mirror of
https://github.com/ION606/COGMOD-HWI.git
synced 2026-05-14 22:16:57 +00:00
re-ran the tests
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data/
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tmp/
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|
||||
14,1.3183710289382935,0.5275,1.0492525255203247,0.6326
|
||||
15,1.309831443862915,0.53334,1.0428013453483582,0.6284
|
||||
16,1.2975196259307862,0.5399,1.0418389265060424,0.6349
|
||||
17,1.2833650760650634,0.5448,1.1197743309020995,0.596
|
||||
18,1.2782311374664306,0.54604,0.9917507829666138,0.6546
|
||||
19,1.2591375436401366,0.55266,0.9647492932319641,0.6582
|
||||
20,1.2543545852279663,0.55702,0.9729726590156555,0.6574
|
||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
1,1.9567125562286376,0.2868,1.6595897144317626,0.4048
|
||||
2,1.5607059629058837,0.43864,1.4107039302825928,0.4848
|
||||
3,1.393210672225952,0.49774,1.2663319400787354,0.5489
|
||||
4,1.3098828198623658,0.52998,1.205306915473938,0.5761
|
||||
5,1.2406870504379273,0.5571,1.1519119177818298,0.5984
|
||||
6,1.1775763750839234,0.58036,1.1193829996109008,0.6051
|
||||
7,1.1138219023132325,0.60238,1.0738257904052735,0.6176
|
||||
8,1.070581941833496,0.61852,1.0231942397117615,0.6371
|
||||
9,1.030339531364441,0.63532,0.9935429817199707,0.6441
|
||||
10,0.9900466967391968,0.65002,0.9499927408218384,0.6665
|
||||
11,0.9637177305793763,0.66046,0.9340457020759583,0.6675
|
||||
12,0.9254747213745117,0.67558,0.9082785024642944,0.6792
|
||||
13,0.908202090473175,0.6779,0.9268069096565247,0.6748
|
||||
14,0.8821638398742676,0.68774,0.8835061459541321,0.6887
|
||||
15,0.8548155406951904,0.69706,0.8872944156646728,0.6871
|
||||
16,0.8442007188415528,0.70044,0.8849920805931091,0.6918
|
||||
17,0.8165878020095825,0.70872,0.8710031011581421,0.6989
|
||||
18,0.7962540114593506,0.718,0.8807716882705688,0.6914
|
||||
19,0.7728271597862244,0.72794,0.852915700340271,0.7069
|
||||
20,0.758258864402771,0.7303,0.8573900122642517,0.7003
|
||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
1,2.0236042365264892,0.257,1.723145390892029,0.3901
|
||||
2,1.5985155703353882,0.4249,1.4042083190917969,0.4924
|
||||
3,1.4218818955612182,0.48632,1.2928504508972167,0.5413
|
||||
4,1.3203161227035523,0.52612,1.2168406352996826,0.5661
|
||||
5,1.2403734153366088,0.55756,1.149209902381897,0.5939
|
||||
6,1.1671098303222656,0.58366,1.1203332425117494,0.5994
|
||||
7,1.112549086380005,0.6046,1.0411104937553406,0.6325
|
||||
8,1.0569730423927308,0.62496,1.014323724079132,0.6456
|
||||
9,1.0219695941925049,0.6371,0.9721902985572815,0.659
|
||||
10,0.9759654503250123,0.65288,0.942803035736084,0.6697
|
||||
11,0.9441324331092834,0.66574,0.9112948065757751,0.679
|
||||
12,0.9140988022041321,0.67698,0.8975791595458984,0.6881
|
||||
13,0.8857126325798035,0.68738,0.8933684177398682,0.689
|
||||
14,0.859081026725769,0.69532,0.8806665014266968,0.6958
|
||||
15,0.8373628576278687,0.7053,0.8862028203964233,0.6894
|
||||
16,0.8062883552742004,0.71626,0.8928611957550049,0.6907
|
||||
17,0.7948164237213134,0.71876,0.8475546907424927,0.7084
|
||||
18,0.7735403092384339,0.72452,0.8641609072685241,0.7011
|
||||
19,0.7580092010688781,0.7301,0.8455605938911438,0.7051
|
||||
20,0.7356696060180664,0.73766,0.8630998106002807,0.704
|
||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
1,1.9932699127578735,0.26908,1.652609211730957,0.4115
|
||||
2,1.6025463925170897,0.42024,1.4165557703018188,0.4886
|
||||
3,1.4385107410812379,0.47978,1.3373357730865478,0.5276
|
||||
4,1.329945457725525,0.52296,1.207246643447876,0.5639
|
||||
5,1.2507697713470458,0.55224,1.1396601531982422,0.5997
|
||||
6,1.1825159574127198,0.5785,1.0910413694381713,0.6131
|
||||
7,1.129948296546936,0.59706,1.0626532356262206,0.6223
|
||||
8,1.0810239276123046,0.61532,1.0606243711471557,0.6271
|
||||
9,1.0398018453979492,0.63036,0.9847188907623291,0.6508
|
||||
10,1.0001467765808105,0.64718,0.978429046344757,0.6578
|
||||
11,0.9662233278274536,0.65672,0.9435468803405762,0.6703
|
||||
12,0.9290380508804321,0.67348,0.9357032821655273,0.6739
|
||||
13,0.8968851718902587,0.6826,0.9126621349334717,0.6813
|
||||
14,0.8746093656349182,0.69122,0.889759654712677,0.6948
|
||||
15,0.8559883063125611,0.69704,0.8787766233444214,0.6967
|
||||
16,0.8247946104431152,0.70706,0.8809524188995361,0.6961
|
||||
17,0.8109111586380005,0.71618,0.8809684686660767,0.6933
|
||||
18,0.7986607175636291,0.7161,0.8621552461624146,0.7016
|
||||
19,0.7699470348548889,0.72814,0.8589315553665161,0.7061
|
||||
20,0.7543044216918945,0.73224,0.8606150555610657,0.7066
|
||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
1,2.0493293154907226,0.2425,1.7525886156082153,0.3748
|
||||
2,1.7320209578704835,0.3674,1.5615552814483642,0.4388
|
||||
3,1.598600202560425,0.4189,1.3815029901504516,0.4997
|
||||
4,1.5132850009155274,0.44868,1.3364418529510498,0.5207
|
||||
5,1.453274436149597,0.47022,1.2501229566574097,0.5498
|
||||
6,1.3984402522277832,0.49416,1.2111383409500123,0.5629
|
||||
7,1.3466207969284059,0.51412,1.1169193510055542,0.6038
|
||||
8,1.3081947090530395,0.52678,1.1443196024894715,0.5976
|
||||
9,1.2682366030120849,0.54628,1.0807610153198242,0.6125
|
||||
10,1.2392250786972046,0.55564,1.0270665140151978,0.6391
|
||||
11,1.2111315982818605,0.5651,1.017524287033081,0.6409
|
||||
12,1.1976571616363525,0.57106,0.9696040712356567,0.6622
|
||||
13,1.1811721408843994,0.57794,0.9810876142501831,0.6563
|
||||
14,1.16085556640625,0.58526,0.9509256943702697,0.6652
|
||||
15,1.152661986503601,0.58886,0.9255242247581482,0.6769
|
||||
16,1.1375279732131958,0.5958,0.9393579832077026,0.6742
|
||||
17,1.1235777826309203,0.59944,0.9380761775970459,0.6738
|
||||
18,1.125510050086975,0.6006,0.9149430327415466,0.6828
|
||||
19,1.107088499584198,0.60576,0.8883607380867005,0.6866
|
||||
20,1.0925483314132691,0.611,0.9142857453346253,0.6797
|
||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
1,2.064392961997986,0.23846,1.7686689800262452,0.3761
|
||||
2,1.7451289974212647,0.3644,1.5356458026885986,0.4497
|
||||
3,1.588267235183716,0.42186,1.3689933862686157,0.5059
|
||||
4,1.519119600906372,0.44644,1.3433129314422607,0.5085
|
||||
5,1.4625473209762574,0.46948,1.277887591934204,0.5426
|
||||
6,1.4183696475982666,0.48196,1.2298621862411498,0.5589
|
||||
7,1.380669080886841,0.50072,1.257154960823059,0.5392
|
||||
8,1.344734386291504,0.51252,1.20913639087677,0.5659
|
||||
9,1.3033011206817626,0.53002,1.083999695968628,0.6162
|
||||
10,1.2634273228454589,0.5458,1.0644443402290344,0.6254
|
||||
11,1.2577572822189331,0.54942,1.030274422645569,0.6359
|
||||
12,1.2248346060943605,0.56484,1.0397949484825135,0.6295
|
||||
13,1.2027203491973877,0.57098,0.9911274933815002,0.6492
|
||||
14,1.187558348007202,0.57758,0.9643227214813233,0.6593
|
||||
15,1.1724095825195313,0.5828,0.9574517963409424,0.6634
|
||||
16,1.1600826649475098,0.5883,0.9531858426094055,0.6656
|
||||
17,1.148004737739563,0.59024,0.9419389196395874,0.6644
|
||||
18,1.135836477394104,0.59494,0.9213238637924195,0.6784
|
||||
19,1.117524945716858,0.60416,0.924640416431427,0.6748
|
||||
20,1.1149262449264525,0.60376,0.8988444912910462,0.6854
|
||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
1,2.0648545223999024,0.23818,1.765181273651123,0.3742
|
||||
2,1.7573804076766968,0.362,1.535401229095459,0.4471
|
||||
3,1.611904190979004,0.41362,1.4302934280395507,0.4844
|
||||
4,1.525922943458557,0.44314,1.3388441865921021,0.5087
|
||||
5,1.467007992515564,0.46652,1.2719555583953857,0.5469
|
||||
6,1.4222887012481689,0.48284,1.248225646018982,0.5555
|
||||
7,1.373562057991028,0.50482,1.169153240585327,0.5856
|
||||
8,1.3381992527008058,0.51634,1.1345109245300293,0.6014
|
||||
9,1.3071355611419677,0.53108,1.103178568649292,0.6051
|
||||
10,1.265291601448059,0.54506,1.071216807079315,0.6169
|
||||
11,1.244923010597229,0.55354,1.068904607105255,0.6212
|
||||
12,1.2326332139205933,0.55886,1.055773473072052,0.6307
|
||||
13,1.2040435157012939,0.57052,0.9872216351509094,0.6528
|
||||
14,1.1909678496170044,0.57444,0.9747416945457459,0.6634
|
||||
15,1.16843085231781,0.58078,0.9478087964057922,0.6734
|
||||
16,1.1639410251617432,0.58364,0.9701937286376953,0.6655
|
||||
17,1.14788178440094,0.59224,0.947301069355011,0.6735
|
||||
18,1.1326425197601317,0.5989,0.9041819067955017,0.6868
|
||||
19,1.1362577977752686,0.59788,0.9516706992149353,0.6716
|
||||
20,1.1200445556259155,0.60232,0.9014985984802246,0.6861
|
||||
|
@@ -1,19 +0,0 @@
|
||||
seed,optimizer,augmentation,test_acc,robustness
|
||||
42,sgd,none,0.7088,"{'0.1': 0.6319, '0.2': 0.4336, '0.3': 0.2913}"
|
||||
42,sgd,standard,0.6859,"{'0.1': 0.5952, '0.2': 0.4019, '0.3': 0.2757}"
|
||||
42,sgd,aggressive,0.6536,"{'0.1': 0.5778, '0.2': 0.43, '0.3': 0.2943}"
|
||||
42,adam,none,0.5451,"{'0.1': 0.4221, '0.2': 0.2298, '0.3': 0.1545}"
|
||||
42,adam,standard,0.5101,"{'0.1': 0.454, '0.2': 0.2098, '0.3': 0.1324}"
|
||||
42,adam,aggressive,0.4427,"{'0.1': 0.4048, '0.2': 0.2461, '0.3': 0.1547}"
|
||||
123,sgd,none,0.6974,"{'0.1': 0.63, '0.2': 0.4452, '0.3': 0.312}"
|
||||
123,sgd,standard,0.6674,"{'0.1': 0.6252, '0.2': 0.4146, '0.3': 0.2764}"
|
||||
123,sgd,aggressive,0.6691,"{'0.1': 0.6179, '0.2': 0.4691, '0.3': 0.3423}"
|
||||
123,adam,none,0.6049,"{'0.1': 0.4685, '0.2': 0.3387, '0.3': 0.2378}"
|
||||
123,adam,standard,0.4654,"{'0.1': 0.4071, '0.2': 0.3073, '0.3': 0.2341}"
|
||||
123,adam,aggressive,0.5096,"{'0.1': 0.4624, '0.2': 0.3219, '0.3': 0.2159}"
|
||||
999,sgd,none,0.7058,"{'0.1': 0.6252, '0.2': 0.3848, '0.3': 0.2276}"
|
||||
999,sgd,standard,0.6861,"{'0.1': 0.6002, '0.2': 0.4184, '0.3': 0.2986}"
|
||||
999,sgd,aggressive,0.6595,"{'0.1': 0.5775, '0.2': 0.4165, '0.3': 0.2899}"
|
||||
999,adam,none,0.5573,"{'0.1': 0.4562, '0.2': 0.293, '0.3': 0.2167}"
|
||||
999,adam,standard,0.4835,"{'0.1': 0.4136, '0.2': 0.2221, '0.3': 0.1548}"
|
||||
999,adam,aggressive,0.5123,"{'0.1': 0.449, '0.2': 0.2571, '0.3': 0.1658}"
|
||||
|
+55
-40
@@ -15,6 +15,7 @@ import pandas as pd
|
||||
import matplotlib.pyplot as plt
|
||||
import statsmodels.api as sm
|
||||
from statsmodels.formula.api import ols
|
||||
from argparse import Namespace
|
||||
|
||||
# simple cnn model definition
|
||||
# I looked a lot at https://github.com/giusarno/SimpleCNN/blob/master/examples/cifar10/themodel.py
|
||||
@@ -24,14 +25,18 @@ from statsmodels.formula.api import ols
|
||||
class SimpleCNN(nn.Module):
|
||||
def __init__(self, num_classes=10):
|
||||
super(SimpleCNN, self).__init__()
|
||||
DROPOUT_RATE = 0.2
|
||||
|
||||
self.features = nn.Sequential(
|
||||
nn.Conv2d(3, 32, 3, padding=1), nn.ReLU(),
|
||||
nn.MaxPool2d(2),
|
||||
nn.Conv2d(32, 64, 3, padding=1), nn.ReLU(),
|
||||
nn.MaxPool2d(2),
|
||||
)
|
||||
|
||||
self.classifier = nn.Sequential(
|
||||
nn.Flatten(),
|
||||
nn.Dropout(DROPOUT_RATE),
|
||||
nn.Linear(64 * 8 * 8, 128), nn.ReLU(),
|
||||
nn.Linear(128, num_classes),
|
||||
)
|
||||
@@ -60,7 +65,7 @@ def get_data_loaders(batch_size, augmentation):
|
||||
transforms.RandomRotation(15),
|
||||
transforms.RandomCrop(32, padding=4),
|
||||
transforms.ColorJitter(brightness=0.2, contrast=0.2,
|
||||
saturation=0.2, hue=0.1),
|
||||
saturation=0.2, hue=0.1),
|
||||
transforms.ToTensor(),
|
||||
])
|
||||
else:
|
||||
@@ -84,16 +89,21 @@ def get_data_loaders(batch_size, augmentation):
|
||||
|
||||
|
||||
# train for 1 epoch
|
||||
|
||||
|
||||
def train_one_epoch(model, optimizer, criterion, dataloader, device):
|
||||
def train_one_epoch(model, optimizer, criterion, dataloader, device, aug=True):
|
||||
model.train()
|
||||
running_loss = 0.0
|
||||
correct = 0
|
||||
total = 0
|
||||
|
||||
for inputs, targets in dataloader:
|
||||
inputs, targets = inputs.to(device), targets.to(device)
|
||||
optimizer.zero_grad()
|
||||
|
||||
if aug:
|
