.95
saving best checkpoint at epoch: 9, Acc: 93.06
EPOCH 10. Progress: 10.0%.
Train loss: 0.0012. Train Acc: 93.6800, Test loss: 0.0013. Test Acc: 93.1500. Time/epoch: 2.1843
saving best checkpoint at epoch: 10, Acc: 93.15
saving best checkpoint at epoch: 11, Acc: 93.57
saving best checkpoint at epoch: 12, Acc: 93.72
saving best checkpoint at epoch: 14, Acc: 93.99
saving best checkpoint at epoch: 15, Acc: 94.0
saving best checkpoint at epoch: 16, Acc: 94.31
saving best checkpoint at epoch: 19, Acc: 94.35
EPOCH 20. Progress: 20.0%.
Train loss: 0.0011. Train Acc: 94.4975, Test loss: 0.0011. Test Acc: 94.3200. Time/epoch: 2.1747
saving best checkpoint at epoch: 22, Acc: 94.56
saving best checkpoint at epoch: 23, Acc: 94.63
saving best checkpoint at epoch: 24, Acc: 94.67
saving best checkpoint at epoch: 25, Acc: 94.81
saving best checkpoint at epoch: 29, Acc: 94.87
EPOCH 30. Progress: 30.0%.
Train loss: 0.0010. Train Acc: 95.2125, Test loss: 0.0010. Test Acc: 94.9400. Time/epoch: 2.1772
saving best checkpoint at epoch: 30, Acc: 94.94
saving best checkpoint at epoch: 31, Acc: 95.05
saving best checkpoint at epoch: 33, Acc: 95.13
saving best checkpoint at epoch: 36, Acc: 95.28
saving best checkpoint at epoch: 38, Acc: 95.33
EPOCH 40. Progress: 40.0%.
Train loss: 0.0009. Train Acc: 95.7600, Test loss: 0.0010. Test Acc: 95.4000. Time/epoch: 2.1743
saving best checkpoint at epoch: 40, Acc: 95.4
saving best checkpoint at epoch: 43, Acc: 95.46
saving best checkpoint at epoch: 45, Acc: 95.53
saving best checkpoint at epoch: 46, Acc: 95.58
saving best checkpoint at epoch: 48, Acc: 95.64
EPOCH 50. Progress: 50.0%.
Train loss: 0.0008. Train Acc: 95.8925, Test loss: 0.0009. Test Acc: 95.4700. Time/epoch: 2.1941
saving best checkpoint at epoch: 55, Acc: 95.78
saving best checkpoint at epoch: 59, Acc: 95.83
EPOCH 60. Progress: 60.0%.
Train loss: 0.0008. Train Acc: 96.2175, Test loss: 0.0009. Test Acc: 95.8500. Time/epoch: 2.2073
saving best checkpoint at epoch: 60, Acc: 95.85
saving best checkpoint at epoch: 61, Acc: 95.97
saving best checkpoint at epoch: 68, Acc: 96.06
EPOCH 70. Progress: 70.0%.
Train loss: 0.0008. Train Acc: 96.3325, Test loss: 0.0008. Test Acc: 95.9700. Time/epoch: 2.2120
saving best checkpoint at epoch: 73, Acc: 96.17
saving best checkpoint at epoch: 79, Acc: 96.35
EPOCH 80. Progress: 80.0%.
Train loss: 0.0007. Train Acc: 96.5350, Test loss: 0.0008. Test Acc: 96.1000. Time/epoch: 2.0475
saving best checkpoint at epoch: 88, Acc: 96.42
EPOCH 90. Progress: 90.0%.
Train loss: 0.0007. Train Acc: 96.5850, Test loss: 0.0008. Test Acc: 96.2200. Time/epoch: 2.1835
EPOCH 100. Progress: 100.0%.
Train loss: 0.0007. Train Acc: 96.8950, Test loss: 0.0007. Test Acc: 96.4800. Time/epoch: 2.1953
saving best checkpoint at epoch: 100, Acc: 96.48
Run history:
Accuracy/train | ▁▆▇▇▇▇▇▇▇▇▇▇████████████████████████████ |
Accuracy/val | ▁▆▇▇▇▇▇▇▇▇██████████████████████████████ |
Loss/train | █▃▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▃▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 96.895 |
Accuracy/val | 96.48 |
Loss/train | 0.00066 |
Loss/val | 0.00075 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_120401-slt84k80/logs
wandb: Agent Starting Run: vsizn60t with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 1e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_120758-vsizn60t
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0026. Train Acc: 62.8525, Test loss: 0.0026. Test Acc: 63.0500. Time/epoch: 1.6718
saving best checkpoint at epoch: 0, Acc: 63.05
saving best checkpoint at epoch: 1, Acc: 78.97
saving best checkpoint at epoch: 2, Acc: 81.73
saving best checkpoint at epoch: 3, Acc: 83.82
saving best checkpoint at epoch: 4, Acc: 86.09
saving best checkpoint at epoch: 5, Acc: 87.43
saving best checkpoint at epoch: 6, Acc: 88.01
saving best checkpoint at epoch: 7, Acc: 88.61
saving best checkpoint at epoch: 8, Acc: 89.36
saving best checkpoint at epoch: 9, Acc: 89.6
EPOCH 10. Progress: 10.0%.
Train loss: 0.0005. Train Acc: 90.2900, Test loss: 0.0005. Test Acc: 90.2300. Time/epoch: 1.5514
saving best checkpoint at epoch: 10, Acc: 90.23
saving best checkpoint at epoch: 11, Acc: 90.51
saving best checkpoint at epoch: 12, Acc: 90.79
saving best checkpoint at epoch: 13, Acc: 90.9
saving best checkpoint at epoch: 14, Acc: 91.21
saving best checkpoint at epoch: 15, Acc: 91.25
saving best checkpoint at epoch: 16, Acc: 91.39
saving best checkpoint at epoch: 18, Acc: 91.74
saving best checkpoint at epoch: 19, Acc: 91.9
EPOCH 20. Progress: 20.0%.
Train loss: 0.0004. Train Acc: 92.3450, Test loss: 0.0004. Test Acc: 92.0300. Time/epoch: 1.5501
saving best checkpoint at epoch: 20, Acc: 92.03
saving best checkpoint at epoch: 21, Acc: 92.32
saving best checkpoint at epoch: 22, Acc: 92.41
saving best checkpoint at epoch: 24, Acc: 92.46
saving best checkpoint at epoch: 25, Acc: 92.81
saving best checkpoint at epoch: 27, Acc: 92.94
saving best checkpoint at epoch: 29, Acc: 93.11
EPOCH 30. Progress: 30.0%.
Train loss: 0.0003. Train Acc: 93.2250, Test loss: 0.0003. Test Acc: 93.1100. Time/epoch: 1.6964
saving best checkpoint at epoch: 31, Acc: 93.18
saving best checkpoint at epoch: 32, Acc: 93.26
saving best checkpoint at epoch: 33, Acc: 93.3
saving best checkpoint at epoch: 34, Acc: 93.4
saving best checkpoint at epoch: 35, Acc: 93.48
saving best checkpoint at epoch: 36, Acc: 93.53
saving best checkpoint at epoch: 37, Acc: 93.56
saving best checkpoint at epoch: 39, Acc: 93.78
EPOCH 40. Progress: 40.0%.
Train loss: 0.0003. Train Acc: 93.7650, Test loss: 0.0003. Test Acc: 93.7100. Time/epoch: 1.5660
saving best checkpoint at epoch: 41, Acc: 93.91
saving best checkpoint at epoch: 45, Acc: 94.06
saving best checkpoint at epoch: 46, Acc: 94.19
saving best checkpoint at epoch: 48, Acc: 94.23
EPOCH 50. Progress: 50.0%.
Train loss: 0.0003. Train Acc: 94.2600, Test loss: 0.0003. Test Acc: 94.1700. Time/epoch: 1.5808
saving best checkpoint at epoch: 52, Acc: 94.24
saving best checkpoint at epoch: 53, Acc: 94.29
saving best checkpoint at epoch: 54, Acc: 94.3
saving best checkpoint at epoch: 55, Acc: 94.42
saving best checkpoint at epoch: 56, Acc: 94.53
saving best checkpoint at epoch: 57, Acc: 94.56
saving best checkpoint at epoch: 59, Acc: 94.62
EPOCH 60. Progress: 60.0%.
Train loss: 0.0003. Train Acc: 94.6925, Test loss: 0.0003. Test Acc: 94.6100. Time/epoch: 1.5503
saving best checkpoint at epoch: 61, Acc: 94.71
saving best checkpoint at epoch: 63, Acc: 94.81
saving best checkpoint at epoch: 66, Acc: 94.88
saving best checkpoint at epoch: 68, Acc: 94.97
EPOCH 70. Progress: 70.0%.
Train loss: 0.0002. Train Acc: 95.0325, Test loss: 0.0003. Test Acc: 94.9400. Time/epoch: 1.5489
saving best checkpoint at epoch: 71, Acc: 95.02
saving best checkpoint at epoch: 73, Acc: 95.21
saving best checkpoint at epoch: 78, Acc: 95.38
EPOCH 80. Progress: 80.0%.
Train loss: 0.0002. Train Acc: 95.4675, Test loss: 0.0003. Test Acc: 95.2600. Time/epoch: 1.6943
saving best checkpoint at epoch: 83, Acc: 95.47
saving best checkpoint at epoch: 85, Acc: 95.56
EPOCH 90. Progress: 90.0%.
Train loss: 0.0002. Train Acc: 95.6750, Test loss: 0.0002. Test Acc: 95.5200. Time/epoch: 1.5546
saving best checkpoint at epoch: 93, Acc: 95.64
saving best checkpoint at epoch: 97, Acc: 95.71
EPOCH 100. Progress: 100.0%.
Train loss: 0.0002. Train Acc: 95.7425, Test loss: 0.0002. Test Acc: 95.6300. Time/epoch: 1.6916
Run history:
Accuracy/train | ▁▅▆▇▇▇▇▇▇▇▇▇▇▇▇█████████████████████████ |
Accuracy/val | ▁▅▆▆▇▇▇▇▇▇▇▇▇▇██████████████████████████ |
Loss/train | █▄▃▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▄▃▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 95.7425 |
Accuracy/val | 95.63 |
Loss/train | 0.00022 |
Loss/val | 0.00024 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_120758-vsizn60t/logs
wandb: Agent Starting Run: kb19l9b1 with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_121056-kb19l9b1
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0005. Train Acc: 89.0325, Test loss: 0.0005. Test Acc: 89.2500. Time/epoch: 1.5802
saving best checkpoint at epoch: 0, Acc: 89.25
saving best checkpoint at epoch: 1, Acc: 91.5
saving best checkpoint at epoch: 2, Acc: 92.61
saving best checkpoint at epoch: 3, Acc: 93.49
saving best checkpoint at epoch: 6, Acc: 94.29
saving best checkpoint at epoch: 8, Acc: 95.26
EPOCH 10. Progress: 10.0%.
Train loss: 0.0004. Train Acc: 91.8675, Test loss: 0.0004. Test Acc: 91.8100. Time/epoch: 1.5471
saving best checkpoint at epoch: 11, Acc: 95.43
saving best checkpoint at epoch: 12, Acc: 95.77
saving best checkpoint at epoch: 16, Acc: 96.02
EPOCH 20. Progress: 20.0%.
Train loss: 0.0002. Train Acc: 96.5300, Test loss: 0.0002. Test Acc: 96.1600. Time/epoch: 1.6889
saving best checkpoint at epoch: 20, Acc: 96.16
saving best checkpoint at epoch: 23, Acc: 96.18
saving best checkpoint at epoch: 24, Acc: 96.45
saving best checkpoint at epoch: 26, Acc: 96.76
saving best checkpoint at epoch: 28, Acc: 96.8
EPOCH 30. Progress: 30.0%.
Train loss: 0.0002. Train Acc: 96.9700, Test loss: 0.0002. Test Acc: 96.3800. Time/epoch: 1.5688
saving best checkpoint at epoch: 33, Acc: 96.87
saving best checkpoint at epoch: 36, Acc: 96.92
EPOCH 40. Progress: 40.0%.
Train loss: 0.0002. Train Acc: 96.7250, Test loss: 0.0002. Test Acc: 96.3500. Time/epoch: 1.6844
saving best checkpoint at epoch: 45, Acc: 97.18
EPOCH 50. Progress: 50.0%.
Train loss: 0.0001. Train Acc: 97.6050, Test loss: 0.0002. Test Acc: 96.8300. Time/epoch: 1.5565
EPOCH 60. Progress: 60.0%.
Train loss: 0.0001. Train Acc: 97.8050, Test loss: 0.0002. Test Acc: 96.7700. Time/epoch: 1.6868
saving best checkpoint at epoch: 65, Acc: 97.2
saving best checkpoint at epoch: 67, Acc: 97.35
EPOCH 70. Progress: 70.0%.
Train loss: 0.0001. Train Acc: 98.1675, Test loss: 0.0002. Test Acc: 97.1300. Time/epoch: 1.5394
saving best checkpoint at epoch: 72, Acc: 97.38
EPOCH 80. Progress: 80.0%.
Train loss: 0.0001. Train Acc: 98.1200, Test loss: 0.0002. Test Acc: 96.9100. Time/epoch: 1.5546
EPOCH 90. Progress: 90.0%.
Train loss: 0.0001. Train Acc: 98.8625, Test loss: 0.0002. Test Acc: 97.4200. Time/epoch: 1.5584
saving best checkpoint at epoch: 90, Acc: 97.42
EPOCH 100. Progress: 100.0%.
Train loss: 0.0001. Train Acc: 97.9950, Test loss: 0.0002. Test Acc: 96.6500. Time/epoch: 1.5454
Run history:
Accuracy/train | ▁▃▄▄▃▆▅▆▆▆▆▇▇▇▆▇▇▇▇▇▇▇▇▆▇▇▇▇▇▇█▇▇██████▇ |
Accuracy/val | ▁▄▄▅▃▇▆▆▇▇▇█▇█▇█▇▇▇██▇▇▆▇▇█████▇███████▇ |
Loss/train | █▆▅▅▆▃▄▄▃▃▃▃▃▂▃▂▂▂▃▂▂▂▂▃▂▂▂▂▂▂▂▂▂▁▁▁▁▁▁▂ |
Loss/val | █▅▅▄▅▂▃▃▂▂▂▁▂▁▂▁▂▂▂▁▁▂▂▃▂▂▁▂▁▁▁▂▂▁▁▁▁▂▁▃ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 97.995 |
Accuracy/val | 96.65 |
Loss/train | 0.00011 |
Loss/val | 0.00023 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_121056-kb19l9b1/logs
wandb: Agent Starting Run: zidsl9pf with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 3e-05
wandb: optimizer: adam
wandb: weight_decay: 0.005
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_121354-zidsl9pf
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0015. Train Acc: 73.1150, Test loss: 0.0015. Test Acc: 73.5300. Time/epoch: 1.7339
saving best checkpoint at epoch: 0, Acc: 73.53
saving best checkpoint at epoch: 1, Acc: 85.32
saving best checkpoint at epoch: 2, Acc: 88.59
saving best checkpoint at epoch: 3, Acc: 90.66
saving best checkpoint at epoch: 4, Acc: 91.54
saving best checkpoint at epoch: 5, Acc: 92.42
saving best checkpoint at epoch: 6, Acc: 92.92
saving best checkpoint at epoch: 8, Acc: 93.52
saving best checkpoint at epoch: 9, Acc: 93.79
EPOCH 10. Progress: 10.0%.
Train loss: 0.0003. Train Acc: 93.8025, Test loss: 0.0003. Test Acc: 93.6900. Time/epoch: 1.5523
saving best checkpoint at epoch: 12, Acc: 93.94
saving best checkpoint at epoch: 13, Acc: 94.3
saving best checkpoint at epoch: 14, Acc: 94.35
saving best checkpoint at epoch: 16, Acc: 94.74
EPOCH 20. Progress: 20.0%.
Train loss: 0.0002. Train Acc: 94.8075, Test loss: 0.0003. Test Acc: 94.7000. Time/epoch: 1.6871
saving best checkpoint at epoch: 21, Acc: 94.89
saving best checkpoint at epoch: 24, Acc: 95.03
saving best checkpoint at epoch: 25, Acc: 95.09
saving best checkpoint at epoch: 27, Acc: 95.26
saving best checkpoint at epoch: 29, Acc: 95.34
EPOCH 30. Progress: 30.0%.
Train loss: 0.0002. Train Acc: 95.5300, Test loss: 0.0002. Test Acc: 95.3500. Time/epoch: 1.5495
saving best checkpoint at epoch: 30, Acc: 95.35
saving best checkpoint at epoch: 32, Acc: 95.36
saving best checkpoint at epoch: 35, Acc: 95.57
saving best checkpoint at epoch: 36, Acc: 95.61
saving best checkpoint at epoch: 37, Acc: 95.62
EPOCH 40. Progress: 40.0%.