||||
noisstd = np.random.uniform(0, 0.2)
|
||||
inputs = inputs + noisstd * torch.randn_like(inputs)
|
||||
# inputs = torch.clamp(inputs, 0.0, 1.0)
|
||||
|
||||
outputs = model(inputs)
|
||||
loss = criterion(outputs, targets)
|
||||
loss.backward()
|
||||
@@ -103,14 +113,13 @@ def train_one_epoch(model, optimizer, criterion, dataloader, device):
|
||||
_, predicted = outputs.max(1)
|
||||
correct += predicted.eq(targets).sum().item()
|
||||
total += targets.size(0)
|
||||
|
||||
epoch_loss = running_loss / total
|
||||
epoch_acc = correct / total
|
||||
return epoch_loss, epoch_acc
|
||||
|
||||
|
||||
# eval on clean data
|
||||
|
||||
|
||||
def evaluate(model, criterion, dataloader, device):
|
||||
model.eval()
|
||||
running_loss = 0.0
|
||||
@@ -132,8 +141,6 @@ def evaluate(model, criterion, dataloader, device):
|
||||
|
||||
|
||||
# eval robustness under gaussian noise
|
||||
|
||||
|
||||
def evaluate_robustness(model, dataloader, device, noise_std):
|
||||
model.eval()
|
||||
correct = 0
|
||||
@@ -141,8 +148,9 @@ def evaluate_robustness(model, dataloader, device, noise_std):
|
||||
with torch.no_grad():
|
||||
for inputs, targets in dataloader:
|
||||
noisy_inputs = inputs + noise_std * torch.randn_like(inputs)
|
||||
noisy_inputs = torch.clamp(noisy_inputs, 0.0, 1.0)
|
||||
# noisy_inputs = torch.clamp(noisy_inputs, 0.0, 1.0)
|
||||
noisy_inputs, targets = noisy_inputs.to(device), targets.to(device)
|
||||
|
||||
outputs = model(noisy_inputs)
|
||||
_, predicted = outputs.max(1)
|
||||
correct += predicted.eq(targets).sum().item()
|
||||
@@ -152,50 +160,52 @@ def evaluate_robustness(model, dataloader, device, noise_std):
|
||||
|
||||
|
||||
def analyze_results(results_path='results.json'):
|
||||
import json
|
||||
import pandas as pd
|
||||
import matplotlib.pyplot as plt
|
||||
from statsmodels.formula.api import ols
|
||||
import statsmodels.api as sm
|
||||
with open(results_path) as f:
|
||||
results = json.load(f)
|
||||
df = pd.DataFrame(results)
|
||||
df.to_csv('analysis_results.csv', index=False)
|
||||
|
||||
with open(results_path) as f:
|
||||
results = json.load(f)
|
||||
df = pd.DataFrame(results)
|
||||
df.to_csv('analysis_results.csv', index=False)
|
||||
# full ANOVA w/interaction
|
||||
model = ols('test_acc ~ C(optimizer) * C(augmentation)', data=df).fit()
|
||||
anova_table = sm.stats.anova_lm(model, typ=2)
|
||||
print('anova on test accuracy:')
|
||||
print(anova_table)
|
||||
|
||||
# full ANOVA w/interaction
|
||||
model = ols('test_acc ~ C(optimizer) * C(augmentation)', data=df).fit()
|
||||
anova_table = sm.stats.anova_lm(model, typ=2)
|
||||
print('anova on test accuracy:')
|
||||
print(anova_table)
|
||||
|
||||
# composite label
|
||||
df['condition'] = df['optimizer'] + '_' + df['augmentation']
|
||||
df.plot.bar(x='condition', y='test_acc', rot=45)
|
||||
plt.ylabel('test accuracy')
|
||||
plt.tight_layout()
|
||||
plt.savefig('test_acc_comparison.png')
|
||||
print('saved plot to test_acc_comparison.png')
|
||||
# composite label
|
||||
df['condition'] = df['optimizer'] + '_' + df['augmentation']
|
||||
df.plot.bar(x='condition', y='test_acc', rot=45)
|
||||
plt.ylabel('test accuracy')
|
||||
plt.tight_layout()
|
||||
|
||||
# ripped off the py docs --> viridis colormap for bars
|
||||
colors = plt.cm.viridis(np.linspace(0.2, 0.8, len(df)))
|
||||
ax = df.plot.bar(x='condition', y='test_acc', rot=45, color=colors)
|
||||
plt.ylabel('test accuracy')
|
||||
plt.tight_layout()
|
||||
plt.savefig('test_acc_comparison.png')
|
||||
print('saved plot to test_acc_comparison.png')
|
||||
|
||||
|
||||
# main (PUBLIC STATIC VOID AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA)
|
||||
def run_experiments(args):
|
||||
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
|
||||
results = []
|
||||
|
||||
optimizers = {
|
||||
'sgd': lambda params: optim.SGD(params, lr=args.lr, momentum=0.9),
|
||||
'adam': lambda params: optim.Adam(params, lr=args.lr)
|
||||
'sgd': lambda params: optim.SGD(params, lr=args.lr, momentum=0.9, weight_decay=1e-3),
|
||||
'adam': lambda params: optim.Adam(params, lr=args.lr, weight_decay=1e-3)
|
||||
}
|
||||
augmentations = ['none', 'standard', 'aggressive']
|
||||
|
||||
seeds = [42, 123, 999]
|
||||
for seed in seeds:
|
||||
print("SEED", seed)
|
||||
torch.manual_seed(seed)
|
||||
np.random.seed(seed)
|
||||
|
||||
for opt_name in optimizers:
|
||||
for aug in augmentations:
|
||||
train_loader, test_loader = get_data_loaders(args.batch_size, aug)
|
||||
noise_levels = [0.1, 0.2, 0.3]
|
||||
model = SimpleCNN(num_classes=10).to(device)
|
||||
optimizer = optimizers[opt_name](model.parameters())
|
||||
criterion = nn.CrossEntropyLoss()
|
||||
@@ -207,6 +217,7 @@ def run_experiments(args):
|
||||
for epoch in range(args.epochs):
|
||||
train_loss, train_acc = train_one_epoch(
|
||||
model, optimizer, criterion, train_loader, device)
|
||||
|
||||
test_loss, test_acc = evaluate(
|
||||
model, criterion, test_loader, device)
|
||||
|
||||
@@ -217,15 +228,15 @@ def run_experiments(args):
|
||||
history['test_acc'].append(test_acc)
|
||||
|
||||
print(f"[{opt_name}][{aug}][epoch {epoch + 1}] "
|
||||
f"train_loss={train_loss:.4f}, train_acc={train_acc:.4f}, "
|
||||
f"test_acc={test_acc:.4f}")
|
||||
f"train_loss={train_loss:.4f}, train_acc={train_acc:.4f}, "
|
||||
f"test_acc={test_acc:.4f}")
|
||||
|
||||
noise_levels = [0.1, 0.2, 0.3]
|
||||
robustness = {noise: evaluate_robustness(
|
||||
model, test_loader, device, noise) for noise in noise_levels}
|
||||
|
||||
pd.DataFrame(history).to_csv(
|
||||
f"history_{opt_name}_{aug}_{seed}.csv", index=False)
|
||||
f"analysis/history_{opt_name}_{aug}_{seed}.csv", index=False)
|
||||
|
||||
results.append({
|
||||
'seed': seed,
|
||||
'optimizer': opt_name,
|
||||
@@ -245,11 +256,15 @@ if __name__ == '__main__':
|
||||
|
||||
parser.add_argument('--batch_size', type=int, default=128)
|
||||
parser.add_argument('--lr', type=float, default=0.01)
|
||||
parser.add_argument('--epochs', type=int, default=10)
|
||||
parser.add_argument('--epochs', type=int, default=20)
|
||||
parser.add_argument('--analyze', action='store_true',
|
||||
help='run analysis on results')
|
||||
help='run analysis on results')
|
||||
|
||||
args = parser.parse_args()
|
||||
print(json.dumps(vars(args)))
|
||||
print(args)
|
||||
# args = Namespace(batch_size=128, lr=0.01, epochs=20, analyze=False)
|
||||
# exit(1)
|
||||
|
||||
if args.analyze:
|
||||
analyze_results()
|
||||
|
||||
@@ -0,0 +1,19 @@
|
||||
seed,optimizer,augmentation,test_acc,robustness
|
||||
42,sgd,none,0.7013,"{'0.1': 0.6895, '0.2': 0.6449, '0.3': 0.5712}"
|
||||
42,sgd,standard,0.6791,"{'0.1': 0.6702, '0.2': 0.6315, '0.3': 0.5601}"
|
||||
42,sgd,aggressive,0.6703,"{'0.1': 0.6505, '0.2': 0.587, '0.3': 0.5143}"
|
||||
42,adam,none,0.5658,"{'0.1': 0.5575, '0.2': 0.5204, '0.3': 0.4498}"
|
||||
42,adam,standard,0.4394,"{'0.1': 0.4385, '0.2': 0.4069, '0.3': 0.3476}"
|
||||
42,adam,aggressive,0.45,"{'0.1': 0.4467, '0.2': 0.4168, '0.3': 0.3557}"
|
||||
123,sgd,none,0.7002,"{'0.1': 0.6902, '0.2': 0.6511, '0.3': 0.5781}"
|
||||
123,sgd,standard,0.6951,"{'0.1': 0.6833, '0.2': 0.6248, '0.3': 0.5406}"
|
||||
123,sgd,aggressive,0.6766,"{'0.1': 0.6661, '0.2': 0.6188, '0.3': 0.5369}"
|
||||
123,adam,none,0.4857,"{'0.1': 0.4851, '0.2': 0.4572, '0.3': 0.4191}"
|
||||
123,adam,standard,0.4536,"{'0.1': 0.4517, '0.2': 0.4216, '0.3': 0.3551}"
|
||||
123,adam,aggressive,0.4542,"{'0.1': 0.4568, '0.2': 0.4363, '0.3': 0.3909}"
|
||||
999,sgd,none,0.6961,"{'0.1': 0.6845, '0.2': 0.6509, '0.3': 0.5702}"
|
||||
999,sgd,standard,0.6896,"{'0.1': 0.6757, '0.2': 0.6251, '0.3': 0.5515}"
|
||||
999,sgd,aggressive,0.663,"{'0.1': 0.6542, '0.2': 0.6143, '0.3': 0.5326}"
|
||||
999,adam,none,0.5189,"{'0.1': 0.5138, '0.2': 0.4787, '0.3': 0.4115}"
|
||||
999,adam,standard,0.4934,"{'0.1': 0.4822, '0.2': 0.4312, '0.3': 0.34}"
|
||||
999,adam,aggressive,0.4039,"{'0.1': 0.4053, '0.2': 0.3814, '0.3': 0.3183}"
|
||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
1,2.0048419479751587,0.26248,1.6749397346496582,0.3807
|
||||
2,1.803226097946167,0.34018,1.5852585729598998,0.4277
|
||||
3,1.7538686734390259,0.3595,1.5596578207015992,0.44
|
||||
4,1.7227864822769166,0.36774,1.5332639671325683,0.4412
|
||||
5,1.707428610610962,0.37698,1.5266790023803711,0.446
|
||||
6,1.687287041053772,0.3853,1.5208749200820924,0.4534
|
||||
7,1.6827863134002685,0.38752,1.4709485807418823,0.4678
|
||||
8,1.6679418573379516,0.39552,1.4785521780014037,0.4569
|
||||
9,1.6778243729400635,0.38932,1.4824026586532593,0.4535
|
||||
10,1.661981136817932,0.39328,1.4527232948303224,0.4733
|
||||
11,1.6635226394271851,0.39552,1.4467358991622925,0.4761
|
||||
12,1.6477233642578124,0.39888,1.4165599590301514,0.4825
|
||||
13,1.64288627204895,0.4028,1.4934470342636108,0.4554
|
||||
14,1.64764131275177,0.40076,1.3920714778900147,0.4971
|
||||
15,1.6471917071151734,0.39942,1.4170124416351317,0.4897
|
||||
16,1.632711910057068,0.40306,1.437167017364502,0.4766
|
||||
17,1.6346079250717163,0.40256,1.4856373008728028,0.4602
|
||||
18,1.6376697371673583,0.40028,1.441266096687317,0.4795
|
||||
19,1.630727212524414,0.40478,1.405259503364563,0.4869
|
||||
20,1.6380860889434814,0.40302,1.500902590560913,0.4542
|
||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
1,1.9924071334075928,0.2727,1.6629206789016724,0.3942
|
||||
2,1.782769969177246,0.34778,1.6269580562591552,0.4111
|
||||
3,1.7246631295776367,0.36938,1.512624101638794,0.4465
|
||||
4,1.699350281906128,0.37616,1.561422179031372,0.4365
|
||||
5,1.6983959941864013,0.37842,1.5700433086395265,0.4367
|
||||
6,1.6805000713348388,0.38506,1.4903933980941773,0.4524
|
||||
7,1.6756603227996827,0.39022,1.589101205253601,0.4264
|
||||
8,1.6851841028594972,0.38372,1.53794698677063,0.4287
|
||||
9,1.667366398010254,0.39178,1.489094132232666,0.4576
|
||||
10,1.6613886919021605,0.39288,1.5648905296325684,0.4195
|
||||
11,1.6709651499176026,0.38908,1.4680940185546876,0.4564
|
||||
12,1.6781271075439452,0.38556,1.6323107133865356,0.3965
|
||||
13,1.6682115633773804,0.38786,1.67539608707428,0.394
|
||||
14,1.6545760455322265,0.39296,1.484992802810669,0.4598
|
||||
15,1.664471877670288,0.39126,1.4973457614898682,0.4527
|
||||
16,1.6631774948501588,0.39178,1.4977839450836181,0.4523
|
||||
17,1.6620827933502198,0.39418,1.4580686128616334,0.4648
|
||||
18,1.6693129856109619,0.3915,1.4670265132904052,0.4499
|
||||
19,1.6571670418548583,0.39328,1.5775521347045898,0.4209
|
||||
20,1.6555169297027588,0.39302,1.4923007045745849,0.45
|
||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
1,2.0259005422592162,0.26528,1.7835535663604736,0.3501
|
||||
2,1.867787606163025,0.313,1.7164635316848755,0.3679
|
||||
3,1.8262985235214233,0.33078,1.6985314193725587,0.3729
|
||||
4,1.8109176992416383,0.33478,1.6716279788970947,0.3847
|
||||
5,1.7937457250976563,0.34112,1.6525777326583861,0.3855
|
||||
6,1.7862395941925049,0.3438,1.6767313753128053,0.3771
|
||||
7,1.7756537421417236,0.34192,1.649860231399536,0.3899
|
||||
8,1.7808906607055663,0.34136,1.642415731048584,0.3915
|
||||
9,1.7794113501358033,0.33866,1.6533834308624267,0.3913
|
||||
10,1.7733372591781615,0.34298,1.679184874534607,0.3706
|
||||
11,1.7687813821411134,0.34438,1.6319498205184937,0.3919
|
||||
12,1.7672993996810913,0.34524,1.5924089086532593,0.4055
|
||||
13,1.7586094732284545,0.34774,1.5894474613189697,0.4183
|
||||
14,1.7682015967178344,0.34308,1.6354400550842285,0.3904
|
||||
15,1.7509896782684327,0.35068,1.6326687992095947,0.3796
|
||||
16,1.7584374965667724,0.34796,1.633549732208252,0.3948
|
||||
17,1.7580876070785523,0.35102,1.5947255432128906,0.4044
|
||||
18,1.750145943069458,0.35058,1.5891325847625732,0.418
|
||||
19,1.7573828769683837,0.3461,1.5960699188232421,0.4032