Train loss: 0.0002. Train Acc: 95.7150, Test loss: 0.0002. Test Acc: 95.6400. Time/epoch: 1.6993
saving best checkpoint at epoch: 40, Acc: 95.64
saving best checkpoint at epoch: 41, Acc: 95.79
saving best checkpoint at epoch: 44, Acc: 95.81
saving best checkpoint at epoch: 46, Acc: 95.91
EPOCH 50. Progress: 50.0%.
Train loss: 0.0002. Train Acc: 96.1875, Test loss: 0.0002. Test Acc: 95.6500. Time/epoch: 1.5522
saving best checkpoint at epoch: 56, Acc: 95.97
saving best checkpoint at epoch: 59, Acc: 96.04
EPOCH 60. Progress: 60.0%.
Train loss: 0.0002. Train Acc: 96.3400, Test loss: 0.0002. Test Acc: 95.8800. Time/epoch: 1.5565
saving best checkpoint at epoch: 62, Acc: 96.1
saving best checkpoint at epoch: 64, Acc: 96.16
EPOCH 70. Progress: 70.0%.
Train loss: 0.0002. Train Acc: 96.4100, Test loss: 0.0002. Test Acc: 95.9600. Time/epoch: 1.6978
saving best checkpoint at epoch: 76, Acc: 96.19
saving best checkpoint at epoch: 79, Acc: 96.21
EPOCH 80. Progress: 80.0%.
Train loss: 0.0002. Train Acc: 96.6600, Test loss: 0.0002. Test Acc: 96.1400. Time/epoch: 1.5489
saving best checkpoint at epoch: 81, Acc: 96.23
saving best checkpoint at epoch: 86, Acc: 96.26
saving best checkpoint at epoch: 88, Acc: 96.32
EPOCH 90. Progress: 90.0%.
Train loss: 0.0002. Train Acc: 96.7075, Test loss: 0.0002. Test Acc: 96.0900. Time/epoch: 1.7001
EPOCH 100. Progress: 100.0%.
Train loss: 0.0002. Train Acc: 96.9900, Test loss: 0.0002. Test Acc: 96.4900. Time/epoch: 1.5420
saving best checkpoint at epoch: 100, Acc: 96.49
Run history:
Accuracy/train | ▁▅▇▇▇▇▇▇▇▇▇█████████████████████████████ |
Accuracy/val | ▁▆▇▇▇▇▇▇▇▇██████████████████████████████ |
Loss/train | █▃▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▃▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 96.99 |
Accuracy/val | 96.49 |
Loss/train | 0.00016 |
Loss/val | 0.00018 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_121354-zidsl9pf/logs
wandb: Agent Starting Run: 3gr5qidy with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 1e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_121654-3gr5qidy
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0030. Train Acc: 46.8275, Test loss: 0.0031. Test Acc: 46.7400. Time/epoch: 1.5724
saving best checkpoint at epoch: 0, Acc: 46.74
saving best checkpoint at epoch: 1, Acc: 72.34
saving best checkpoint at epoch: 2, Acc: 75.68
saving best checkpoint at epoch: 3, Acc: 82.82
saving best checkpoint at epoch: 4, Acc: 86.38
saving best checkpoint at epoch: 5, Acc: 88.03
saving best checkpoint at epoch: 6, Acc: 89.11
saving best checkpoint at epoch: 7, Acc: 89.97
saving best checkpoint at epoch: 8, Acc: 90.77
saving best checkpoint at epoch: 9, Acc: 91.32
EPOCH 10. Progress: 10.0%.
Train loss: 0.0004. Train Acc: 91.5075, Test loss: 0.0005. Test Acc: 91.4400. Time/epoch: 1.5550
saving best checkpoint at epoch: 10, Acc: 91.44
saving best checkpoint at epoch: 11, Acc: 91.74
saving best checkpoint at epoch: 12, Acc: 92.15
saving best checkpoint at epoch: 13, Acc: 92.35
saving best checkpoint at epoch: 14, Acc: 92.74
saving best checkpoint at epoch: 15, Acc: 92.83
saving best checkpoint at epoch: 16, Acc: 92.95
saving best checkpoint at epoch: 17, Acc: 93.01
saving best checkpoint at epoch: 18, Acc: 93.37
saving best checkpoint at epoch: 19, Acc: 93.51
EPOCH 20. Progress: 20.0%.
Train loss: 0.0003. Train Acc: 93.6000, Test loss: 0.0003. Test Acc: 93.6500. Time/epoch: 1.5476
saving best checkpoint at epoch: 20, Acc: 93.65
saving best checkpoint at epoch: 22, Acc: 93.94
saving best checkpoint at epoch: 23, Acc: 94.05
saving best checkpoint at epoch: 26, Acc: 94.22
saving best checkpoint at epoch: 27, Acc: 94.25
saving best checkpoint at epoch: 29, Acc: 94.3
EPOCH 30. Progress: 30.0%.
Train loss: 0.0003. Train Acc: 94.3725, Test loss: 0.0003. Test Acc: 94.4400. Time/epoch: 1.6881
saving best checkpoint at epoch: 30, Acc: 94.44
saving best checkpoint at epoch: 33, Acc: 94.61
saving best checkpoint at epoch: 34, Acc: 94.74
saving best checkpoint at epoch: 36, Acc: 94.81
saving best checkpoint at epoch: 37, Acc: 94.85
saving best checkpoint at epoch: 38, Acc: 94.92
EPOCH 40. Progress: 40.0%.
Train loss: 0.0003. Train Acc: 94.9700, Test loss: 0.0003. Test Acc: 95.0200. Time/epoch: 1.5364
saving best checkpoint at epoch: 40, Acc: 95.02
saving best checkpoint at epoch: 42, Acc: 95.03
saving best checkpoint at epoch: 45, Acc: 95.06
saving best checkpoint at epoch: 46, Acc: 95.15
saving best checkpoint at epoch: 48, Acc: 95.28
EPOCH 50. Progress: 50.0%.
Train loss: 0.0002. Train Acc: 95.4650, Test loss: 0.0003. Test Acc: 95.0400. Time/epoch: 1.5621
saving best checkpoint at epoch: 52, Acc: 95.41
saving best checkpoint at epoch: 59, Acc: 95.45
EPOCH 60. Progress: 60.0%.
Train loss: 0.0002. Train Acc: 95.6175, Test loss: 0.0003. Test Acc: 95.2800. Time/epoch: 1.5489
saving best checkpoint at epoch: 62, Acc: 95.49
saving best checkpoint at epoch: 65, Acc: 95.61
saving best checkpoint at epoch: 69, Acc: 95.71
EPOCH 70. Progress: 70.0%.
Train loss: 0.0002. Train Acc: 95.8650, Test loss: 0.0002. Test Acc: 95.7200. Time/epoch: 1.5479
saving best checkpoint at epoch: 70, Acc: 95.72
saving best checkpoint at epoch: 75, Acc: 95.82
saving best checkpoint at epoch: 78, Acc: 95.94
EPOCH 80. Progress: 80.0%.
Train loss: 0.0002. Train Acc: 96.0450, Test loss: 0.0002. Test Acc: 95.8600. Time/epoch: 1.6866
saving best checkpoint at epoch: 84, Acc: 95.95
saving best checkpoint at epoch: 85, Acc: 96.01
EPOCH 90. Progress: 90.0%.
Train loss: 0.0002. Train Acc: 96.1675, Test loss: 0.0002. Test Acc: 95.8500. Time/epoch: 1.5493
saving best checkpoint at epoch: 92, Acc: 96.02
saving best checkpoint at epoch: 93, Acc: 96.07
saving best checkpoint at epoch: 98, Acc: 96.08
EPOCH 100. Progress: 100.0%.
Train loss: 0.0002. Train Acc: 96.3375, Test loss: 0.0002. Test Acc: 96.0500. Time/epoch: 1.6948
Run history:
Accuracy/train | ▁▅▇▇▇▇██████████████████████████████████ |
Accuracy/val | ▁▅▇▇▇▇██████████████████████████████████ |
Loss/train | █▄▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▄▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 96.3375 |
Accuracy/val | 96.05 |
Loss/train | 0.0002 |
Loss/val | 0.00021 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_121654-3gr5qidy/logs
wandb: Agent Starting Run: gyikufvq with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 3e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_121952-gyikufvq
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0019. Train Acc: 65.9575, Test loss: 0.0019. Test Acc: 66.3500. Time/epoch: 1.5593
saving best checkpoint at epoch: 0, Acc: 66.35
saving best checkpoint at epoch: 1, Acc: 84.45
saving best checkpoint at epoch: 2, Acc: 86.88
saving best checkpoint at epoch: 3, Acc: 87.92
saving best checkpoint at epoch: 4, Acc: 89.13
saving best checkpoint at epoch: 5, Acc: 90.21
saving best checkpoint at epoch: 6, Acc: 91.28
saving best checkpoint at epoch: 7, Acc: 92.36
saving best checkpoint at epoch: 8, Acc: 92.86
saving best checkpoint at epoch: 9, Acc: 93.58
EPOCH 10. Progress: 10.0%.