|
||||
20,1.7578185536956787,0.3469,1.5921159523010253,0.4039
|
||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
1,1.8579250992584229,0.32392,1.5558856401443482,0.4313
|
||||
2,1.6377606032562255,0.4044,1.5286170751571655,0.4396
|
||||
3,1.5881630603408814,0.41738,1.5185808382034303,0.4484
|
||||
4,1.5531442667388915,0.43602,1.4579217964172364,0.4586
|
||||
5,1.5474866276931762,0.43182,1.45462444896698,0.4727
|
||||
6,1.5150492757415772,0.44956,1.4247750133514405,0.475
|
||||
7,1.5141647922515868,0.44442,1.4379277662277221,0.4691
|
||||
8,1.5064603635406495,0.44778,1.4320051357269288,0.4814
|
||||
9,1.4982417543029785,0.45322,1.4486036586761475,0.4788
|
||||
10,1.495431781539917,0.45466,1.4063307929992677,0.4955
|
||||
11,1.477474406814575,0.46004,1.3848083011627197,0.5074
|
||||
12,1.478807368774414,0.46202,1.4433747045516967,0.4806
|
||||
13,1.481698868713379,0.45994,1.4207568691253663,0.4875
|
||||
14,1.4778631386184693,0.46108,1.3489213497161865,0.5107
|
||||
15,1.4712807468032838,0.46604,1.3919997245788573,0.4893
|
||||
16,1.483530824584961,0.46112,1.4437157917022705,0.4853
|
||||
17,1.4729563687133789,0.4616,1.3912005447387696,0.496
|
||||
18,1.4708208094787598,0.46484,1.4403230434417724,0.4778
|
||||
19,1.469524460105896,0.46858,1.3713474117279052,0.5112
|
||||
20,1.4658287371444703,0.46598,1.4386186960220337,0.4857
|
||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
1,1.7651092416763305,0.34864,1.4801026742935182,0.4452
|
||||
2,1.4773385808563233,0.4608,1.4107468299865722,0.4928
|
||||
3,1.4245695472717286,0.48826,1.3724896883010864,0.5095
|
||||
4,1.3900219127273559,0.49736,1.2948982368469237,0.5366
|
||||
5,1.3694689385223389,0.50896,1.2803543266296387,0.5367
|
||||
6,1.3547902798843383,0.51456,1.2770936399459838,0.5403
|
||||
7,1.3447893646621705,0.51488,1.2862837057113647,0.5363
|
||||
8,1.3417145071411132,0.519,1.2915318742752075,0.5294
|
||||
9,1.338515231552124,0.52032,1.247458812904358,0.5552
|
||||
10,1.3313588520050048,0.52276,1.23068475151062,0.5559
|
||||
11,1.3147309407806396,0.52892,1.2065896244049072,0.5765
|
||||
12,1.3206113652801514,0.52802,1.2014692079544067,0.5784
|
||||
13,1.3099163648223877,0.52914,1.219766689491272,0.5604
|
||||
14,1.3167620611953736,0.52754,1.1866582777023316,0.5766
|
||||
15,1.3133597641754151,0.53076,1.2739620433807373,0.5413
|
||||
16,1.3288053150939942,0.5251,1.280159574699402,0.5474
|
||||
17,1.3213993626785279,0.5305,1.3356346948623656,0.5339
|
||||
18,1.3234788956451415,0.5274,1.2488118535995483,0.5621
|
||||
19,1.3162768488693237,0.53068,1.1890131019592285,0.5786
|
||||
20,1.3078575289154053,0.53372,1.2257861446380616,0.5658
|
||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
1,1.8653128273773194,0.32796,1.611533346939087,0.3995
|
||||
2,1.612140337791443,0.41292,1.623063315963745,0.4098
|
||||
3,1.5402255586242677,0.44038,1.4548933393478394,0.4697
|
||||
4,1.5275923446655273,0.44896,1.440786859703064,0.4802
|
||||
5,1.4979061844635009,0.45434,1.417161144065857,0.4818
|
||||
6,1.4915729135131837,0.46008,1.3997222789764405,0.4988
|
||||
7,1.4728927141571044,0.46468,1.387175965309143,0.4972
|
||||
8,1.4769946060943604,0.46384,1.466834031867981,0.4687
|
||||
9,1.4653232444000244,0.46896,1.4313162572860718,0.4816
|
||||
10,1.4634774406433106,0.47178,1.3978804470062256,0.4935
|
||||
11,1.464304472732544,0.47028,1.4218554107666015,0.4782
|
||||
12,1.4602648656463624,0.47172,1.4064278043746947,0.4873
|
||||
13,1.4479452781295776,0.47628,1.4901286466598511,0.4706
|
||||
14,1.4542893864059447,0.47666,1.3517237024307251,0.5077
|
||||
15,1.4511225904846192,0.4727,1.3578523971557617,0.5074
|
||||
16,1.4690848288726808,0.47104,1.3588831977844238,0.5053
|
||||
17,1.4494867483520508,0.47718,1.3755928480148316,0.5045
|
||||
18,1.460067735671997,0.4717,1.3654316268920899,0.5149
|
||||
19,1.4619887506103515,0.47406,1.3814095928192138,0.5031
|
||||
20,1.4534882698059082,0.47412,1.34085482711792,0.5189
|
||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
1,2.0278418547058106,0.24944,1.8780883220672608,0.3251
|
||||
2,1.8143817639541626,0.331,1.6300555017471314,0.4045
|
||||
3,1.7264616962432862,0.3622,1.597921866607666,0.4111
|
||||
4,1.6720347478866577,0.38138,1.608277184677124,0.41
|
||||
5,1.6579552675628662,0.3885,1.5234451871871948,0.435
|
||||
6,1.6298340225982666,0.39974,1.5039015756607055,0.4597
|
||||
7,1.6189628750610352,0.40322,1.5221681720733642,0.4422
|
||||
8,1.6198538191986085,0.40798,1.4737193891525269,0.4565
|
||||
9,1.6145962512969971,0.4075,1.466329651069641,0.4629
|
||||
10,1.621643498878479,0.40454,1.6072639640808106,0.4081
|
||||
11,1.6055096750259399,0.40826,1.527749220275879,0.4358
|
||||
12,1.6175734860229491,0.40692,1.4493362300872803,0.4722
|
||||
13,1.599906416091919,0.4124,1.4468452342987062,0.4715
|
||||
14,1.5933954864883424,0.41398,1.4764380693435668,0.4626
|
||||
15,1.5933787399291992,0.41372,1.533870811843872,0.4468
|
||||
16,1.5964966577911377,0.41302,1.4542985107421875,0.467
|
||||
17,1.6135705094146728,0.40712,1.4721424545288087,0.4527
|
||||
18,1.5964763764190675,0.41558,1.4527687072753905,0.4593
|
||||
19,1.591530082244873,0.41652,1.4388617012023925,0.4642
|
||||
20,1.589130754928589,0.41602,1.4646002044677735,0.4536
|
||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
1,2.0309293317031862,0.24762,1.7998561183929442,0.3421
|
||||
2,1.7957917514801025,0.33852,1.6648591684341432,0.3857
|
||||
3,1.7348672610855103,0.35496,1.654585442352295,0.4019
|
||||
4,1.7112164305877686,0.36548,1.5846896692276,0.4141
|
||||
5,1.6914103266525269,0.37268,1.5373584619522094,0.4395
|
||||
6,1.676686876564026,0.37698,1.637582375717163,0.3837
|
||||
7,1.6700877303695678,0.38384,1.5936841482162476,0.4161
|
||||
8,1.6569111339569091,0.38968,1.5129856206893921,0.4351
|
||||
9,1.6577720043182373,0.3908,1.499471364212036,0.4555
|
||||
10,1.6537026256942748,0.39124,1.537830891418457,0.4293
|
||||
11,1.6379817530059815,0.401,1.5753344255447388,0.4145
|
||||
12,1.64174579536438,0.39604,1.6890381210327148,0.3761
|
||||
13,1.6474020536422729,0.39648,1.5377606107711792,0.4443
|
||||
14,1.631554557762146,0.40042,1.5029741109848023,0.4553
|
||||
15,1.6246128929138184,0.40476,1.4533207773208618,0.4794
|
||||
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|
||||
17,1.6160261626815795,0.40666,1.4699448907852173,0.4644
|
||||
18,1.6250457259750366,0.40384,1.43235032081604,0.4734
|
||||
19,1.6166238045501709,0.40848,1.6371612733840943,0.3933
|
||||
20,1.6181047994995117,0.40592,1.5512634952545166,0.4394
|
||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
1,1.9290429125213624,0.29754,1.6215127836227416,0.4071
|
||||
2,1.7239283940124512,0.36334,1.738866775894165,0.3631
|
||||
3,1.6748943075942992,0.38214,1.5513272310256958,0.4274
|
||||
4,1.6455059506988525,0.39562,1.508594535446167,0.4514
|
||||
5,1.624495430870056,0.40286,1.5517113952636719,0.4313
|
||||
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|
||||
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|
||||
8,1.5953116985702516,0.41482,1.4611921619415282,0.4639
|
||||
9,1.5824666970062256,0.4168,1.4630669622421264,0.4662
|
||||
10,1.5835675071334838,0.4205,1.4603066038131713,0.4595
|
||||
11,1.5734461785125733,0.42412,1.4167298784255982,0.4862
|
||||
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|
||||
13,1.5812189110946655,0.42152,1.4088649713516235,0.4889
|
||||
14,1.5847568724822998,0.42022,1.4178233968734741,0.4823
|
||||
15,1.576828946876526,0.42272,1.4326917642593384,0.4809
|
||||
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|
||||
17,1.5560429149246215,0.43062,1.4361749185562134,0.4727
|
||||
18,1.5523672427749633,0.43476,1.4626990962982178,0.4581
|
||||
19,1.5581282339859008,0.42906,1.4140942724227905,0.4822
|
||||
20,1.5584481320190429,0.42816,1.4160622207641602,0.4934
|
||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
1,2.0803506112289427,0.23,1.8052742357254028,0.3649
|
||||
2,1.795086921234131,0.35172,1.513138659286499,0.4536
|
||||
3,1.6374745911407471,0.4064,1.4209930673599243,0.4924
|
||||
4,1.5572372722625731,0.43516,1.3496723909378052,0.5132
|
||||
5,1.51327647895813,0.45306,1.2944782655715943,0.5399
|
||||
6,1.4705483396148682,0.47014,1.2843341438293456,0.5457
|
||||
7,1.419877719154358,0.48872,1.2024114828109742,0.5757
|
||||
8,1.3825100279998779,0.50334,1.1727403156280518,0.5862
|
||||
9,1.349350403137207,0.51694,1.1227089519500733,0.6043
|
||||
10,1.3265677324295044,0.5264,1.1120436277389527,0.6032
|
||||
11,1.2989790354156494,0.53608,1.09653370552063,0.6181
|
||||
12,1.271951921310425,0.5476,1.0683507353782653,0.6288
|
||||
13,1.252325573387146,0.55396,1.0399812242507935,0.6344
|
||||
14,1.2363645384979247,0.56054,1.005698392677307,0.6526
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||||
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||||
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|
||||
17,1.1860296492004394,0.58086,0.9641439270019532,0.659
|
||||
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|
||||
19,1.1792696018218993,0.57868,0.9344734144210816,0.6784
|
||||
20,1.1561780276107787,0.5907,0.9342237223625183,0.6766
|
||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
1,2.0498613494491575,0.24344,1.827182295036316,0.3315
|
||||
2,1.7751250897216797,0.35796,1.5328051206588744,0.4525
|
||||
3,1.6295417392730713,0.40922,1.4538747985839844,0.4708
|
||||
4,1.556714581451416,0.4379,1.3427102214813234,0.5272
|
||||
5,1.5068591191864014,0.45632,1.3105488367080689,0.5268
|
||||
6,1.4472922039413452,0.48044,1.2710780916213988,0.5427
|
||||
7,1.416664746017456,0.49122,1.184156767177582,0.5828
|
||||
8,1.3932555706787109,0.50056,1.1800921089172363,0.5861
|
||||
9,1.354030286064148,0.51452,1.11541519241333,0.6093
|
||||
10,1.3268484888839722,0.52786,1.0645180792808533,0.6262
|
||||
11,1.2946206281661987,0.53744,1.0727122479438782,0.621
|
||||
12,1.2794264878082275,0.54414,1.044085719871521,0.6339
|
||||
13,1.2605588024902343,0.55172,1.0073520627975463,0.6379
|
||||
14,1.2451800212478639,0.55708,0.989365707397461,0.6558
|
||||
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||||
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|
||||
17,1.2089972533798217,0.57022,0.9678337673187256,0.6643
|
||||
18,1.1906279234695434,0.57802,0.9852053064346313,0.6507
|
||||
19,1.1747162343597413,0.58308,0.9369933985710144,0.6728
|
||||
20,1.160263595199585,0.58824,0.9429312159538269,0.6703
|
||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
1,2.0627308975601197,0.24156,1.80689540309906,0.3478
|
||||
2,1.7932613165283202,0.35134,1.6185862417221069,0.4216
|
||||
3,1.658083698501587,0.39922,1.4435414199829102,0.4786
|
||||
4,1.563901499633789,0.43574,1.3859216415405273,0.5008
|
||||
5,1.5054525188827514,0.45402,1.2911276792526245,0.5423
|
||||
6,1.450156503715515,0.47896,1.2477545137405395,0.5579
|
||||
7,1.4208231299591065,0.49338,1.2044965368270875,0.5692
|
||||
8,1.3701529790115357,0.50918,1.1438802488327027,0.5956
|
||||
9,1.3449303218460082,0.51834,1.1281687593460084,0.6007
|
||||
10,1.3100552983856202,0.5339,1.0984893451690674,0.617
|
||||
11,1.2957517767715454,0.53988,1.0663194850921631,0.6201
|
||||
12,1.2759582391357422,0.54506,1.0382993364334105,0.6332
|
||||
13,1.256755221672058,0.55376,1.0107640748977662,0.638
|
||||
14,1.240665273475647,0.55926,1.0230664975166321,0.6393
|
||||
15,1.232104567527771,0.55946,1.0093883613586425,0.645
|
||||
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|
||||
17,1.202742511291504,0.57248,0.9765661770820617,0.654
|
||||
18,1.1869954927825928,0.57676,0.9522229454994202,0.6696
|
||||
19,1.1841716981315613,0.5796,0.982388532447815,0.6555
|
||||
20,1.1647253083992004,0.58448,0.9557765811920166,0.663
|
||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
1,1.933640638999939,0.29732,1.6238486095428466,0.419
|
||||
2,1.5058992380523681,0.4574,1.416843348312378,0.4962
|
||||
3,1.3495764307403564,0.51736,1.2509430753707886,0.5525
|
||||
4,1.2513321809768676,0.55462,1.1895510234832765,0.5781
|
||||
5,1.1647147640228273,0.58834,1.0852176672935485,0.6106
|
||||
6,1.090117392807007,0.61272,1.0372767268180847,0.6397
|
||||
7,1.0261711755180358,0.6359,1.0134801021575928,0.6398
|
||||
8,0.9832253789138794,0.65152,0.958988918209076,0.6642
|
||||
9,0.9298850146102905,0.67178,0.9321723978996277,0.6715
|
||||
10,0.8931379676055908,0.68462,0.9411900254249572,0.6734
|
||||
11,0.8506363994216919,0.69908,0.9130176817893982,0.6856
|
||||
12,0.8162826980781556,0.71196,0.9254231359481812,0.6771
|
||||
13,0.7824999229240418,0.72322,0.8887297651290894,0.69
|
||||
14,0.7469561821365357,0.73758,0.8926811159133912,0.6945
|
||||
15,0.7194658122444153,0.7479,0.8924074723243713,0.6951
|
||||
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|
||||
17,0.6697472100067139,0.76272,0.9309483677864074,0.6851
|
||||
18,0.64141212266922,0.77758,0.9145923362731934,0.6949
|
||||
19,0.6034097666549683,0.78874,0.9149182550430298,0.6954
|
||||
20,0.5872987679862977,0.7941,0.8907693174362182,0.7002
|
||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
1,2.0053396127319334,0.26608,1.7093295513153077,0.3923
|
||||
2,1.5551787852859498,0.44096,1.4028151916503906,0.4985
|
||||
3,1.3658983665466309,0.51162,1.303923954963684,0.5425
|
||||
4,1.2634439575958252,0.54832,1.163003251361847,0.5884
|
||||
5,1.1752150338745118,0.58098,1.1534721800804137,0.5867
|
||||
6,1.0963337196731568,0.6116,1.0367407133102418,0.6368
|
||||
7,1.0309874046707153,0.6359,1.01473597574234,0.6424
|
||||
8,0.9726004527282714,0.65736,0.9714125958442688,0.6589
|
||||
9,0.9323004844665528,0.67234,0.9494790088653564,0.6647
|
||||
10,0.8843243282318115,0.68848,0.9313362251281738,0.6754
|
||||
11,0.8454029673957825,0.70276,0.9059185691833496,0.6839
|
||||
12,0.8084154852294921,0.71458,0.9137783187866211,0.6844
|
||||
13,0.7736339636802674,0.72754,0.8896457827568054,0.6905
|
||||
14,0.7404502736854554,0.7391,0.9187201057434082,0.6847
|
||||
15,0.7178288528823853,0.74732,0.8655570640563964,0.7029
|
||||
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|
||||
17,0.6591360913085937,0.7693,0.9042986038208007,0.6946
|
||||
18,0.6323869649124145,0.77696,0.8995812829971314,0.7046
|
||||
19,0.6078444783401489,0.78464,0.9112963752746582,0.7003
|
||||
20,0.5815039796447754,0.79348,0.8971220227241516,0.7013
|
||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
1,1.9614395635604858,0.28388,1.643307664680481,0.4046
|
||||
2,1.5448385535430909,0.44616,1.395233334159851,0.4981
|
||||
3,1.384000219039917,0.50478,1.2697911640167237,0.5481
|
||||
4,1.27566444480896,0.5418,1.2024863681793212,0.5712
|
||||
5,1.1857435577011108,0.57704,1.110471813774109,0.5998
|
||||
6,1.10453219291687,0.60846,1.063853458595276,0.6177
|
||||
7,1.0465589532089234,0.63092,1.056383687210083,0.6266
|
||||
8,0.9939296613693237,0.65138,1.0162584516525268,0.6429
|
||||
9,0.952554736328125,0.66554,0.9766125122070313,0.6542
|
||||
10,0.9012007156181335,0.68404,0.9544676315307618,0.6643
|
||||
11,0.8649646133804322,0.69644,0.9271421590805053,0.676
|
||||
12,0.8223739467048645,0.70954,0.9386976690292358,0.6767
|
||||
13,0.7874418495559692,0.72296,0.9196794429779053,0.679
|
||||
14,0.7571423944664002,0.73368,0.9027493181228637,0.6858
|
||||
15,0.7220863299465179,0.74638,0.902780525970459,0.6937
|
||||
16,0.6927142573738098,0.7568,0.8872590173721313,0.6978
|
||||
17,0.6688128486442566,0.7631,0.8854528800964355,0.7009
|
||||
18,0.6569424513626099,0.769,0.8944921180725097,0.6999
|
||||
19,0.6169235229301453,0.78028,0.886359746170044,0.6992
|
||||
20,0.5988713124084473,0.78786,0.9267883558273315,0.6961
|
||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
1,2.054507377700806,0.24836,1.7629061944961548,0.3766
|
||||
2,1.7023405939102172,0.38108,1.4944005809783936,0.4511
|
||||
3,1.5391481832122802,0.44006,1.3729140111923217,0.5054
|
||||
4,1.48024245677948,0.46148,1.3319352336883545,0.5222
|
||||
5,1.4120918664550781,0.48858,1.2639450727462769,0.5524
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||||
6,1.3601713945770264,0.51062,1.1844155906677245,0.5765
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||||
7,1.3003378784942627,0.53042,1.153577501964569,0.5892
|
||||
8,1.2586501470565796,0.54992,1.0892585767745973,0.6125
|
||||
9,1.2181877610397338,0.56466,1.0839576932907105,0.621
|
||||
10,1.1902454167175294,0.57382,1.0581496836662292,0.6269
|
||||
11,1.1582570567703248,0.58646,1.0145035231590271,0.6385
|
||||
12,1.1427707640457154,0.5913,0.9702991489410401,0.6493
|
||||
13,1.1167496506881713,0.60266,0.9598955163002014,0.6567
|
||||
14,1.1066592629623413,0.60824,0.9935148837089539,0.652
|
||||
15,1.0919563820648193,0.61256,0.9485135807991028,0.6679
|
||||
16,1.07323411693573,0.61778,0.9448822968482972,0.6692
|
||||
17,1.0547150045776368,0.62656,0.9020288042068482,0.6852
|
||||
18,1.0447941234588622,0.62932,0.8850298257827759,0.6878
|
||||
19,1.0325043148803712,0.63322,0.8606620573997498,0.7026
|
||||
20,1.0181197985839843,0.64104,0.8649613096237183,0.6951
|
||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
1,2.035904112930298,0.2552,1.7296793979644776,0.3902
|
||||
2,1.708837389717102,0.3825,1.4909840774536134,0.4608
|
||||
3,1.539429332046509,0.4392,1.3871454195022583,0.5077
|
||||
4,1.4547308851242065,0.47234,1.304142402458191,0.5314
|
||||
5,1.38470291431427,0.50112,1.2006133085250854,0.5736
|
||||
6,1.3219089529800414,0.52174,1.1560321960449218,0.5886
|
||||
7,1.2655390045928956,0.54448,1.0789848009109497,0.62
|
||||
8,1.2301358563995362,0.56088,1.0741067754745484,0.615
|
||||
9,1.1941656197357178,0.57536,1.0340390792846679,0.6317
|
||||
10,1.1679337029647827,0.58268,0.9948765556335449,0.6496
|
||||
11,1.1529586157226563,0.58736,0.9822504173278809,0.6523
|
||||
12,1.120876918144226,0.59952,0.9725488736152649,0.6542
|
||||
13,1.100623334312439,0.6071,0.9678766529083251,0.6636
|
||||
14,1.0869316192626952,0.61298,0.9187479448318482,0.6743
|
||||
15,1.066665187110901,0.6217,0.9006691802978516,0.6889
|
||||
16,1.0647497671890258,0.62334,0.8880218561172485,0.6859
|
||||
17,1.0438396575164794,0.62966,0.8780597747802734,0.6906
|
||||
18,1.0385048112487794,0.63038,0.8763846193313599,0.6939
|
||||
19,1.0159992222976684,0.64046,0.8701905465126037,0.6895
|
||||
20,1.0131669343566894,0.64074,0.8963505390167237,0.6791
|
||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
1,2.031018338546753,0.25506,1.7647437294006347,0.3568
|
||||
2,1.7171751900482177,0.37778,1.510964904975891,0.4514
|
||||
3,1.5605473971176147,0.43146,1.4323553239822389,0.4787
|
||||
4,1.4770329965972901,0.45964,1.3029861038208008,0.5318
|
||||
5,1.4138119129180908,0.48766,1.25504387550354,0.5538
|
||||
6,1.3561226502227783,0.51288,1.1646997854232788,0.5827
|
||||
7,1.3055281218719483,0.52908,1.1090957656860352,0.6042
|
||||
8,1.256667589073181,0.55272,1.106753503894806,0.6148
|
||||
9,1.2256172871017457,0.56104,1.0723959255218505,0.6215
|
||||
10,1.1950459407806397,0.57334,1.0152456411361694,0.6431
|
||||
11,1.1654781759643555,0.58468,0.9916627891540527,0.6515
|
||||
12,1.1399137686538696,0.59356,1.0249745522499085,0.6378
|
||||
13,1.1239594958877563,0.60214,0.944364684677124,0.6656
|
||||
14,1.1052272381401063,0.60858,0.9644020311355591,0.6585
|
||||
15,1.0886156544876098,0.61204,0.92658356590271,0.6714
|
||||
16,1.0744145578384399,0.61968,0.9169919846534729,0.6851
|
||||
17,1.0608087825012207,0.62458,0.906572629737854,0.6838
|
||||
18,1.0402798016357422,0.62994,0.8794814926147461,0.6894
|
||||
19,1.039906374988556,0.62976,0.8636875254631042,0.6966
|
||||
20,1.0233247353744508,0.63816,0.8742800078392029,0.6896
|
||||
|
@@ -0,0 +1,436 @@
|
||||
python main.py
|
||||
/usr/local/lib/python3.10/dist-packages/torch/cuda/__init__.py:138: UserWarning: CUDA initialization: CUDA driver initialization failed, you might not have a CUDA gpu. (Triggered internally at ../c10/cuda/CUDAFunctions.cpp:108.)
|
||||
return torch._C._cuda_getDeviceCount() > 0
|
||||
Message sent successfully!
|
||||
Namespace(batch_size=128, lr=0.01, epochs=20, analyze=False)
|
||||
SEED 42
|
||||
Files already downloaded and verified
|
||||
Files already downloaded and verified
|
||||
[sgd][none][epoch 1] train_loss=2.0053, train_acc=0.2661, test_acc=0.3923
|
||||
[sgd][none][epoch 2] train_loss=1.5552, train_acc=0.4410, test_acc=0.4985
|
||||
[sgd][none][epoch 3] train_loss=1.3659, train_acc=0.5116, test_acc=0.5425
|
||||
[sgd][none][epoch 4] train_loss=1.2634, train_acc=0.5483, test_acc=0.5884
|
||||
[sgd][none][epoch 5] train_loss=1.1752, train_acc=0.5810, test_acc=0.5867
|
||||
[sgd][none][epoch 6] train_loss=1.0963, train_acc=0.6116, test_acc=0.6368
|
||||
[sgd][none][epoch 7] train_loss=1.0310, train_acc=0.6359, test_acc=0.6424
|
||||
[sgd][none][epoch 8] train_loss=0.9726, train_acc=0.6574, test_acc=0.6589
|
||||
[sgd][none][epoch 9] train_loss=0.9323, train_acc=0.6723, test_acc=0.6647
|
||||
[sgd][none][epoch 10] train_loss=0.8843, train_acc=0.6885, test_acc=0.6754
|
||||
[sgd][none][epoch 11] train_loss=0.8454, train_acc=0.7028, test_acc=0.6839
|
||||
[sgd][none][epoch 12] train_loss=0.8084, train_acc=0.7146, test_acc=0.6844
|
||||
[sgd][none][epoch 13] train_loss=0.7736, train_acc=0.7275, test_acc=0.6905
|
||||
[sgd][none][epoch 14] train_loss=0.7405, train_acc=0.7391, test_acc=0.6847
|
||||
[sgd][none][epoch 15] train_loss=0.7178, train_acc=0.7473, test_acc=0.7029
|
||||
[sgd][none][epoch 16] train_loss=0.6816, train_acc=0.7612, test_acc=0.6944
|
||||
[sgd][none][epoch 17] train_loss=0.6591, train_acc=0.7693, test_acc=0.6946
|
||||
[sgd][none][epoch 18] train_loss=0.6324, train_acc=0.7770, test_acc=0.7046
|
||||
[sgd][none][epoch 19] train_loss=0.6078, train_acc=0.7846, test_acc=0.7003
|
||||
[sgd][none][epoch 20] train_loss=0.5815, train_acc=0.7935, test_acc=0.7013
|
||||
Files already downloaded and verified
|
||||
Files already downloaded and verified
|
||||
[sgd][standard][epoch 1] train_loss=2.0359, train_acc=0.2552, test_acc=0.3902
|
||||
[sgd][standard][epoch 2] train_loss=1.7088, train_acc=0.3825, test_acc=0.4608
|
||||
[sgd][standard][epoch 3] train_loss=1.5394, train_acc=0.4392, test_acc=0.5077
|
||||
[sgd][standard][epoch 4] train_loss=1.4547, train_acc=0.4723, test_acc=0.5314
|
||||
[sgd][standard][epoch 5] train_loss=1.3847, train_acc=0.5011, test_acc=0.5736
|
||||
[sgd][standard][epoch 6] train_loss=1.3219, train_acc=0.5217, test_acc=0.5886
|
||||
[sgd][standard][epoch 7] train_loss=1.2655, train_acc=0.5445, test_acc=0.6200
|
||||
[sgd][standard][epoch 8] train_loss=1.2301, train_acc=0.5609, test_acc=0.6150
|
||||
[sgd][standard][epoch 9] train_loss=1.1942, train_acc=0.5754, test_acc=0.6317
|
||||
[sgd][standard][epoch 10] train_loss=1.1679, train_acc=0.5827, test_acc=0.6496
|
||||
[sgd][standard][epoch 11] train_loss=1.1530, train_acc=0.5874, test_acc=0.6523
|
||||
[sgd][standard][epoch 12] train_loss=1.1209, train_acc=0.5995, test_acc=0.6542
|
||||
[sgd][standard][epoch 13] train_loss=1.1006, train_acc=0.6071, test_acc=0.6636
|
||||
[sgd][standard][epoch 14] train_loss=1.0869, train_acc=0.6130, test_acc=0.6743
|
||||
[sgd][standard][epoch 15] train_loss=1.0667, train_acc=0.6217, test_acc=0.6889
|
||||
[sgd][standard][epoch 16] train_loss=1.0647, train_acc=0.6233, test_acc=0.6859
|
||||
[sgd][standard][epoch 17] train_loss=1.0438, train_acc=0.6297, test_acc=0.6906
|
||||
[sgd][standard][epoch 18] train_loss=1.0385, train_acc=0.6304, test_acc=0.6939
|
||||
[sgd][standard][epoch 19] train_loss=1.0160, train_acc=0.6405, test_acc=0.6895
|
||||
[sgd][standard][epoch 20] train_loss=1.0132, train_acc=0.6407, test_acc=0.6791
|
||||
Files already downloaded and verified