Train loss: 0.0003. Train Acc: 93.9625, Test loss: 0.0003. Test Acc: 94.1600. Time/epoch: 1.5730
saving best checkpoint at epoch: 10, Acc: 94.16
saving best checkpoint at epoch: 12, Acc: 94.72
saving best checkpoint at epoch: 14, Acc: 94.76
saving best checkpoint at epoch: 15, Acc: 95.08
saving best checkpoint at epoch: 16, Acc: 95.2
saving best checkpoint at epoch: 19, Acc: 95.38
EPOCH 20. Progress: 20.0%.
Train loss: 0.0002. Train Acc: 95.2875, Test loss: 0.0002. Test Acc: 95.5100. Time/epoch: 1.6838
saving best checkpoint at epoch: 20, Acc: 95.51
saving best checkpoint at epoch: 21, Acc: 95.61
saving best checkpoint at epoch: 22, Acc: 95.66
saving best checkpoint at epoch: 23, Acc: 95.69
saving best checkpoint at epoch: 24, Acc: 95.72
saving best checkpoint at epoch: 26, Acc: 95.94
saving best checkpoint at epoch: 29, Acc: 95.98
EPOCH 30. Progress: 30.0%.
Train loss: 0.0002. Train Acc: 96.0875, Test loss: 0.0002. Test Acc: 95.9700. Time/epoch: 1.5531
saving best checkpoint at epoch: 36, Acc: 96.06
saving best checkpoint at epoch: 37, Acc: 96.1
saving best checkpoint at epoch: 39, Acc: 96.15
EPOCH 40. Progress: 40.0%.
Train loss: 0.0002. Train Acc: 95.7450, Test loss: 0.0002. Test Acc: 95.6600. Time/epoch: 1.6934
saving best checkpoint at epoch: 44, Acc: 96.21
saving best checkpoint at epoch: 45, Acc: 96.26
saving best checkpoint at epoch: 48, Acc: 96.29
saving best checkpoint at epoch: 49, Acc: 96.3
EPOCH 50. Progress: 50.0%.
Train loss: 0.0002. Train Acc: 96.6175, Test loss: 0.0002. Test Acc: 96.3800. Time/epoch: 1.5560
saving best checkpoint at epoch: 50, Acc: 96.38
saving best checkpoint at epoch: 54, Acc: 96.42
saving best checkpoint at epoch: 55, Acc: 96.43
saving best checkpoint at epoch: 56, Acc: 96.54
EPOCH 60. Progress: 60.0%.
Train loss: 0.0002. Train Acc: 96.8975, Test loss: 0.0002. Test Acc: 96.5800. Time/epoch: 1.6839
saving best checkpoint at epoch: 60, Acc: 96.58
saving best checkpoint at epoch: 65, Acc: 96.6
saving best checkpoint at epoch: 67, Acc: 96.65
EPOCH 70. Progress: 70.0%.
Train loss: 0.0002. Train Acc: 96.9550, Test loss: 0.0002. Test Acc: 96.5900. Time/epoch: 1.5488
saving best checkpoint at epoch: 71, Acc: 96.88
saving best checkpoint at epoch: 79, Acc: 96.93
EPOCH 80. Progress: 80.0%.
Train loss: 0.0001. Train Acc: 97.3225, Test loss: 0.0002. Test Acc: 96.8800. Time/epoch: 1.5538
saving best checkpoint at epoch: 82, Acc: 96.96
saving best checkpoint at epoch: 85, Acc: 97.03
saving best checkpoint at epoch: 87, Acc: 97.13
EPOCH 90. Progress: 90.0%.
Train loss: 0.0001. Train Acc: 97.4925, Test loss: 0.0002. Test Acc: 97.1000. Time/epoch: 1.5505
saving best checkpoint at epoch: 96, Acc: 97.14
saving best checkpoint at epoch: 99, Acc: 97.21
EPOCH 100. Progress: 100.0%.
Train loss: 0.0001. Train Acc: 97.5700, Test loss: 0.0002. Test Acc: 97.1900. Time/epoch: 1.5448
Run history:
Accuracy/train | ▁▆▆▇▇▇▇▇▇███████████████████████████████ |
Accuracy/val | ▁▆▆▇▇▇██████████████████████████████████ |
Loss/train | █▃▂▂▂▂▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▃▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 97.57 |
Accuracy/val | 97.19 |
Loss/train | 0.00013 |
Loss/val | 0.00017 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_121952-gyikufvq/logs
wandb: Agent Starting Run: 9gn8bvsn with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_122250-9gn8bvsn
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0004. Train Acc: 90.9175, Test loss: 0.0004. Test Acc: 91.1600. Time/epoch: 1.7233
saving best checkpoint at epoch: 0, Acc: 91.16
saving best checkpoint at epoch: 1, Acc: 91.95
saving best checkpoint at epoch: 2, Acc: 93.96
saving best checkpoint at epoch: 3, Acc: 94.35
saving best checkpoint at epoch: 5, Acc: 94.44
saving best checkpoint at epoch: 7, Acc: 95.08
saving best checkpoint at epoch: 8, Acc: 95.25
EPOCH 10. Progress: 10.0%.
Train loss: 0.0002. Train Acc: 96.0650, Test loss: 0.0002. Test Acc: 96.1200. Time/epoch: 1.5560
saving best checkpoint at epoch: 10, Acc: 96.12
saving best checkpoint at epoch: 13, Acc: 96.51
saving best checkpoint at epoch: 17, Acc: 96.74
EPOCH 20. Progress: 20.0%.
Train loss: 0.0002. Train Acc: 94.9700, Test loss: 0.0003. Test Acc: 94.7400. Time/epoch: 1.7078
saving best checkpoint at epoch: 23, Acc: 96.99
saving best checkpoint at epoch: 27, Acc: 97.08
EPOCH 30. Progress: 30.0%.
Train loss: 0.0002. Train Acc: 96.9325, Test loss: 0.0002. Test Acc: 96.5600. Time/epoch: 1.5596
saving best checkpoint at epoch: 32, Acc: 97.47
saving best checkpoint at epoch: 37, Acc: 97.51
EPOCH 40. Progress: 40.0%.
Train loss: 0.0002. Train Acc: 95.3600, Test loss: 0.0003. Test Acc: 95.0400. Time/epoch: 1.6962
saving best checkpoint at epoch: 41, Acc: 97.58
saving best checkpoint at epoch: 44, Acc: 97.68
saving best checkpoint at epoch: 45, Acc: 97.8
EPOCH 50. Progress: 50.0%.
Train loss: 0.0001. Train Acc: 97.6800, Test loss: 0.0002. Test Acc: 97.0900. Time/epoch: 1.5595
saving best checkpoint at epoch: 53, Acc: 97.93
EPOCH 60. Progress: 60.0%.
Train loss: 0.0001. Train Acc: 98.3700, Test loss: 0.0001. Test Acc: 97.6400. Time/epoch: 1.6867
saving best checkpoint at epoch: 64, Acc: 97.97
EPOCH 70. Progress: 70.0%.
Train loss: 0.0001. Train Acc: 98.9225, Test loss: 0.0001. Test Acc: 98.1500. Time/epoch: 1.5493
saving best checkpoint at epoch: 70, Acc: 98.15
EPOCH 80. Progress: 80.0%.
Train loss: 0.0001. Train Acc: 98.6575, Test loss: 0.0001. Test Acc: 97.6200. Time/epoch: 1.5591
EPOCH 90. Progress: 90.0%.
Train loss: 0.0000. Train Acc: 99.1675, Test loss: 0.0001. Test Acc: 98.0200. Time/epoch: 1.5565
EPOCH 100. Progress: 100.0%.