|
||||
Files already downloaded and verified
|
||||
[sgd][aggressive][epoch 1] train_loss=2.0499, train_acc=0.2434, test_acc=0.3315
|
||||
[sgd][aggressive][epoch 2] train_loss=1.7751, train_acc=0.3580, test_acc=0.4525
|
||||
[sgd][aggressive][epoch 3] train_loss=1.6295, train_acc=0.4092, test_acc=0.4708
|
||||
[sgd][aggressive][epoch 4] train_loss=1.5567, train_acc=0.4379, test_acc=0.5272
|
||||
[sgd][aggressive][epoch 5] train_loss=1.5069, train_acc=0.4563, test_acc=0.5268
|
||||
[sgd][aggressive][epoch 6] train_loss=1.4473, train_acc=0.4804, test_acc=0.5427
|
||||
[sgd][aggressive][epoch 7] train_loss=1.4167, train_acc=0.4912, test_acc=0.5828
|
||||
[sgd][aggressive][epoch 8] train_loss=1.3933, train_acc=0.5006, test_acc=0.5861
|
||||
[sgd][aggressive][epoch 9] train_loss=1.3540, train_acc=0.5145, test_acc=0.6093
|
||||
[sgd][aggressive][epoch 10] train_loss=1.3268, train_acc=0.5279, test_acc=0.6262
|
||||
[sgd][aggressive][epoch 11] train_loss=1.2946, train_acc=0.5374, test_acc=0.6210
|
||||
[sgd][aggressive][epoch 12] train_loss=1.2794, train_acc=0.5441, test_acc=0.6339
|
||||
[sgd][aggressive][epoch 13] train_loss=1.2606, train_acc=0.5517, test_acc=0.6379
|
||||
[sgd][aggressive][epoch 14] train_loss=1.2452, train_acc=0.5571, test_acc=0.6558
|
||||
[sgd][aggressive][epoch 15] train_loss=1.2263, train_acc=0.5650, test_acc=0.6631
|
||||
[sgd][aggressive][epoch 16] train_loss=1.2119, train_acc=0.5681, test_acc=0.6508
|
||||
[sgd][aggressive][epoch 17] train_loss=1.2090, train_acc=0.5702, test_acc=0.6643
|
||||
[sgd][aggressive][epoch 18] train_loss=1.1906, train_acc=0.5780, test_acc=0.6507
|
||||
[sgd][aggressive][epoch 19] train_loss=1.1747, train_acc=0.5831, test_acc=0.6728
|
||||
[sgd][aggressive][epoch 20] train_loss=1.1603, train_acc=0.5882, test_acc=0.6703
|
||||
Files already downloaded and verified
|
||||
Files already downloaded and verified
|
||||
[adam][none][epoch 1] train_loss=1.7651, train_acc=0.3486, test_acc=0.4452
|
||||
[adam][none][epoch 2] train_loss=1.4773, train_acc=0.4608, test_acc=0.4928
|
||||
[adam][none][epoch 3] train_loss=1.4246, train_acc=0.4883, test_acc=0.5095
|
||||
[adam][none][epoch 4] train_loss=1.3900, train_acc=0.4974, test_acc=0.5366
|
||||
[adam][none][epoch 5] train_loss=1.3695, train_acc=0.5090, test_acc=0.5367
|
||||
[adam][none][epoch 6] train_loss=1.3548, train_acc=0.5146, test_acc=0.5403
|
||||
[adam][none][epoch 7] train_loss=1.3448, train_acc=0.5149, test_acc=0.5363
|
||||
[adam][none][epoch 8] train_loss=1.3417, train_acc=0.5190, test_acc=0.5294
|
||||
[adam][none][epoch 9] train_loss=1.3385, train_acc=0.5203, test_acc=0.5552
|
||||
[adam][none][epoch 10] train_loss=1.3314, train_acc=0.5228, test_acc=0.5559
|
||||
[adam][none][epoch 11] train_loss=1.3147, train_acc=0.5289, test_acc=0.5765
|
||||
[adam][none][epoch 12] train_loss=1.3206, train_acc=0.5280, test_acc=0.5784
|
||||
[adam][none][epoch 13] train_loss=1.3099, train_acc=0.5291, test_acc=0.5604
|
||||
[adam][none][epoch 14] train_loss=1.3168, train_acc=0.5275, test_acc=0.5766
|
||||
[adam][none][epoch 15] train_loss=1.3134, train_acc=0.5308, test_acc=0.5413
|
||||
[adam][none][epoch 16] train_loss=1.3288, train_acc=0.5251, test_acc=0.5474
|
||||
[adam][none][epoch 17] train_loss=1.3214, train_acc=0.5305, test_acc=0.5339
|
||||
[adam][none][epoch 18] train_loss=1.3235, train_acc=0.5274, test_acc=0.5621
|
||||
[adam][none][epoch 19] train_loss=1.3163, train_acc=0.5307, test_acc=0.5786
|
||||
[adam][none][epoch 20] train_loss=1.3079, train_acc=0.5337, test_acc=0.5658
|
||||
Files already downloaded and verified
|
||||
Files already downloaded and verified
|
||||
[adam][standard][epoch 1] train_loss=2.0309, train_acc=0.2476, test_acc=0.3421
|
||||
[adam][standard][epoch 2] train_loss=1.7958, train_acc=0.3385, test_acc=0.3857
|
||||
[adam][standard][epoch 3] train_loss=1.7349, train_acc=0.3550, test_acc=0.4019
|
||||
[adam][standard][epoch 4] train_loss=1.7112, train_acc=0.3655, test_acc=0.4141
|
||||
[adam][standard][epoch 5] train_loss=1.6914, train_acc=0.3727, test_acc=0.4395
|
||||
[adam][standard][epoch 6] train_loss=1.6767, train_acc=0.3770, test_acc=0.3837
|
||||
[adam][standard][epoch 7] train_loss=1.6701, train_acc=0.3838, test_acc=0.4161
|
||||
[adam][standard][epoch 8] train_loss=1.6569, train_acc=0.3897, test_acc=0.4351
|
||||
[adam][standard][epoch 9] train_loss=1.6578, train_acc=0.3908, test_acc=0.4555
|
||||
[adam][standard][epoch 10] train_loss=1.6537, train_acc=0.3912, test_acc=0.4293
|
||||
[adam][standard][epoch 11] train_loss=1.6380, train_acc=0.4010, test_acc=0.4145
|
||||
[adam][standard][epoch 12] train_loss=1.6417, train_acc=0.3960, test_acc=0.3761
|
||||
[adam][standard][epoch 13] train_loss=1.6474, train_acc=0.3965, test_acc=0.4443
|
||||
[adam][standard][epoch 14] train_loss=1.6316, train_acc=0.4004, test_acc=0.4553
|
||||
[adam][standard][epoch 15] train_loss=1.6246, train_acc=0.4048, test_acc=0.4794
|
||||
[adam][standard][epoch 16] train_loss=1.6243, train_acc=0.4045, test_acc=0.4646
|
||||
[adam][standard][epoch 17] train_loss=1.6160, train_acc=0.4067, test_acc=0.4644
|
||||
[adam][standard][epoch 18] train_loss=1.6250, train_acc=0.4038, test_acc=0.4734
|
||||
[adam][standard][epoch 19] train_loss=1.6166, train_acc=0.4085, test_acc=0.3933
|
||||
[adam][standard][epoch 20] train_loss=1.6181, train_acc=0.4059, test_acc=0.4394
|
||||
Files already downloaded and verified
|
||||
Files already downloaded and verified
|
||||
[adam][aggressive][epoch 1] train_loss=1.9924, train_acc=0.2727, test_acc=0.3942
|
||||
[adam][aggressive][epoch 2] train_loss=1.7828, train_acc=0.3478, test_acc=0.4111
|
||||
[adam][aggressive][epoch 3] train_loss=1.7247, train_acc=0.3694, test_acc=0.4465
|
||||
[adam][aggressive][epoch 4] train_loss=1.6994, train_acc=0.3762, test_acc=0.4365
|
||||
[adam][aggressive][epoch 5] train_loss=1.6984, train_acc=0.3784, test_acc=0.4367
|
||||
[adam][aggressive][epoch 6] train_loss=1.6805, train_acc=0.3851, test_acc=0.4524
|
||||
[adam][aggressive][epoch 7] train_loss=1.6757, train_acc=0.3902, test_acc=0.4264
|
||||
[adam][aggressive][epoch 8] train_loss=1.6852, train_acc=0.3837, test_acc=0.4287
|
||||
[adam][aggressive][epoch 9] train_loss=1.6674, train_acc=0.3918, test_acc=0.4576
|
||||
[adam][aggressive][epoch 10] train_loss=1.6614, train_acc=0.3929, test_acc=0.4195
|
||||
[adam][aggressive][epoch 11] train_loss=1.6710, train_acc=0.3891, test_acc=0.4564
|
||||
[adam][aggressive][epoch 12] train_loss=1.6781, train_acc=0.3856, test_acc=0.3965
|
||||
[adam][aggressive][epoch 13] train_loss=1.6682, train_acc=0.3879, test_acc=0.3940
|
||||
[adam][aggressive][epoch 14] train_loss=1.6546, train_acc=0.3930, test_acc=0.4598
|
||||
[adam][aggressive][epoch 15] train_loss=1.6645, train_acc=0.3913, test_acc=0.4527
|
||||
[adam][aggressive][epoch 16] train_loss=1.6632, train_acc=0.3918, test_acc=0.4523
|
||||
[adam][aggressive][epoch 17] train_loss=1.6621, train_acc=0.3942, test_acc=0.4648
|
||||
[adam][aggressive][epoch 18] train_loss=1.6693, train_acc=0.3915, test_acc=0.4499
|
||||
[adam][aggressive][epoch 19] train_loss=1.6572, train_acc=0.3933, test_acc=0.4209
|
||||
[adam][aggressive][epoch 20] train_loss=1.6555, train_acc=0.3930, test_acc=0.4500
|
||||
SEED 123
|
||||
Files already downloaded and verified
|
||||
Files already downloaded and verified
|
||||
[sgd][none][epoch 1] train_loss=1.9336, train_acc=0.2973, test_acc=0.4190
|
||||
[sgd][none][epoch 2] train_loss=1.5059, train_acc=0.4574, test_acc=0.4962
|
||||
[sgd][none][epoch 3] train_loss=1.3496, train_acc=0.5174, test_acc=0.5525
|
||||
[sgd][none][epoch 4] train_loss=1.2513, train_acc=0.5546, test_acc=0.5781
|
||||
[sgd][none][epoch 5] train_loss=1.1647, train_acc=0.5883, test_acc=0.6106
|
||||
[sgd][none][epoch 6] train_loss=1.0901, train_acc=0.6127, test_acc=0.6397
|
||||
[sgd][none][epoch 7] train_loss=1.0262, train_acc=0.6359, test_acc=0.6398
|
||||
[sgd][none][epoch 8] train_loss=0.9832, train_acc=0.6515, test_acc=0.6642
|
||||
[sgd][none][epoch 9] train_loss=0.9299, train_acc=0.6718, test_acc=0.6715
|
||||
[sgd][none][epoch 10] train_loss=0.8931, train_acc=0.6846, test_acc=0.6734
|
||||
[sgd][none][epoch 11] train_loss=0.8506, train_acc=0.6991, test_acc=0.6856
|
||||
[sgd][none][epoch 12] train_loss=0.8163, train_acc=0.7120, test_acc=0.6771
|
||||
[sgd][none][epoch 13] train_loss=0.7825, train_acc=0.7232, test_acc=0.6900
|
||||
[sgd][none][epoch 14] train_loss=0.7470, train_acc=0.7376, test_acc=0.6945
|
||||
[sgd][none][epoch 15] train_loss=0.7195, train_acc=0.7479, test_acc=0.6951
|
||||
[sgd][none][epoch 16] train_loss=0.6972, train_acc=0.7545, test_acc=0.6973
|
||||
[sgd][none][epoch 17] train_loss=0.6697, train_acc=0.7627, test_acc=0.6851
|
||||
[sgd][none][epoch 18] train_loss=0.6414, train_acc=0.7776, test_acc=0.6949
|
||||
[sgd][none][epoch 19] train_loss=0.6034, train_acc=0.7887, test_acc=0.6954
|
||||
[sgd][none][epoch 20] train_loss=0.5873, train_acc=0.7941, test_acc=0.7002
|
||||
Files already downloaded and verified
|
||||
Files already downloaded and verified
|
||||
[sgd][standard][epoch 1] train_loss=2.0545, train_acc=0.2484, test_acc=0.3766
|
||||
[sgd][standard][epoch 2] train_loss=1.7023, train_acc=0.3811, test_acc=0.4511
|
||||
[sgd][standard][epoch 3] train_loss=1.5391, train_acc=0.4401, test_acc=0.5054
|
||||
[sgd][standard][epoch 4] train_loss=1.4802, train_acc=0.4615, test_acc=0.5222
|
||||
[sgd][standard][epoch 5] train_loss=1.4121, train_acc=0.4886, test_acc=0.5524
|
||||
[sgd][standard][epoch 6] train_loss=1.3602, train_acc=0.5106, test_acc=0.5765
|
||||
[sgd][standard][epoch 7] train_loss=1.3003, train_acc=0.5304, test_acc=0.5892
|
||||
[sgd][standard][epoch 8] train_loss=1.2587, train_acc=0.5499, test_acc=0.6125
|
||||
[sgd][standard][epoch 9] train_loss=1.2182, train_acc=0.5647, test_acc=0.6210
|
||||
[sgd][standard][epoch 10] train_loss=1.1902, train_acc=0.5738, test_acc=0.6269
|
||||
[sgd][standard][epoch 11] train_loss=1.1583, train_acc=0.5865, test_acc=0.6385
|
||||
[sgd][standard][epoch 12] train_loss=1.1428, train_acc=0.5913, test_acc=0.6493
|
||||
[sgd][standard][epoch 13] train_loss=1.1167, train_acc=0.6027, test_acc=0.6567
|
||||
[sgd][standard][epoch 14] train_loss=1.1067, train_acc=0.6082, test_acc=0.6520
|
||||
[sgd][standard][epoch 15] train_loss=1.0920, train_acc=0.6126, test_acc=0.6679
|
||||
[sgd][standard][epoch 16] train_loss=1.0732, train_acc=0.6178, test_acc=0.6692
|
||||
[sgd][standard][epoch 17] train_loss=1.0547, train_acc=0.6266, test_acc=0.6852
|
||||
[sgd][standard][epoch 18] train_loss=1.0448, train_acc=0.6293, test_acc=0.6878
|
||||
[sgd][standard][epoch 19] train_loss=1.0325, train_acc=0.6332, test_acc=0.7026
|
||||
[sgd][standard][epoch 20] train_loss=1.0181, train_acc=0.6410, test_acc=0.6951
|
||||
Files already downloaded and verified
|
||||
Files already downloaded and verified
|
||||
[sgd][aggressive][epoch 1] train_loss=2.0804, train_acc=0.2300, test_acc=0.3649
|
||||
[sgd][aggressive][epoch 2] train_loss=1.7951, train_acc=0.3517, test_acc=0.4536
|
||||
[sgd][aggressive][epoch 3] train_loss=1.6375, train_acc=0.4064, test_acc=0.4924
|
||||
[sgd][aggressive][epoch 4] train_loss=1.5572, train_acc=0.4352, test_acc=0.5132
|
||||
[sgd][aggressive][epoch 5] train_loss=1.5133, train_acc=0.4531, test_acc=0.5399
|
||||
[sgd][aggressive][epoch 6] train_loss=1.4705, train_acc=0.4701, test_acc=0.5457
|
||||
[sgd][aggressive][epoch 7] train_loss=1.4199, train_acc=0.4887, test_acc=0.5757
|
||||
[sgd][aggressive][epoch 8] train_loss=1.3825, train_acc=0.5033, test_acc=0.5862
|
||||
[sgd][aggressive][epoch 9] train_loss=1.3494, train_acc=0.5169, test_acc=0.6043
|
||||
[sgd][aggressive][epoch 10] train_loss=1.3266, train_acc=0.5264, test_acc=0.6032
|
||||
[sgd][aggressive][epoch 11] train_loss=1.2990, train_acc=0.5361, test_acc=0.6181
|
||||
[sgd][aggressive][epoch 12] train_loss=1.2720, train_acc=0.5476, test_acc=0.6288
|
||||
[sgd][aggressive][epoch 13] train_loss=1.2523, train_acc=0.5540, test_acc=0.6344
|
||||
[sgd][aggressive][epoch 14] train_loss=1.2364, train_acc=0.5605, test_acc=0.6526
|
||||
[sgd][aggressive][epoch 15] train_loss=1.2198, train_acc=0.5675, test_acc=0.6531
|
||||
[sgd][aggressive][epoch 16] train_loss=1.2122, train_acc=0.5668, test_acc=0.6472
|
||||
[sgd][aggressive][epoch 17] train_loss=1.1860, train_acc=0.5809, test_acc=0.6590
|
||||
[sgd][aggressive][epoch 18] train_loss=1.1860, train_acc=0.5799, test_acc=0.6720
|
||||
[sgd][aggressive][epoch 19] train_loss=1.1793, train_acc=0.5787, test_acc=0.6784
|
||||
[sgd][aggressive][epoch 20] train_loss=1.1562, train_acc=0.5907, test_acc=0.6766
|
||||
Files already downloaded and verified
|
||||
Files already downloaded and verified
|
||||
[adam][none][epoch 1] train_loss=1.8579, train_acc=0.3239, test_acc=0.4313
|
||||
[adam][none][epoch 2] train_loss=1.6378, train_acc=0.4044, test_acc=0.4396
|
||||
[adam][none][epoch 3] train_loss=1.5882, train_acc=0.4174, test_acc=0.4484
|
||||
[adam][none][epoch 4] train_loss=1.5531, train_acc=0.4360, test_acc=0.4586
|
||||
[adam][none][epoch 5] train_loss=1.5475, train_acc=0.4318, test_acc=0.4727
|
||||
[adam][none][epoch 6] train_loss=1.5150, train_acc=0.4496, test_acc=0.4750
|
||||
[adam][none][epoch 7] train_loss=1.5142, train_acc=0.4444, test_acc=0.4691
|
||||
[adam][none][epoch 8] train_loss=1.5065, train_acc=0.4478, test_acc=0.4814
|
||||
[adam][none][epoch 9] train_loss=1.4982, train_acc=0.4532, test_acc=0.4788
|
||||
[adam][none][epoch 10] train_loss=1.4954, train_acc=0.4547, test_acc=0.4955
|
||||
[adam][none][epoch 11] train_loss=1.4775, train_acc=0.4600, test_acc=0.5074
|
||||
[adam][none][epoch 12] train_loss=1.4788, train_acc=0.4620, test_acc=0.4806
|
||||
[adam][none][epoch 13] train_loss=1.4817, train_acc=0.4599, test_acc=0.4875
|
||||
[adam][none][epoch 14] train_loss=1.4779, train_acc=0.4611, test_acc=0.5107
|
||||
[adam][none][epoch 15] train_loss=1.4713, train_acc=0.4660, test_acc=0.4893
|
||||
[adam][none][epoch 16] train_loss=1.4835, train_acc=0.4611, test_acc=0.4853
|
||||
[adam][none][epoch 17] train_loss=1.4730, train_acc=0.4616, test_acc=0.4960
|
||||
[adam][none][epoch 18] train_loss=1.4708, train_acc=0.4648, test_acc=0.4778
|
||||
[adam][none][epoch 19] train_loss=1.4695, train_acc=0.4686, test_acc=0.5112
|
||||
[adam][none][epoch 20] train_loss=1.4658, train_acc=0.4660, test_acc=0.4857
|
||||
Files already downloaded and verified
|
||||
Files already downloaded and verified
|
||||
[adam][standard][epoch 1] train_loss=2.0278, train_acc=0.2494, test_acc=0.3251
|
||||
[adam][standard][epoch 2] train_loss=1.8144, train_acc=0.3310, test_acc=0.4045
|
||||
[adam][standard][epoch 3] train_loss=1.7265, train_acc=0.3622, test_acc=0.4111
|
||||
[adam][standard][epoch 4] train_loss=1.6720, train_acc=0.3814, test_acc=0.4100
|
||||
[adam][standard][epoch 5] train_loss=1.6580, train_acc=0.3885, test_acc=0.4350
|
||||
[adam][standard][epoch 6] train_loss=1.6298, train_acc=0.3997, test_acc=0.4597
|
||||
[adam][standard][epoch 7] train_loss=1.6190, train_acc=0.4032, test_acc=0.4422
|
||||
[adam][standard][epoch 8] train_loss=1.6199, train_acc=0.4080, test_acc=0.4565
|
||||
[adam][standard][epoch 9] train_loss=1.6146, train_acc=0.4075, test_acc=0.4629
|
||||
[adam][standard][epoch 10] train_loss=1.6216, train_acc=0.4045, test_acc=0.4081
|
||||
[adam][standard][epoch 11] train_loss=1.6055, train_acc=0.4083, test_acc=0.4358
|
||||
[adam][standard][epoch 12] train_loss=1.6176, train_acc=0.4069, test_acc=0.4722
|
||||
[adam][standard][epoch 13] train_loss=1.5999, train_acc=0.4124, test_acc=0.4715
|
||||
[adam][standard][epoch 14] train_loss=1.5934, train_acc=0.4140, test_acc=0.4626
|
||||
[adam][standard][epoch 15] train_loss=1.5934, train_acc=0.4137, test_acc=0.4468
|
||||
[adam][standard][epoch 16] train_loss=1.5965, train_acc=0.4130, test_acc=0.4670
|
||||
[adam][standard][epoch 17] train_loss=1.6136, train_acc=0.4071, test_acc=0.4527
|
||||
[adam][standard][epoch 18] train_loss=1.5965, train_acc=0.4156, test_acc=0.4593
|
||||
[adam][standard][epoch 19] train_loss=1.5915, train_acc=0.4165, test_acc=0.4642
|
||||
[adam][standard][epoch 20] train_loss=1.5891, train_acc=0.4160, test_acc=0.4536
|
||||
Files already downloaded and verified
|
||||
Files already downloaded and verified
|
||||
[adam][aggressive][epoch 1] train_loss=2.0048, train_acc=0.2625, test_acc=0.3807
|
||||
[adam][aggressive][epoch 2] train_loss=1.8032, train_acc=0.3402, test_acc=0.4277
|
||||
[adam][aggressive][epoch 3] train_loss=1.7539, train_acc=0.3595, test_acc=0.4400
|
||||
[adam][aggressive][epoch 4] train_loss=1.7228, train_acc=0.3677, test_acc=0.4412
|
||||
[adam][aggressive][epoch 5] train_loss=1.7074, train_acc=0.3770, test_acc=0.4460
|
||||
[adam][aggressive][epoch 6] train_loss=1.6873, train_acc=0.3853, test_acc=0.4534
|
||||
[adam][aggressive][epoch 7] train_loss=1.6828, train_acc=0.3875, test_acc=0.4678
|
||||
[adam][aggressive][epoch 8] train_loss=1.6679, train_acc=0.3955, test_acc=0.4569
|
||||
[adam][aggressive][epoch 9] train_loss=1.6778, train_acc=0.3893, test_acc=0.4535
|
||||
[adam][aggressive][epoch 10] train_loss=1.6620, train_acc=0.3933, test_acc=0.4733
|
||||
[adam][aggressive][epoch 11] train_loss=1.6635, train_acc=0.3955, test_acc=0.4761
|
||||
[adam][aggressive][epoch 12] train_loss=1.6477, train_acc=0.3989, test_acc=0.4825
|
||||
[adam][aggressive][epoch 13] train_loss=1.6429, train_acc=0.4028, test_acc=0.4554
|
||||
[adam][aggressive][epoch 14] train_loss=1.6476, train_acc=0.4008, test_acc=0.4971
|
||||
[adam][aggressive][epoch 15] train_loss=1.6472, train_acc=0.3994, test_acc=0.4897
|
||||
[adam][aggressive][epoch 16] train_loss=1.6327, train_acc=0.4031, test_acc=0.4766
|
||||
[adam][aggressive][epoch 17] train_loss=1.6346, train_acc=0.4026, test_acc=0.4602
|
||||
[adam][aggressive][epoch 18] train_loss=1.6377, train_acc=0.4003, test_acc=0.4795
|
||||
[adam][aggressive][epoch 19] train_loss=1.6307, train_acc=0.4048, test_acc=0.4869
|
||||
[adam][aggressive][epoch 20] train_loss=1.6381, train_acc=0.4030, test_acc=0.4542
|
||||
SEED 999
|
||||
Files already downloaded and verified
|
||||
Files already downloaded and verified
|
||||
[sgd][none][epoch 1] train_loss=1.9614, train_acc=0.2839, test_acc=0.4046
|
||||
[sgd][none][epoch 2] train_loss=1.5448, train_acc=0.4462, test_acc=0.4981
|
||||
[sgd][none][epoch 3] train_loss=1.3840, train_acc=0.5048, test_acc=0.5481
|
||||
[sgd][none][epoch 4] train_loss=1.2757, train_acc=0.5418, test_acc=0.5712
|
||||
[sgd][none][epoch 5] train_loss=1.1857, train_acc=0.5770, test_acc=0.5998
|
||||
[sgd][none][epoch 6] train_loss=1.1045, train_acc=0.6085, test_acc=0.6177
|
||||
[sgd][none][epoch 7] train_loss=1.0466, train_acc=0.6309, test_acc=0.6266
|
||||
[sgd][none][epoch 8] train_loss=0.9939, train_acc=0.6514, test_acc=0.6429
|
||||
[sgd][none][epoch 9] train_loss=0.9526, train_acc=0.6655, test_acc=0.6542
|
||||
[sgd][none][epoch 10] train_loss=0.9012, train_acc=0.6840, test_acc=0.6643
|
||||
[sgd][none][epoch 11] train_loss=0.8650, train_acc=0.6964, test_acc=0.6760
|
||||
[sgd][none][epoch 12] train_loss=0.8224, train_acc=0.7095, test_acc=0.6767
|
||||
[sgd][none][epoch 13] train_loss=0.7874, train_acc=0.7230, test_acc=0.6790
|
||||
[sgd][none][epoch 14] train_loss=0.7571, train_acc=0.7337, test_acc=0.6858
|
||||
[sgd][none][epoch 15] train_loss=0.7221, train_acc=0.7464, test_acc=0.6937
|
||||
[sgd][none][epoch 16] train_loss=0.6927, train_acc=0.7568, test_acc=0.6978
|
||||
[sgd][none][epoch 17] train_loss=0.6688, train_acc=0.7631, test_acc=0.7009
|
||||
[sgd][none][epoch 18] train_loss=0.6569, train_acc=0.7690, test_acc=0.6999
|
||||
[sgd][none][epoch 19] train_loss=0.6169, train_acc=0.7803, test_acc=0.6992
|
||||
[sgd][none][epoch 20] train_loss=0.5989, train_acc=0.7879, test_acc=0.6961
|
||||
Files already downloaded and verified
|
||||
Files already downloaded and verified
|
||||
[sgd][standard][epoch 1] train_loss=2.0310, train_acc=0.2551, test_acc=0.3568
|
||||
[sgd][standard][epoch 2] train_loss=1.7172, train_acc=0.3778, test_acc=0.4514
|
||||
[sgd][standard][epoch 3] train_loss=1.5605, train_acc=0.4315, test_acc=0.4787
|
||||
[sgd][standard][epoch 4] train_loss=1.4770, train_acc=0.4596, test_acc=0.5318
|
||||
[sgd][standard][epoch 5] train_loss=1.4138, train_acc=0.4877, test_acc=0.5538
|
||||
[sgd][standard][epoch 6] train_loss=1.3561, train_acc=0.5129, test_acc=0.5827
|
||||
[sgd][standard][epoch 7] train_loss=1.3055, train_acc=0.5291, test_acc=0.6042
|
||||
[sgd][standard][epoch 8] train_loss=1.2567, train_acc=0.5527, test_acc=0.6148
|
||||
[sgd][standard][epoch 9] train_loss=1.2256, train_acc=0.5610, test_acc=0.6215
|
||||
[sgd][standard][epoch 10] train_loss=1.1950, train_acc=0.5733, test_acc=0.6431
|
||||
[sgd][standard][epoch 11] train_loss=1.1655, train_acc=0.5847, test_acc=0.6515
|
||||
[sgd][standard][epoch 12] train_loss=1.1399, train_acc=0.5936, test_acc=0.6378
|
||||
[sgd][standard][epoch 13] train_loss=1.1240, train_acc=0.6021, test_acc=0.6656
|
||||
[sgd][standard][epoch 14] train_loss=1.1052, train_acc=0.6086, test_acc=0.6585
|
||||
[sgd][standard][epoch 15] train_loss=1.0886, train_acc=0.6120, test_acc=0.6714
|
||||
[sgd][standard][epoch 16] train_loss=1.0744, train_acc=0.6197, test_acc=0.6851
|
||||
[sgd][standard][epoch 17] train_loss=1.0608, train_acc=0.6246, test_acc=0.6838
|
||||
[sgd][standard][epoch 18] train_loss=1.0403, train_acc=0.6299, test_acc=0.6894
|
||||
[sgd][standard][epoch 19] train_loss=1.0399, train_acc=0.6298, test_acc=0.6966
|
||||
[sgd][standard][epoch 20] train_loss=1.0233, train_acc=0.6382, test_acc=0.6896
|
||||
Files already downloaded and verified
|
||||
Files already downloaded and verified
|
||||
[sgd][aggressive][epoch 1] train_loss=2.0627, train_acc=0.2416, test_acc=0.3478
|
||||
[sgd][aggressive][epoch 2] train_loss=1.7933, train_acc=0.3513, test_acc=0.4216
|
||||
[sgd][aggressive][epoch 3] train_loss=1.6581, train_acc=0.3992, test_acc=0.4786
|
||||
[sgd][aggressive][epoch 4] train_loss=1.5639, train_acc=0.4357, test_acc=0.5008
|
||||
[sgd][aggressive][epoch 5] train_loss=1.5055, train_acc=0.4540, test_acc=0.5423
|
||||
[sgd][aggressive][epoch 6] train_loss=1.4502, train_acc=0.4790, test_acc=0.5579
|
||||
[sgd][aggressive][epoch 7] train_loss=1.4208, train_acc=0.4934, test_acc=0.5692
|
||||
[sgd][aggressive][epoch 8] train_loss=1.3702, train_acc=0.5092, test_acc=0.5956
|
||||
[sgd][aggressive][epoch 9] train_loss=1.3449, train_acc=0.5183, test_acc=0.6007
|
||||
[sgd][aggressive][epoch 10] train_loss=1.3101, train_acc=0.5339, test_acc=0.6170
|
||||
[sgd][aggressive][epoch 11] train_loss=1.2958, train_acc=0.5399, test_acc=0.6201
|
||||
[sgd][aggressive][epoch 12] train_loss=1.2760, train_acc=0.5451, test_acc=0.6332
|
||||
[sgd][aggressive][epoch 13] train_loss=1.2568, train_acc=0.5538, test_acc=0.6380
|
||||
[sgd][aggressive][epoch 14] train_loss=1.2407, train_acc=0.5593, test_acc=0.6393
|
||||
[sgd][aggressive][epoch 15] train_loss=1.2321, train_acc=0.5595, test_acc=0.6450
|
||||
[sgd][aggressive][epoch 16] train_loss=1.2164, train_acc=0.5673, test_acc=0.6538
|
||||
[sgd][aggressive][epoch 17] train_loss=1.2027, train_acc=0.5725, test_acc=0.6540
|
||||
[sgd][aggressive][epoch 18] train_loss=1.1870, train_acc=0.5768, test_acc=0.6696
|
||||
[sgd][aggressive][epoch 19] train_loss=1.1842, train_acc=0.5796, test_acc=0.6555
|
||||
[sgd][aggressive][epoch 20] train_loss=1.1647, train_acc=0.5845, test_acc=0.6630
|
||||
Files already downloaded and verified
|
||||
Files already downloaded and verified
|
||||