Train loss: 0.0001. Train Acc: 98.7725, Test loss: 0.0002. Test Acc: 97.4700. Time/epoch: 1.5640
Run history:
Accuracy/train | ▁▃▄▄▅▄▆▆▄▆▆▆▆▅▆▆▇▇▇▇▇▇▆▇████▇█▇███▇▆█▇██ |
Accuracy/val | ▁▄▄▅▆▄▆▇▅▇▇▆▆▅▆▆▇▇▇▇▇█▅▇████▇█▇██▇▇▆█▆█▇ |
Loss/train | █▆▅▅▄▅▃▃▅▃▃▃▃▄▃▃▂▂▂▂▂▂▄▂▂▁▁▁▂▁▂▁▁▁▁▃▁▂▁▁ |
Loss/val | █▅▄▄▃▅▃▃▄▂▂▃▂▃▃▃▁▁▁▁▁▁▄▂▁▁▁▁▂▁▂▁▁▁▂▃▁▃▁▂ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.7725 |
Accuracy/val | 97.47 |
Loss/train | 6e-05 |
Loss/val | 0.00016 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_122250-9gn8bvsn/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: m674t9aj with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 3e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_122605-m674t9aj
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0025. Train Acc: 38.0850, Test loss: 0.0025. Test Acc: 38.7600. Time/epoch: 1.8129
saving best checkpoint at epoch: 0, Acc: 38.76
saving best checkpoint at epoch: 1, Acc: 73.85
saving best checkpoint at epoch: 2, Acc: 77.87
saving best checkpoint at epoch: 3, Acc: 89.8
saving best checkpoint at epoch: 4, Acc: 90.9
saving best checkpoint at epoch: 5, Acc: 91.07
saving best checkpoint at epoch: 6, Acc: 91.74
saving best checkpoint at epoch: 7, Acc: 92.08
saving best checkpoint at epoch: 8, Acc: 92.34
saving best checkpoint at epoch: 9, Acc: 92.59
EPOCH 10. Progress: 10.0%.
Train loss: 0.0004. Train Acc: 92.5600, Test loss: 0.0004. Test Acc: 92.6500. Time/epoch: 1.5551
saving best checkpoint at epoch: 10, Acc: 92.65
saving best checkpoint at epoch: 11, Acc: 93.18
saving best checkpoint at epoch: 12, Acc: 93.41
saving best checkpoint at epoch: 13, Acc: 93.44
saving best checkpoint at epoch: 14, Acc: 93.59
saving best checkpoint at epoch: 16, Acc: 93.78
saving best checkpoint at epoch: 17, Acc: 93.92
saving best checkpoint at epoch: 18, Acc: 94.2
EPOCH 20. Progress: 20.0%.
Train loss: 0.0003. Train Acc: 94.3200, Test loss: 0.0003. Test Acc: 94.5100. Time/epoch: 1.6992
saving best checkpoint at epoch: 20, Acc: 94.51
saving best checkpoint at epoch: 24, Acc: 94.61
saving best checkpoint at epoch: 25, Acc: 94.79
saving best checkpoint at epoch: 26, Acc: 94.95
saving best checkpoint at epoch: 29, Acc: 95.21
EPOCH 30. Progress: 30.0%.
Train loss: 0.0003. Train Acc: 95.2275, Test loss: 0.0003. Test Acc: 95.3200. Time/epoch: 1.5568
saving best checkpoint at epoch: 30, Acc: 95.32
saving best checkpoint at epoch: 35, Acc: 95.47
saving best checkpoint at epoch: 39, Acc: 95.72
EPOCH 40. Progress: 40.0%.
Train loss: 0.0002. Train Acc: 95.6475, Test loss: 0.0002. Test Acc: 95.6500. Time/epoch: 1.6973
saving best checkpoint at epoch: 43, Acc: 95.88
saving best checkpoint at epoch: 48, Acc: 95.96
EPOCH 50. Progress: 50.0%.
Train loss: 0.0002. Train Acc: 95.8100, Test loss: 0.0002. Test Acc: 95.6400. Time/epoch: 1.5618
saving best checkpoint at epoch: 53, Acc: 96.05
saving best checkpoint at epoch: 56, Acc: 96.17
EPOCH 60. Progress: 60.0%.
Train loss: 0.0002. Train Acc: 96.3250, Test loss: 0.0002. Test Acc: 96.1700. Time/epoch: 1.6886
saving best checkpoint at epoch: 64, Acc: 96.29
EPOCH 70. Progress: 70.0%.
Train loss: 0.0002. Train Acc: 96.4625, Test loss: 0.0002. Test Acc: 96.2300. Time/epoch: 1.5446
saving best checkpoint at epoch: 75, Acc: 96.42
saving best checkpoint at epoch: 79, Acc: 96.52
EPOCH 80. Progress: 80.0%.
Train loss: 0.0002. Train Acc: 96.6500, Test loss: 0.0002. Test Acc: 96.3900. Time/epoch: 1.5512
saving best checkpoint at epoch: 88, Acc: 96.57
EPOCH 90. Progress: 90.0%.
Train loss: 0.0002. Train Acc: 96.7625, Test loss: 0.0002. Test Acc: 96.4100. Time/epoch: 1.5503
saving best checkpoint at epoch: 93, Acc: 96.58
saving best checkpoint at epoch: 99, Acc: 96.65
EPOCH 100. Progress: 100.0%.
Train loss: 0.0002. Train Acc: 96.7550, Test loss: 0.0002. Test Acc: 96.5000. Time/epoch: 1.5737
Run history:
Accuracy/train | ▁▆▇▇▇███████████████████████████████████ |
Accuracy/val | ▁▆▇▇████████████████████████████████████ |
Loss/train | █▃▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▃▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 96.755 |
Accuracy/val | 96.5 |
Loss/train | 0.00017 |
Loss/val | 0.00019 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_122605-m674t9aj/logs
wandb: Agent Starting Run: jp3cygfx with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 1e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_122903-jp3cygfx
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0025. Train Acc: 65.9500, Test loss: 0.0025. Test Acc: 66.2100. Time/epoch: 1.7282
saving best checkpoint at epoch: 0, Acc: 66.21
saving best checkpoint at epoch: 1, Acc: 79.69
saving best checkpoint at epoch: 2, Acc: 81.37
saving best checkpoint at epoch: 3, Acc: 85.2
saving best checkpoint at epoch: 4, Acc: 86.54
saving best checkpoint at epoch: 5, Acc: 87.62
saving best checkpoint at epoch: 6, Acc: 88.27
saving best checkpoint at epoch: 7, Acc: 88.91
saving best checkpoint at epoch: 8, Acc: 89.12
saving best checkpoint at epoch: 9, Acc: 89.44
EPOCH 10. Progress: 10.0%.
Train loss: 0.0005. Train Acc: 89.7750, Test loss: 0.0005. Test Acc: 89.8100. Time/epoch: 1.5568
saving best checkpoint at epoch: 10, Acc: 89.81
saving best checkpoint at epoch: 11, Acc: 89.83
saving best checkpoint at epoch: 12, Acc: 90.17
saving best checkpoint at epoch: 13, Acc: 90.55
saving best checkpoint at epoch: 14, Acc: 90.71
saving best checkpoint at epoch: 15, Acc: 90.76
saving best checkpoint at epoch: 17, Acc: 90.79
saving best checkpoint at epoch: 18, Acc: 91.04
saving best checkpoint at epoch: 19, Acc: 91.23
EPOCH 20. Progress: 20.0%.
Train loss: 0.0004. Train Acc: 91.4525, Test loss: 0.0004. Test Acc: 91.6100. Time/epoch: 1.6912
saving best checkpoint at epoch: 20, Acc: 91.61
saving best checkpoint at epoch: 21, Acc: 91.9
saving best checkpoint at epoch: 22, Acc: 92.47
saving best checkpoint at epoch: 23, Acc: 92.89
saving best checkpoint at epoch: 24, Acc: 93.18
saving best checkpoint at epoch: 25, Acc: 93.51
saving best checkpoint at epoch: 28, Acc: 93.6
saving best checkpoint at epoch: 29, Acc: 93.77
EPOCH 30. Progress: 30.0%.
Train loss: 0.0003. Train Acc: 93.5400, Test loss: 0.0003. Test Acc: 93.8800. Time/epoch: 1.5431
saving best checkpoint at epoch: 30, Acc: 93.88
saving best checkpoint at epoch: 31, Acc: 93.89
saving best checkpoint at epoch: 32, Acc: 94.05
saving best checkpoint at epoch: 34, Acc: 94.09
saving best checkpoint at epoch: 35, Acc: 94.16
saving best checkpoint at epoch: 36, Acc: 94.22
saving best checkpoint at epoch: 37, Acc: 94.23
saving best checkpoint at epoch: 38, Acc: 94.45
EPOCH 40. Progress: 40.0%.