[adam][none][epoch 1] train_loss=1.8653, train_acc=0.3280, test_acc=0.3995
|
||||
[adam][none][epoch 2] train_loss=1.6121, train_acc=0.4129, test_acc=0.4098
|
||||
[adam][none][epoch 3] train_loss=1.5402, train_acc=0.4404, test_acc=0.4697
|
||||
[adam][none][epoch 4] train_loss=1.5276, train_acc=0.4490, test_acc=0.4802
|
||||
[adam][none][epoch 5] train_loss=1.4979, train_acc=0.4543, test_acc=0.4818
|
||||
[adam][none][epoch 6] train_loss=1.4916, train_acc=0.4601, test_acc=0.4988
|
||||
[adam][none][epoch 7] train_loss=1.4729, train_acc=0.4647, test_acc=0.4972
|
||||
[adam][none][epoch 8] train_loss=1.4770, train_acc=0.4638, test_acc=0.4687
|
||||
[adam][none][epoch 9] train_loss=1.4653, train_acc=0.4690, test_acc=0.4816
|
||||
[adam][none][epoch 10] train_loss=1.4635, train_acc=0.4718, test_acc=0.4935
|
||||
[adam][none][epoch 11] train_loss=1.4643, train_acc=0.4703, test_acc=0.4782
|
||||
[adam][none][epoch 12] train_loss=1.4603, train_acc=0.4717, test_acc=0.4873
|
||||
[adam][none][epoch 13] train_loss=1.4479, train_acc=0.4763, test_acc=0.4706
|
||||
[adam][none][epoch 14] train_loss=1.4543, train_acc=0.4767, test_acc=0.5077
|
||||
[adam][none][epoch 15] train_loss=1.4511, train_acc=0.4727, test_acc=0.5074
|
||||
[adam][none][epoch 16] train_loss=1.4691, train_acc=0.4710, test_acc=0.5053
|
||||
[adam][none][epoch 17] train_loss=1.4495, train_acc=0.4772, test_acc=0.5045
|
||||
[adam][none][epoch 18] train_loss=1.4601, train_acc=0.4717, test_acc=0.5149
|
||||
[adam][none][epoch 19] train_loss=1.4620, train_acc=0.4741, test_acc=0.5031
|
||||
[adam][none][epoch 20] train_loss=1.4535, train_acc=0.4741, test_acc=0.5189
|
||||
Files already downloaded and verified
|
||||
Files already downloaded and verified
|
||||
[adam][standard][epoch 1] train_loss=1.9290, train_acc=0.2975, test_acc=0.4071
|
||||
[adam][standard][epoch 2] train_loss=1.7239, train_acc=0.3633, test_acc=0.3631
|
||||
[adam][standard][epoch 3] train_loss=1.6749, train_acc=0.3821, test_acc=0.4274
|
||||
[adam][standard][epoch 4] train_loss=1.6455, train_acc=0.3956, test_acc=0.4514
|
||||
[adam][standard][epoch 5] train_loss=1.6245, train_acc=0.4029, test_acc=0.4313
|
||||
[adam][standard][epoch 6] train_loss=1.6053, train_acc=0.4100, test_acc=0.4484
|
||||
[adam][standard][epoch 7] train_loss=1.6106, train_acc=0.4080, test_acc=0.4302
|
||||
[adam][standard][epoch 8] train_loss=1.5953, train_acc=0.4148, test_acc=0.4639
|
||||
[adam][standard][epoch 9] train_loss=1.5825, train_acc=0.4168, test_acc=0.4662
|
||||
[adam][standard][epoch 10] train_loss=1.5836, train_acc=0.4205, test_acc=0.4595
|
||||
[adam][standard][epoch 11] train_loss=1.5734, train_acc=0.4241, test_acc=0.4862
|
||||
[adam][standard][epoch 12] train_loss=1.5816, train_acc=0.4209, test_acc=0.4603
|
||||
[adam][standard][epoch 13] train_loss=1.5812, train_acc=0.4215, test_acc=0.4889
|
||||
[adam][standard][epoch 14] train_loss=1.5848, train_acc=0.4202, test_acc=0.4823
|
||||
[adam][standard][epoch 15] train_loss=1.5768, train_acc=0.4227, test_acc=0.4809
|
||||
[adam][standard][epoch 16] train_loss=1.5763, train_acc=0.4241, test_acc=0.4911
|
||||
[adam][standard][epoch 17] train_loss=1.5560, train_acc=0.4306, test_acc=0.4727
|
||||
[adam][standard][epoch 18] train_loss=1.5524, train_acc=0.4348, test_acc=0.4581
|
||||
[adam][standard][epoch 19] train_loss=1.5581, train_acc=0.4291, test_acc=0.4822
|
||||
[adam][standard][epoch 20] train_loss=1.5584, train_acc=0.4282, test_acc=0.4934
|
||||
Files already downloaded and verified
|
||||
Files already downloaded and verified
|
||||
[adam][aggressive][epoch 1] train_loss=2.0259, train_acc=0.2653, test_acc=0.3501
|
||||
[adam][aggressive][epoch 2] train_loss=1.8678, train_acc=0.3130, test_acc=0.3679
|
||||
[adam][aggressive][epoch 3] train_loss=1.8263, train_acc=0.3308, test_acc=0.3729
|
||||
[adam][aggressive][epoch 4] train_loss=1.8109, train_acc=0.3348, test_acc=0.3847
|
||||
[adam][aggressive][epoch 5] train_loss=1.7937, train_acc=0.3411, test_acc=0.3855
|
||||
[adam][aggressive][epoch 6] train_loss=1.7862, train_acc=0.3438, test_acc=0.3771
|
||||
[adam][aggressive][epoch 7] train_loss=1.7757, train_acc=0.3419, test_acc=0.3899
|
||||
[adam][aggressive][epoch 8] train_loss=1.7809, train_acc=0.3414, test_acc=0.3915
|
||||
[adam][aggressive][epoch 9] train_loss=1.7794, train_acc=0.3387, test_acc=0.3913
|
||||
[adam][aggressive][epoch 10] train_loss=1.7733, train_acc=0.3430, test_acc=0.3706
|
||||
[adam][aggressive][epoch 11] train_loss=1.7688, train_acc=0.3444, test_acc=0.3919
|
||||
[adam][aggressive][epoch 12] train_loss=1.7673, train_acc=0.3452, test_acc=0.4055
|
||||
[adam][aggressive][epoch 13] train_loss=1.7586, train_acc=0.3477, test_acc=0.4183
|
||||
[adam][aggressive][epoch 14] train_loss=1.7682, train_acc=0.3431, test_acc=0.3904
|
||||
[adam][aggressive][epoch 15] train_loss=1.7510, train_acc=0.3507, test_acc=0.3796
|
||||
[adam][aggressive][epoch 16] train_loss=1.7584, train_acc=0.3480, test_acc=0.3948
|
||||
[adam][aggressive][epoch 17] train_loss=1.7581, train_acc=0.3510, test_acc=0.4044
|
||||
[adam][aggressive][epoch 18] train_loss=1.7501, train_acc=0.3506, test_acc=0.4180
|
||||
[adam][aggressive][epoch 19] train_loss=1.7574, train_acc=0.3461, test_acc=0.4032
|
||||
[adam][aggressive][epoch 20] train_loss=1.7578, train_acc=0.3469, test_acc=0.4039
|
||||
saved results to results.json
|
||||
anova on test accuracy:
|
||||
sum_sq df F PR(>F)
|
||||
C(optimizer) 0.201909 1.0 366.885184 2.308516e-10
|
||||
C(augmentation) 0.010412 2.0 9.459614 3.417556e-03
|
||||
C(optimizer):C(augmentation) 0.002980 2.0 2.707481 1.070415e-01
|
||||
Residual 0.006604 12.0 NaN NaN
|
||||
saved plot to test_acc_comparison.png
|
||||
Message sent successfully!
|
||||
python main.py --analyze
|
||||
/usr/local/lib/python3.10/dist-packages/torch/cuda/__init__.py:138: UserWarning: CUDA initialization: CUDA driver initialization failed, you might not have a CUDA gpu. (Triggered internally at ../c10/cuda/CUDAFunctions.cpp:108.)
|
||||
return torch._C._cuda_getDeviceCount() > 0
|
||||
Message sent successfully!
|
||||
Namespace(batch_size=128, lr=0.01, epochs=20, analyze=True)
|
||||
SEED 42
|
||||
Files already downloaded and verified
|
||||
Files already downloaded and verified
|
||||
[sgd][none][epoch 1] train_loss=2.0053, train_acc=0.2661, test_acc=0.3923
|
||||
[sgd][none][epoch 2] train_loss=1.5552, train_acc=0.4410, test_acc=0.4985
|
||||
[sgd][none][epoch 3] train_loss=1.3659, train_acc=0.5116, test_acc=0.5425
|
||||
[sgd][none][epoch 4] train_loss=1.2634, train_acc=0.5483, test_acc=0.5884
|
||||
[sgd][none][epoch 5] train_loss=1.1752, train_acc=0.5810, test_acc=0.5867
|
||||
[sgd][none][epoch 6] train_loss=1.0963, train_acc=0.6116, test_acc=0.6368
|
||||
[sgd][none][epoch 7] train_loss=1.0310, train_acc=0.6359, test_acc=0.6424
|
||||
[sgd][none][epoch 8] train_loss=0.9726, train_acc=0.6574, test_acc=0.6589
|
||||
[sgd][none][epoch 9] train_loss=0.9323, train_acc=0.6723, test_acc=0.6647
|
||||
[sgd][none][epoch 10] train_loss=0.8843, train_acc=0.6885, test_acc=0.6754
|
||||
[sgd][none][epoch 11] train_loss=0.8454, train_acc=0.7028, test_acc=0.6839
|
||||
[sgd][none][epoch 12] train_loss=0.8084, train_acc=0.7146, test_acc=0.6844
|
||||
[sgd][none][epoch 13] train_loss=0.7736, train_acc=0.7275, test_acc=0.6905
|
||||
[sgd][none][epoch 14] train_loss=0.7405, train_acc=0.7391, test_acc=0.6847
|
||||
[sgd][none][epoch 15] train_loss=0.7178, train_acc=0.7473, test_acc=0.7029
|
||||
@@ -0,0 +1,200 @@
|
||||
[
|
||||
{
|
||||
"seed": 42,
|
||||
"optimizer": "sgd",
|
||||
"augmentation": "none",
|
||||
"test_acc": 0.7013,
|
||||
"robustness": {
|
||||
"0.1": 0.6895,
|
||||
"0.2": 0.6449,
|
||||
"0.3": 0.5712
|
||||
}
|
||||
},
|
||||
{
|
||||
"seed": 42,
|
||||
"optimizer": "sgd",
|
||||
"augmentation": "standard",
|
||||
"test_acc": 0.6791,
|
||||
"robustness": {
|
||||
"0.1": 0.6702,
|
||||
"0.2": 0.6315,
|
||||
"0.3": 0.5601
|
||||
}
|
||||
},
|
||||
{
|
||||
"seed": 42,
|
||||
"optimizer": "sgd",
|
||||
"augmentation": "aggressive",
|
||||
"test_acc": 0.6703,
|
||||
"robustness": {
|
||||
"0.1": 0.6505,
|
||||
"0.2": 0.587,
|
||||
"0.3": 0.5143
|
||||
}
|
||||
},
|
||||
{
|
||||
"seed": 42,
|
||||
"optimizer": "adam",
|
||||
"augmentation": "none",
|
||||
"test_acc": 0.5658,
|
||||
"robustness": {
|
||||
"0.1": 0.5575,
|
||||
"0.2": 0.5204,
|
||||
"0.3": 0.4498
|
||||
}
|
||||
},
|
||||
{
|
||||
"seed": 42,
|
||||
"optimizer": "adam",
|
||||
"augmentation": "standard",
|
||||
"test_acc": 0.4394,
|
||||
"robustness": {
|
||||
"0.1": 0.4385,
|
||||
"0.2": 0.4069,
|
||||
"0.3": 0.3476
|
||||
}
|
||||
},
|
||||
{
|
||||
"seed": 42,
|
||||
"optimizer": "adam",
|
||||
"augmentation": "aggressive",
|
||||
"test_acc": 0.45,
|
||||
"robustness": {
|
||||
"0.1": 0.4467,
|
||||
"0.2": 0.4168,
|
||||
"0.3": 0.3557
|
||||
}
|
||||
},
|
||||
{
|
||||
"seed": 123,
|
||||
"optimizer": "sgd",
|
||||
"augmentation": "none",
|
||||
"test_acc": 0.7002,
|
||||
"robustness": {
|
||||
"0.1": 0.6902,
|
||||
"0.2": 0.6511,
|
||||
"0.3": 0.5781
|
||||
}
|
||||
},
|
||||
{
|
||||
"seed": 123,
|
||||
"optimizer": "sgd",
|
||||
"augmentation": "standard",
|
||||
"test_acc": 0.6951,
|
||||
"robustness": {
|
||||
"0.1": 0.6833,
|
||||
"0.2": 0.6248,
|
||||
"0.3": 0.5406
|
||||
}
|
||||
},
|
||||
{
|
||||
"seed": 123,
|
||||
"optimizer": "sgd",
|
||||
"augmentation": "aggressive",
|
||||
"test_acc": 0.6766,
|
||||
"robustness": {
|
||||
"0.1": 0.6661,
|
||||
"0.2": 0.6188,
|
||||
"0.3": 0.5369
|
||||
}
|
||||
},
|
||||
{
|
||||
"seed": 123,
|
||||
"optimizer": "adam",
|
||||
"augmentation": "none",
|
||||
"test_acc": 0.4857,
|
||||
"robustness": {
|
||||
"0.1": 0.4851,
|
||||
"0.2": 0.4572,
|
||||
"0.3": 0.4191
|
||||
}
|
||||
},
|
||||
{
|
||||
"seed": 123,
|
||||
"optimizer": "adam",
|
||||
"augmentation": "standard",
|
||||
"test_acc": 0.4536,
|
||||
"robustness": {
|
||||
"0.1": 0.4517,
|
||||
"0.2": 0.4216,
|
||||
"0.3": 0.3551
|
||||
}
|
||||
},
|
||||
{
|
||||
"seed": 123,
|
||||
"optimizer": "adam",
|
||||
"augmentation": "aggressive",
|
||||
"test_acc": 0.4542,
|
||||
"robustness": {
|
||||
"0.1": 0.4568,
|
||||
"0.2": 0.4363,
|
||||
"0.3": 0.3909
|
||||
}
|
||||
},
|
||||
{
|
||||
"seed": 999,
|
||||
"optimizer": "sgd",
|
||||
"augmentation": "none",
|
||||
"test_acc": 0.6961,
|
||||
"robustness": {
|
||||
"0.1": 0.6845,
|
||||
"0.2": 0.6509,
|
||||
"0.3": 0.5702
|
||||
}
|
||||
},
|
||||
{
|
||||
"seed": 999,
|
||||
"optimizer": "sgd",
|
||||
"augmentation": "standard",
|
||||
"test_acc": 0.6896,
|
||||
"robustness": {
|
||||
"0.1": 0.6757,
|
||||
"0.2": 0.6251,
|
||||
"0.3": 0.5515
|
||||
}
|
||||
},
|
||||
{
|
||||
"seed": 999,
|
||||
"optimizer": "sgd",
|
||||
"augmentation": "aggressive",
|
||||
"test_acc": 0.663,
|
||||
"robustness": {
|
||||
"0.1": 0.6542,
|
||||
"0.2": 0.6143,
|
||||
"0.3": 0.5326
|
||||
}
|
||||
},
|
||||
{
|
||||
"seed": 999,
|
||||
"optimizer": "adam",
|
||||
"augmentation": "none",
|
||||
"test_acc": 0.5189,
|
||||
"robustness": {
|
||||
"0.1": 0.5138,
|
||||
"0.2": 0.4787,
|
||||
"0.3": 0.4115
|
||||
}
|
||||
},
|
||||
{
|
||||
"seed": 999,
|
||||
"optimizer": "adam",
|
||||
"augmentation": "standard",
|
||||
"test_acc": 0.4934,
|
||||
"robustness": {
|
||||
"0.1": 0.4822,
|
||||
"0.2": 0.4312,
|
||||
"0.3": 0.34
|
||||
}
|
||||
},
|
||||
{
|
||||
"seed": 999,
|
||||
"optimizer": "adam",
|
||||
"augmentation": "aggressive",
|
||||
"test_acc": 0.4039,
|
||||
"robustness": {
|
||||
"0.1": 0.4053,
|
||||
"0.2": 0.3814,
|
||||
"0.3": 0.3183
|
||||
}
|
||||
}
|
||||
]
|
||||
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|
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|
After Width: | Height: | Size: 29 KiB |
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|
After Width: | Height: | Size: 28 KiB |