Train loss: 0.0003. Train Acc: 94.1750, Test loss: 0.0003. Test Acc: 94.2100. Time/epoch: 1.5590
saving best checkpoint at epoch: 41, Acc: 94.51
saving best checkpoint at epoch: 42, Acc: 94.54
saving best checkpoint at epoch: 43, Acc: 94.56
saving best checkpoint at epoch: 46, Acc: 94.6
saving best checkpoint at epoch: 47, Acc: 94.66
saving best checkpoint at epoch: 48, Acc: 94.85
EPOCH 50. Progress: 50.0%.
Train loss: 0.0003. Train Acc: 94.5675, Test loss: 0.0003. Test Acc: 94.7700. Time/epoch: 1.5568
saving best checkpoint at epoch: 51, Acc: 94.87
saving best checkpoint at epoch: 53, Acc: 94.9
saving best checkpoint at epoch: 55, Acc: 95.05
saving best checkpoint at epoch: 57, Acc: 95.09
saving best checkpoint at epoch: 58, Acc: 95.15
saving best checkpoint at epoch: 59, Acc: 95.2
EPOCH 60. Progress: 60.0%.
Train loss: 0.0003. Train Acc: 94.9650, Test loss: 0.0003. Test Acc: 95.1100. Time/epoch: 1.6908
saving best checkpoint at epoch: 61, Acc: 95.27
saving best checkpoint at epoch: 62, Acc: 95.33
saving best checkpoint at epoch: 67, Acc: 95.45
EPOCH 70. Progress: 70.0%.
Train loss: 0.0002. Train Acc: 95.4325, Test loss: 0.0003. Test Acc: 95.5000. Time/epoch: 1.5482
saving best checkpoint at epoch: 70, Acc: 95.5
saving best checkpoint at epoch: 72, Acc: 95.52
saving best checkpoint at epoch: 76, Acc: 95.57
saving best checkpoint at epoch: 78, Acc: 95.64
EPOCH 80. Progress: 80.0%.
Train loss: 0.0002. Train Acc: 95.5175, Test loss: 0.0002. Test Acc: 95.3300. Time/epoch: 1.5511
saving best checkpoint at epoch: 81, Acc: 95.69
saving best checkpoint at epoch: 83, Acc: 95.72
EPOCH 90. Progress: 90.0%.
Train loss: 0.0002. Train Acc: 95.8800, Test loss: 0.0002. Test Acc: 95.8100. Time/epoch: 1.5446
saving best checkpoint at epoch: 90, Acc: 95.81
saving best checkpoint at epoch: 96, Acc: 95.88
saving best checkpoint at epoch: 97, Acc: 95.9
EPOCH 100. Progress: 100.0%.
Train loss: 0.0002. Train Acc: 96.1625, Test loss: 0.0002. Test Acc: 95.8300. Time/epoch: 1.5488
Run history:
Accuracy/train | ▁▅▆▆▇▇▇▇▇▇▇▇▇▇▇█████████████████████████ |
Accuracy/val | ▁▅▆▆▇▇▇▇▇▇▇▇████████████████████████████ |
Loss/train | █▄▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▄▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 96.1625 |
Accuracy/val | 95.83 |
Loss/train | 0.00021 |
Loss/val | 0.00023 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_122903-jp3cygfx/logs
wandb: Agent Starting Run: 85cnnwwy with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.0005
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_123204-85cnnwwy
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0006. Train Acc: 88.1500, Test loss: 0.0006. Test Acc: 88.3600. Time/epoch: 1.7109
saving best checkpoint at epoch: 0, Acc: 88.36
saving best checkpoint at epoch: 1, Acc: 90.87
saving best checkpoint at epoch: 4, Acc: 93.47
saving best checkpoint at epoch: 5, Acc: 94.24
saving best checkpoint at epoch: 6, Acc: 95.39
EPOCH 10. Progress: 10.0%.
Train loss: 0.0002. Train Acc: 95.5600, Test loss: 0.0003. Test Acc: 95.2800. Time/epoch: 1.6901
saving best checkpoint at epoch: 11, Acc: 95.46
saving best checkpoint at epoch: 12, Acc: 95.82
saving best checkpoint at epoch: 15, Acc: 95.91
saving best checkpoint at epoch: 16, Acc: 96.03
saving best checkpoint at epoch: 18, Acc: 96.68
saving best checkpoint at epoch: 19, Acc: 96.78
EPOCH 20. Progress: 20.0%.
Train loss: 0.0002. Train Acc: 96.6200, Test loss: 0.0002. Test Acc: 96.3100. Time/epoch: 1.5512
saving best checkpoint at epoch: 24, Acc: 96.91
saving best checkpoint at epoch: 26, Acc: 97.12
saving best checkpoint at epoch: 27, Acc: 97.24
EPOCH 30. Progress: 30.0%.
Train loss: 0.0001. Train Acc: 97.4800, Test loss: 0.0002. Test Acc: 97.1800. Time/epoch: 1.6915
saving best checkpoint at epoch: 32, Acc: 97.41
saving best checkpoint at epoch: 38, Acc: 97.48
EPOCH 40. Progress: 40.0%.
Train loss: 0.0001. Train Acc: 97.7725, Test loss: 0.0002. Test Acc: 97.2000. Time/epoch: 1.5395
EPOCH 50. Progress: 50.0%.
Train loss: 0.0001. Train Acc: 98.3025, Test loss: 0.0001. Test Acc: 97.4800. Time/epoch: 1.6963
saving best checkpoint at epoch: 52, Acc: 97.56
EPOCH 60. Progress: 60.0%.
Train loss: 0.0001. Train Acc: 98.0975, Test loss: 0.0002. Test Acc: 97.2500. Time/epoch: 1.5455
saving best checkpoint at epoch: 61, Acc: 97.79
EPOCH 70. Progress: 70.0%.
Train loss: 0.0001. Train Acc: 97.8225, Test loss: 0.0002. Test Acc: 97.0700. Time/epoch: 1.7666
saving best checkpoint at epoch: 72, Acc: 97.83
saving best checkpoint at epoch: 73, Acc: 97.85
saving best checkpoint at epoch: 75, Acc: 97.94
EPOCH 80. Progress: 80.0%.
Train loss: 0.0001. Train Acc: 98.3725, Test loss: 0.0002. Test Acc: 97.4700. Time/epoch: 1.5510
EPOCH 90. Progress: 90.0%.
Train loss: 0.0001. Train Acc: 98.8625, Test loss: 0.0001. Test Acc: 97.7200. Time/epoch: 1.5698
saving best checkpoint at epoch: 94, Acc: 98.05
EPOCH 100. Progress: 100.0%.
Train loss: 0.0001. Train Acc: 98.4500, Test loss: 0.0002. Test Acc: 97.4600. Time/epoch: 1.5458
Run history:
Accuracy/train | ▁▂▅▆▆▆▆▆▆▅▆▇▇▇▇▇▇▇▆▇▇▇▇▅██▇▇█▇█████▇████ |
Accuracy/val | ▁▂▅▆▆▆▆▆▇▆▆▇▇▇▇█▇▇▇▇▇█▇▄███▇█▇████▇▇▇███ |
Loss/train | █▇▄▃▃▃▃▃▃▃▃▃▂▂▂▂▂▂▂▂▂▂▂▄▁▁▂▂▁▂▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▇▃▃▃▂▂▂▂▃▂▂▁▂▂▁▁▁▂▁▁▁▂▄▁▁▁▁▁▂▁▁▁▁▁▂▂▁▁▂ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.45 |
Accuracy/val | 97.46 |
Loss/train | 8e-05 |
Loss/val | 0.00018 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_123204-85cnnwwy/logs
wandb: Agent Starting Run: 6xwudzpi with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 1e-05
wandb: optimizer: adam
wandb: weight_decay: 0.05
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_123503-6xwudzpi
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0029. Train Acc: 56.9525, Test loss: 0.0029. Test Acc: 57.0800. Time/epoch: 1.5937
saving best checkpoint at epoch: 0, Acc: 57.08
saving best checkpoint at epoch: 1, Acc: 75.08
saving best checkpoint at epoch: 2, Acc: 81.17
saving best checkpoint at epoch: 3, Acc: 83.53
saving best checkpoint at epoch: 4, Acc: 86.24
saving best checkpoint at epoch: 5, Acc: 87.58
saving best checkpoint at epoch: 6, Acc: 88.49
saving best checkpoint at epoch: 7, Acc: 89.24
saving best checkpoint at epoch: 8, Acc: 89.64
saving best checkpoint at epoch: 9, Acc: 89.91
EPOCH 10. Progress: 10.0%.
Train loss: 0.0005. Train Acc: 90.0575, Test loss: 0.0005. Test Acc: 90.0700. Time/epoch: 1.5676
saving best checkpoint at epoch: 10, Acc: 90.07
saving best checkpoint at epoch: 11, Acc: 90.23
saving best checkpoint at epoch: 12, Acc: 90.54
saving best checkpoint at epoch: 13, Acc: 90.8
saving best checkpoint at epoch: 14, Acc: 90.96
saving best checkpoint at epoch: 15, Acc: 91.11
saving best checkpoint at epoch: 16, Acc: 91.23
saving best checkpoint at epoch: 17, Acc: 91.41
saving best checkpoint at epoch: 18, Acc: 91.59
saving best checkpoint at epoch: 19, Acc: 91.67
EPOCH 20. Progress: 20.0%.
Train loss: 0.0004. Train Acc: 91.7100, Test loss: 0.0004. Test Acc: 91.9200. Time/epoch: 1.6876
saving best checkpoint at epoch: 20, Acc: 91.92
saving best checkpoint at epoch: 21, Acc: 91.99
saving best checkpoint at epoch: 22, Acc: 92.02
saving best checkpoint at epoch: 23, Acc: 92.2
saving best checkpoint at epoch: 24, Acc: 92.32
saving best checkpoint at epoch: 25, Acc: 92.42
saving best checkpoint at epoch: 26, Acc: 92.55
saving best checkpoint at epoch: 27, Acc: 92.61
saving best checkpoint at epoch: 28, Acc: 92.68
saving best checkpoint at epoch: 29, Acc: 92.98
EPOCH 30. Progress: 30.0%.
Train loss: 0.0003. Train Acc: 92.8275, Test loss: 0.0004. Test Acc: 93.1700. Time/epoch: 1.5538
saving best checkpoint at epoch: 30, Acc: 93.17
saving best checkpoint at epoch: 31, Acc: 93.35
saving best checkpoint at epoch: 32, Acc: 93.46
saving best checkpoint at epoch: 33, Acc: 93.55
saving best checkpoint at epoch: 34, Acc: 93.63
saving best checkpoint at epoch: 36, Acc: 93.7
saving best checkpoint at epoch: 38, Acc: 93.86
saving best checkpoint at epoch: 39, Acc: 93.98
EPOCH 40. Progress: 40.0%.
Train loss: 0.0003. Train Acc: 93.6200, Test loss: 0.0003. Test Acc: 93.8300. Time/epoch: 1.5547
saving best checkpoint at epoch: 41, Acc: 94.08
saving best checkpoint at epoch: 43, Acc: 94.23
saving best checkpoint at epoch: 44, Acc: 94.32
saving best checkpoint at epoch: 45, Acc: 94.38
saving best checkpoint at epoch: 46, Acc: 94.52
EPOCH 50. Progress: 50.0%.
Train loss: 0.0003. Train Acc: 94.4475, Test loss: 0.0003. Test Acc: 94.5200. Time/epoch: 1.5643
saving best checkpoint at epoch: 52, Acc: 94.65
saving best checkpoint at epoch: 55, Acc: 94.69
saving best checkpoint at epoch: 57, Acc: 94.7
saving best checkpoint at epoch: 58, Acc: 94.74
saving best checkpoint at epoch: 59, Acc: 94.8
EPOCH 60. Progress: 60.0%.
Train loss: 0.0003. Train Acc: 94.7300, Test loss: 0.0003. Test Acc: 94.7000. Time/epoch: 1.5514
saving best checkpoint at epoch: 63, Acc: 94.81
saving best checkpoint at epoch: 64, Acc: 94.86
saving best checkpoint at epoch: 68, Acc: 94.92
saving best checkpoint at epoch: 69, Acc: 94.93
EPOCH 70. Progress: 70.0%.
Train loss: 0.0003. Train Acc: 94.9900, Test loss: 0.0003. Test Acc: 94.9300. Time/epoch: 1.5565
saving best checkpoint at epoch: 71, Acc: 94.94
saving best checkpoint at epoch: 72, Acc: 95.0
saving best checkpoint at epoch: 77, Acc: 95.07
EPOCH 80. Progress: 80.0%.
Train loss: 0.0003. Train Acc: 95.0625, Test loss: 0.0003. Test Acc: 94.9900. Time/epoch: 1.5577
saving best checkpoint at epoch: 83, Acc: 95.16
saving best checkpoint at epoch: 87, Acc: 95.19
EPOCH 90. Progress: 90.0%.
Train loss: 0.0002. Train Acc: 95.3650, Test loss: 0.0003. Test Acc: 95.1900. Time/epoch: 1.6952
saving best checkpoint at epoch: 91, Acc: 95.26
saving best checkpoint at epoch: 95, Acc: 95.31
EPOCH 100. Progress: 100.0%.
Train loss: 0.0002. Train Acc: 95.5325, Test loss: 0.0002. Test Acc: 95.3000. Time/epoch: 1.5494
Run history:
Accuracy/train | ▁▅▆▇▇▇▇▇▇▇▇▇████████████████████████████ |
Accuracy/val | ▁▅▇▇▇▇▇▇▇▇▇█████████████████████████████ |
Loss/train | █▄▃▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
Loss/val | █▄▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 95.5325 |
Accuracy/val | 95.3 |
Loss/train | 0.00023 |
Loss/val | 0.00025 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_123503-6xwudzpi/logs
wandb: Agent Starting Run: q3dr4w53 with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 0.0003
wandb: optimizer: adam
wandb: weight_decay: 0.005
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_123803-q3dr4w53
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0004. Train Acc: 90.4925, Test loss: 0.0004. Test Acc: 90.2800. Time/epoch: 1.5818
saving best checkpoint at epoch: 0, Acc: 90.28
saving best checkpoint at epoch: 1, Acc: 90.41
saving best checkpoint at epoch: 2, Acc: 93.56
saving best checkpoint at epoch: 3, Acc: 93.79
saving best checkpoint at epoch: 4, Acc: 94.32
saving best checkpoint at epoch: 6, Acc: 95.0
saving best checkpoint at epoch: 7, Acc: 95.35
EPOCH 10. Progress: 10.0%.
Train loss: 0.0002. Train Acc: 95.6825, Test loss: 0.0002. Test Acc: 95.4500. Time/epoch: 1.6953
saving best checkpoint at epoch: 10, Acc: 95.45
saving best checkpoint at epoch: 11, Acc: 95.77
saving best checkpoint at epoch: 13, Acc: 96.25
saving best checkpoint at epoch: 18, Acc: 96.33
EPOCH 20. Progress: 20.0%.
Train loss: 0.0002. Train Acc: 96.3925, Test loss: 0.0002. Test Acc: 96.1500. Time/epoch: 1.5409
saving best checkpoint at epoch: 21, Acc: 96.64
saving best checkpoint at epoch: 28, Acc: 96.74
saving best checkpoint at epoch: 29, Acc: 96.89
EPOCH 30. Progress: 30.0%.
Train loss: 0.0002. Train Acc: 96.8200, Test loss: 0.0002. Test Acc: 96.4500. Time/epoch: 1.5950
EPOCH 40. Progress: 40.0%.
Train loss: 0.0001. Train Acc: 97.3300, Test loss: 0.0002. Test Acc: 96.8400. Time/epoch: 1.5545
saving best checkpoint at epoch: 43, Acc: 97.11
saving best checkpoint at epoch: 47, Acc: 97.18
EPOCH 50. Progress: 50.0%.
Train loss: 0.0001. Train Acc: 97.0450, Test loss: 0.0002. Test Acc: 96.6500. Time/epoch: 1.7074
saving best checkpoint at epoch: 52, Acc: 97.19
saving best checkpoint at epoch: 55, Acc: 97.39
EPOCH 60. Progress: 60.0%.
Train loss: 0.0001. Train Acc: 97.4625, Test loss: 0.0002. Test Acc: 96.8300. Time/epoch: 1.5645
saving best checkpoint at epoch: 69, Acc: 97.48
EPOCH 70. Progress: 70.0%.
Train loss: 0.0001. Train Acc: 97.8475, Test loss: 0.0002. Test Acc: 97.1800. Time/epoch: 1.6847
saving best checkpoint at epoch: 71, Acc: 97.52
EPOCH 80. Progress: 80.0%.
Train loss: 0.0001. Train Acc: 98.0400, Test loss: 0.0002. Test Acc: 97.3000. Time/epoch: 1.5567
EPOCH 90. Progress: 90.0%.
Train loss: 0.0001. Train Acc: 98.6225, Test loss: 0.0001. Test Acc: 97.5600. Time/epoch: 1.7204
saving best checkpoint at epoch: 90, Acc: 97.56
saving best checkpoint at epoch: 91, Acc: 97.69
EPOCH 100. Progress: 100.0%.