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|
After Width: | Height: | Size: 32 KiB |
@@ -0,0 +1,19 @@
|
||||
seed,optimizer,augmentation,test_acc,robustness
|
||||
42,sgd,none,0.7017,"{'0.1': 0.6874, '0.2': 0.6539, '0.3': 0.573}"
|
||||
42,sgd,standard,0.6983,"{'0.1': 0.685, '0.2': 0.6393, '0.3': 0.5324}"
|
||||
42,sgd,aggressive,0.6529,"{'0.1': 0.6441, '0.2': 0.5905, '0.3': 0.5073}"
|
||||
42,adam,none,0.5754,"{'0.1': 0.5688, '0.2': 0.5225, '0.3': 0.461}"
|
||||
42,adam,standard,0.5012,"{'0.1': 0.5008, '0.2': 0.4696, '0.3': 0.3933}"
|
||||
42,adam,aggressive,0.4534,"{'0.1': 0.443, '0.2': 0.4074, '0.3': 0.3669}"
|
||||
123,sgd,none,0.7018,"{'0.1': 0.6907, '0.2': 0.6513, '0.3': 0.5808}"
|
||||
123,sgd,standard,0.6987,"{'0.1': 0.688, '0.2': 0.6378, '0.3': 0.5488}"
|
||||
123,sgd,aggressive,0.6736,"{'0.1': 0.6591, '0.2': 0.6077, '0.3': 0.5265}"
|
||||
123,adam,none,0.5414,"{'0.1': 0.5207, '0.2': 0.4721, '0.3': 0.3951}"
|
||||
123,adam,standard,0.4439,"{'0.1': 0.4509, '0.2': 0.4256, '0.3': 0.3567}"
|
||||
123,adam,aggressive,0.4519,"{'0.1': 0.4502, '0.2': 0.4266, '0.3': 0.3584}"
|
||||
999,sgd,none,0.6778,"{'0.1': 0.669, '0.2': 0.6288, '0.3': 0.5506}"
|
||||
999,sgd,standard,0.6961,"{'0.1': 0.6862, '0.2': 0.6491, '0.3': 0.5655}"
|
||||
999,sgd,aggressive,0.6623,"{'0.1': 0.6504, '0.2': 0.5934, '0.3': 0.5163}"
|
||||
999,adam,none,0.5477,"{'0.1': 0.5394, '0.2': 0.4983, '0.3': 0.4188}"
|
||||
999,adam,standard,0.4508,"{'0.1': 0.4455, '0.2': 0.3987, '0.3': 0.308}"
|
||||
999,adam,aggressive,0.4209,"{'0.1': 0.4268, '0.2': 0.4071, '0.3': 0.3368}"
|
||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
1,2.021981541175842,0.25682,1.7806077911376954,0.3374
|
||||
2,1.7999388361358644,0.33548,1.61310339717865,0.4133
|
||||
3,1.7349447472763062,0.3581,1.5748741884231567,0.4205
|
||||
4,1.7071615340805053,0.36902,1.585918094444275,0.426
|
||||
5,1.6942062984466553,0.37512,1.5335152185440064,0.4365
|
||||
6,1.682510565185547,0.38064,1.5587552444458008,0.4198
|
||||
7,1.6737361584091186,0.38374,1.463624397468567,0.4576
|
||||
8,1.6662311582946778,0.3874,1.542683459854126,0.4461
|
||||
9,1.6689811365509033,0.38424,1.4910095794677733,0.4494
|
||||
10,1.6586080972290038,0.39098,1.4566748039245605,0.4718
|
||||
11,1.6606470708847045,0.39202,1.45227852268219,0.4709
|
||||
12,1.6646523748016357,0.39152,1.4916118307113648,0.4603
|
||||
13,1.6484171169281006,0.39868,1.5345939838409424,0.4381
|
||||
14,1.6551834521865845,0.39018,1.440371674346924,0.4754
|
||||
15,1.653093519821167,0.39436,1.465016110420227,0.4632
|
||||
16,1.6464548859024049,0.39566,1.4275858160018922,0.4774
|
||||
17,1.6686206332397462,0.39034,1.4911364223480224,0.4495
|
||||
18,1.6486382946395874,0.39726,1.489304538154602,0.4583
|
||||
19,1.6871330679321288,0.38462,1.4915159872055053,0.4529
|
||||
20,1.6607746768188476,0.39282,1.491070439338684,0.4519
|
||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
1,1.9946132025909424,0.26546,1.7465605016708374,0.342
|
||||
2,1.7975156771087646,0.33534,1.6129542232513427,0.4064
|
||||
3,1.7742824270248414,0.34438,1.5872959531784057,0.42
|
||||
4,1.737174402770996,0.35786,1.6175920555114747,0.4113
|
||||
5,1.726973815536499,0.36836,1.5620707996368408,0.4221
|
||||
6,1.7160892931365967,0.3704,1.536605580329895,0.4449
|
||||
7,1.696208762741089,0.37986,1.5236610635757446,0.4352
|
||||
8,1.6957400606536865,0.38076,1.5052044256210326,0.4409
|
||||
9,1.6930768957138063,0.38038,1.5134387523651123,0.4434
|
||||
10,1.6858074627304078,0.37872,1.4595767322540283,0.4671
|
||||
11,1.6876252536773682,0.38142,1.473248080444336,0.456
|
||||
12,1.6892691661834718,0.38366,1.554956097793579,0.4288
|
||||
13,1.6795142168426513,0.3832,1.5135724742889405,0.4422
|
||||
14,1.6710495895767212,0.38514,1.632836058998108,0.4082
|
||||
15,1.6752502041625976,0.3846,1.459756902885437,0.4628
|
||||
16,1.6733012282562256,0.38312,1.5108640363693238,0.437
|
||||
17,1.6646488619613649,0.38898,1.4822496488571166,0.4529
|
||||
18,1.6782792532348634,0.38288,1.4726739952087402,0.4649
|
||||
19,1.6774794401168822,0.38574,1.5311094917297363,0.4383
|
||||
20,1.671811372718811,0.38212,1.5132373497009277,0.4534
|
||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
1,2.0723634432601927,0.23022,1.876600818824768,0.3199
|
||||
2,1.9161218788909913,0.29064,1.731086205482483,0.3617
|
||||
3,1.8448259813690187,0.3195,1.6460390392303468,0.3999
|
||||
4,1.8053451504135132,0.33482,1.5930611736297609,0.4099
|
||||
5,1.7892016728973388,0.34036,1.601932553291321,0.4121
|
||||
6,1.7877225128936767,0.33872,1.9846259342193604,0.3256
|
||||
7,1.7722377728652954,0.34716,1.5737567417144775,0.4181
|
||||
8,1.7613219201278687,0.34792,1.6388108669281005,0.3857
|
||||
9,1.7486019417953491,0.35528,1.6210294721603393,0.3986
|
||||
10,1.7620320590209961,0.34984,1.6138639379501343,0.3982
|
||||
11,1.7493324411010742,0.35366,1.592185188484192,0.4078
|
||||
12,1.745043455810547,0.35408,1.6113332284927369,0.4106
|
||||
13,1.7523625258636475,0.3513,1.5707368755340576,0.4204
|
||||
14,1.7393008434677124,0.3585,1.5894966974258422,0.4125
|
||||
15,1.7469453559112549,0.35858,1.6415567993164062,0.3921
|
||||
16,1.7383291018295288,0.35804,1.6457257890701293,0.3887
|
||||
17,1.7539940619659424,0.35182,1.649910280227661,0.3902
|
||||
18,1.7417138710403441,0.35358,1.6048244901657105,0.4027
|
||||
19,1.7405921878814696,0.3585,1.540078621673584,0.4284
|
||||
20,1.7527848522567748,0.3491,1.5630715839385987,0.4209
|
||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
1,1.7930121985626222,0.34364,1.461875290298462,0.4587
|
||||
2,1.5388130508041382,0.43978,1.442550922393799,0.4631
|
||||
3,1.4962808783721924,0.45782,1.4238734016418457,0.4876
|
||||
4,1.4607513367462157,0.4701,1.347493274497986,0.5141
|
||||
5,1.4432476579666138,0.47944,1.3734356439590454,0.5123
|
||||
6,1.421063133468628,0.48706,1.3214570888519288,0.529
|
||||
7,1.4215787218475342,0.48914,1.3083847173690797,0.5334
|
||||
8,1.4135805054092407,0.48904,1.3078678575515748,0.5363
|
||||
9,1.4087683379745484,0.49214,1.3223941360473632,0.5187
|
||||
10,1.4120303262710572,0.49486,1.2843070182800294,0.5335
|
||||
11,1.3871485186767578,0.50006,1.2921210390090943,0.5329
|
||||
12,1.3999624375915527,0.49512,1.2802863786697387,0.5462
|
||||
13,1.3897427955627442,0.50096,1.2707655395507813,0.5448
|
||||
14,1.3929189464950562,0.49866,1.280012000465393,0.5352
|
||||
15,1.3815861407852172,0.50394,1.303921529006958,0.538
|
||||
16,1.3858564881134032,0.50334,1.271148939704895,0.5447
|
||||
17,1.3741848274230957,0.50992,1.2622444095611571,0.5518
|
||||
18,1.3721859537506103,0.50712,1.250786780166626,0.5568
|
||||
19,1.3785438285064697,0.50654,1.2690851692199707,0.5513
|
||||
20,1.3659724238586426,0.51068,1.3006612928390502,0.5414
|
||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
1,1.7538864451980591,0.3666,1.5667252685546875,0.4474
|
||||
2,1.5012665232467652,0.4559,1.4435671327590942,0.4801
|
||||
3,1.4560056861877442,0.47398,1.3615544191360474,0.511
|
||||
4,1.4221073620223998,0.48824,1.344312677192688,0.5162
|
||||
5,1.3943471972274781,0.49968,1.3266402479171753,0.5221
|
||||
6,1.3839806178665162,0.50374,1.3004958406448364,0.5295
|
||||
7,1.3604061797332763,0.51462,1.3282047555923462,0.5269
|
||||
8,1.3528923289108277,0.51308,1.2727963297843934,0.5478
|
||||
9,1.3496200884246825,0.51504,1.2338088079452514,0.5602
|
||||
10,1.3384253984069825,0.51992,1.2602990411758423,0.5414
|
||||
11,1.3298793702697753,0.52298,1.2460808729171753,0.5535
|
||||
12,1.3380408303070068,0.52314,1.201425923538208,0.5783
|
||||
13,1.3282683892822265,0.52384,1.2300636964797973,0.5622
|
||||
14,1.3240932238769532,0.5305,1.2329102926254272,0.5585
|
||||
15,1.3172099641799926,0.53152,1.2063555044174195,0.5775
|
||||
16,1.3192347250366212,0.53014,1.2183320951461791,0.5694
|
||||
17,1.3198897607040405,0.5286,1.2268210130691528,0.5755
|
||||
18,1.3245510208892821,0.52778,1.248089506149292,0.5589
|
||||
19,1.3320170434570313,0.5294,1.2209409841537475,0.5715
|
||||
20,1.3129964478302,0.53108,1.1870027980804443,0.5754
|
||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
1,1.7632377227020264,0.35308,1.5758346817016602,0.4299
|
||||
2,1.524346548271179,0.4486,1.4102591985702515,0.4979
|
||||
3,1.456631953201294,0.47108,1.3265910715103149,0.5188
|
||||
4,1.4304079055023193,0.48082,1.377274009513855,0.5
|
||||
5,1.4108501930999755,0.49066,1.4178906629562378,0.5087
|
||||
6,1.4031479808807372,0.4983,1.309526050758362,0.5271
|
||||
7,1.383127350769043,0.50128,1.3740155362129212,0.5123
|
||||
8,1.3820967692565918,0.50244,1.2505300882339478,0.5529
|
||||
9,1.3669423685073852,0.51028,1.311721753692627,0.5251
|
||||
10,1.3696778673553467,0.5087,1.3234023988723755,0.5277
|
||||
11,1.3733588944244384,0.50774,1.2789020259857178,0.5407
|
||||
12,1.3640874988174438,0.5121,1.31283944940567,0.531
|
||||
13,1.3571320106887816,0.51374,1.265874310874939,0.5501
|
||||
14,1.3592108781051635,0.51512,1.346185697746277,0.5302
|
||||
15,1.3577870546340942,0.51416,1.2771299747467042,0.5569
|
||||
16,1.3403621031570434,0.51896,1.2562333318710328,0.55
|
||||
17,1.3543927292633056,0.51506,1.2568754550933838,0.5515
|
||||
18,1.3482802200698853,0.51838,1.282126469898224,0.5486
|
||||
19,1.3436878190994264,0.51798,1.251200986480713,0.548
|
||||
20,1.3356118139648439,0.52016,1.2636010625839234,0.5477
|
||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
1,1.9765228209686279,0.275,1.838960478782654,0.3317
|
||||
2,1.7586317385482788,0.3564,1.5927722663879396,0.4192
|
||||
3,1.7182956017303468,0.36878,1.6095290222167968,0.3962
|
||||
4,1.6878443021011353,0.3778,1.5945830318450929,0.4209
|
||||
5,1.6782778314971925,0.38232,1.4996938594818114,0.4596
|
||||
6,1.6617775799560548,0.38782,1.5637247476577758,0.4273
|
||||
7,1.6519146921920775,0.39274,1.4898227006912232,0.4477
|
||||
8,1.6319190932846068,0.39776,1.4631493810653686,0.464
|
||||
9,1.6271585168457032,0.39996,1.4658390745162964,0.4671
|
||||
10,1.6192712731170655,0.40386,1.4798445970535279,0.4555
|
||||
11,1.6236518589782716,0.4038,1.4518645431518555,0.4712
|
||||
12,1.6256605269241333,0.39904,1.5097844490051269,0.4606
|
||||
13,1.6252113864517213,0.4029,1.4985135524749755,0.4628
|
||||
14,1.6405798107147216,0.40094,1.5247799369812012,0.4417
|
||||
15,1.6137488632202148,0.40722,1.470830341720581,0.4691
|
||||
16,1.6058656929779054,0.40896,1.4936083711624146,0.4535
|
||||
17,1.609079775390625,0.4086,1.5095022733688355,0.4407
|
||||
18,1.5937296617126464,0.41062,1.4561285724639892,0.4711
|
||||
19,1.6145524578094483,0.40402,1.4767372095108031,0.4599
|
||||
20,1.6014677686309815,0.4094,1.490078086090088,0.4439
|
||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
1,1.9662294528198243,0.28166,1.646554655456543,0.4059
|
||||
2,1.6907201608657836,0.38096,1.4890975648880005,0.4608
|
||||
3,1.630640150680542,0.40234,1.461022783470154,0.4703
|
||||
4,1.5946281551361083,0.41298,1.4765422527313232,0.4582
|
||||
5,1.5847036001586914,0.41944,1.463464338684082,0.4656
|
||||
6,1.5700461378860473,0.42448,1.4435549175262452,0.4742
|
||||
7,1.5596910428237916,0.43166,1.4010505067825318,0.4815
|
||||
8,1.5500616349411012,0.4339,1.4645743618011475,0.4736
|
||||
9,1.5521124801254274,0.4347,1.3910032358169555,0.4965
|
||||
10,1.540557314529419,0.43936,1.3937551671981812,0.4963
|
||||
11,1.542716057395935,0.4397,1.3852252645492553,0.5065
|
||||
12,1.5426535359954834,0.43796,1.3814128866195678,0.4952
|
||||
13,1.5383161214828491,0.43854,1.3704833930969238,0.519
|
||||
14,1.535815538673401,0.43938,1.3828128046035766,0.4922
|
||||
15,1.5208821871185303,0.44786,1.336184846496582,0.5174
|
||||
16,1.5207045543670654,0.44292,1.3120759601593017,0.5318
|
||||
17,1.5427820779800414,0.44198,1.3777759956359863,0.5101
|
||||
18,1.5282205264282227,0.44214,1.3206209297180176,0