Train loss: 0.0001. Train Acc: 98.4675, Test loss: 0.0002. Test Acc: 97.4600. Time/epoch: 1.5554
Run history:
Accuracy/train | ▁▄▃▅▅▅▅▆▆▆▆▇▆▆▆▆▆▇▇▇▇▆▇▇▇▇▇██▇▇▇█▇██▇███ |
Accuracy/val | ▁▄▃▆▆▅▆▆▇▆▇▇▇▆▇▇▇▇▇▇▇▆▇▇██▇██▇███▇██▇███ |
Loss/train | █▆▆▄▄▄▄▃▃▃▃▃▃▃▃▃▃▂▂▂▂▃▂▂▂▂▂▁▁▂▁▂▁▁▁▁▂▁▁▁ |
Loss/val | █▅▅▃▃▄▃▂▂▂▂▂▂▃▂▂▂▁▂▁▂▃▂▂▁▁▂▁▁▂▁▁▁▂▁▁▂▁▁▁ |
epoch | ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
Run summary:
Accuracy/train | 98.4675 |
Accuracy/val | 97.46 |
Loss/train | 8e-05 |
Loss/val | 0.00015 |
epoch | 100 |
Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)
./wandb/run-20230518_123803-q3dr4w53/logs
wandb: Sweep Agent: Waiting for job.
wandb: Job received.
wandb: Agent Starting Run: 3jluxc9k with config:
wandb: batch_size: 512
wandb: epochs: 100
wandb: learning_rate: 3e-05
wandb: optimizer: adam
wandb: weight_decay: 0.005
Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.
/vast/palmer/home.mccleary/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_124109-3jluxc9k
Sweep page: https://wandb.ai/ahof1704/CNN_Sat_sweep/sweeps/tyzcsl8s
EPOCH 0. Progress: 0.0%.
Train loss: 0.0022. Train Acc: 74.0225, Test loss: 0.0023. Test Acc: 74.2800. Time/epoch: 1.7199
saving best checkpoint at epoch: 0, Acc: 74.28
saving best checkpoint at epoch: 1, Acc: 88.55
saving best checkpoint at epoch: 2, Acc: 90.66
saving best checkpoint at epoch: 3, Acc: 91.04
saving best checkpoint at epoch: 4, Acc: 91.74
saving best checkpoint at epoch: 5, Acc: 92.05
saving best checkpoint at epoch: 6, Acc: 92.49
saving best checkpoint at epoch: 7, Acc: 92.84
saving best checkpoint at epoch: 8, Acc: 92.95
saving best checkpoint at epoch: 9, Acc: 93.28
EPOCH 10. Progress: 10.0%.
Train loss: 0.0003. Train Acc: 93.6025, Test loss: 0.0003. Test Acc: 93.6100. Time/epoch: 1.5491
saving best checkpoint at epoch: 10, Acc: 93.61
saving best checkpoint at epoch: 11, Acc: 93.7
saving best checkpoint at epoch: 12, Acc: 93.88
saving best checkpoint at epoch: 13, Acc: 94.01
saving best checkpoint at epoch: 14, Acc: 94.25
saving best checkpoint at epoch: 16, Acc: 94.41
saving best checkpoint at epoch: 18, Acc: 94.67
saving best checkpoint at epoch: 19, Acc: 94.68
EPOCH 20. Progress: 20.0%.
Train loss: 0.0003. Train Acc: 94.9875, Test loss: 0.0003. Test Acc: 94.8900. Time/epoch: 1.5437
saving best checkpoint at epoch: 20, Acc: 94.89
saving best checkpoint at epoch: 21, Acc: 94.93
saving best checkpoint at epoch: 24, Acc: 95.08
saving best checkpoint at epoch: 27, Acc: 95.12
saving best checkpoint at epoch: 28, Acc: 95.16
EPOCH 30. Progress: 30.0%.
Train loss: 0.0002. Train Acc: 95.4850, Test loss: 0.0003. Test Acc: 94.9700. Time/epoch: 1.6928
saving best checkpoint at epoch: 31, Acc: 95.26
saving best checkpoint at epoch: 32, Acc: 95.32
saving best checkpoint at epoch: 33, Acc: 95.47
saving best checkpoint at epoch: 34, Acc: 95.54
saving best checkpoint at epoch: 35, Acc: 95.72
saving best checkpoint at epoch: 37, Acc: 95.78
EPOCH 40. Progress: 40.0%.
Train loss: 0.0002. Train Acc: 96.0075, Test loss: 0.0002. Test Acc: 95.8500. Time/epoch: 1.5406
saving best checkpoint at epoch: 40, Acc: 95.85
saving best checkpoint at epoch: 47, Acc: 96.08
EPOCH 50. Progress: 50.0%.
Train loss: 0.0002. Train Acc: 96.1000, Test loss: 0.0002. Test Acc: 95.7900. Time/epoch: 1.7070
saving best checkpoint at epoch: 57, Acc: 96.2
EPOCH 60. Progress: 60.0%.
Train loss: 0.0002. Train Acc: 96.5800, Test loss: 0.0002. Test Acc: 96.1500. Time/epoch: 1.5503
saving best checkpoint at epoch: 62, Acc: 96.24
EPOCH 70. Progress: 70.0%.
Train loss: 0.0002. Train Acc: 96.7575, Test loss: 0.0002. Test Acc: 96.3600. Time/epoch: 1.6897
saving best checkpoint at epoch: 70, Acc: 96.36
wandb: Ctrl + C detected. Stopping sweep.
[ ]:
# Load the best model based on the sweeping
class CNNet(nn.Module):
def __init__(self):
super().__init__()
self.conv1 = nn.Conv2d(4, 6, 5)
self.pool = nn.MaxPool2d(2, 2)
self.conv2 = nn.Conv2d(6, 16, 5)
self.fc1 = nn.Linear(16 * 4 * 4, 120)
self.fc2 = nn.Linear(120, 84)
self.fc3 = nn.Linear(84, 6)
def forward(self, x):
x = self.pool(F.relu(self.conv1(x)))
x = self.pool(F.relu(self.conv2(x)))
x = torch.flatten(x, 1) # flatten all dimensions except batch
x = F.relu(self.fc1(x))
x = F.relu(self.fc2(x))
x = self.fc3(x)
return x
model = CNNet()
PATH_ = '/home/ahf38/Documents/geo_comp_offline/2022/wandb/run-20230518_090544-krnzu5ta/files'
model.load_state_dict(torch.load(os.path.join(PATH_,'model.pt')))
<All keys matched successfully>
[ ]:
#Change the dimension to fit into the model
x_test = test_images.transpose(3,0,1,2)
t_test = test_labels.transpose()
model = model.to(device)
model.eval()
# with torch.no_grad():
# Retrieve output from the image
# idx_to_plot = 2
for idx_to_plot in range(10):
image = x_test[idx_to_plot,:,:,:]
image_orig = image.copy()
image = torch.FloatTensor(image).permute(2, 1, 0).to(device)
# Make input tensor require gradient
# X.requires_grad_()
image = image[None,:].requires_grad_()
print(image.shape)
output = model(image)
# Catch the output
output_idx = output.argmax()
output_max = output[0, output_idx]
# Do backpropagation to get the derivative of the output based on the image
output_max.backward()
# Retireve the saliency map and also pick the maximum value from channels on each pixel.
# In this case, we look at dim=1. Recall the shape (batch_size, channel, width, height)
saliency, _ = torch.max(image.grad.data.abs(), dim=1)
saliency = saliency.reshape(28, 28)
# # Reshape the image
# image = image.reshape(-1, 28, 28)
# Visualize the image and the saliency map
fig, ax = plt.subplots(1, 2)
# x_train[count,:,:,0:3]
# print(image.shape)
# image = image.permute(3, 2, 1,0).squeeze()
# print(image.shape)
ax[0].imshow(image_orig[:,:,0:3])
ax[0].axis('off')
ax[1].imshow(saliency.cpu(), cmap='hot')
ax[1].axis('off')
ax[0].set_title('Label: {}, Pred: {}'.format(t_test[idx_to_plot].argmax(),output_idx.cpu()))
plt.tight_layout()
fig.suptitle('The Image and Its Saliency Map')
plt.show()
torch.Size([1, 4, 28, 28])

torch.Size([1, 4, 28, 28])

torch.Size([1, 4, 28, 28])

torch.Size([1, 4, 28, 28])

torch.Size([1, 4, 28, 28])

torch.Size([1, 4, 28, 28])

torch.Size([1, 4, 28, 28])

torch.Size([1, 4, 28, 28])

torch.Size([1, 4, 28, 28])

torch.Size([1, 4, 28, 28])

[ ]: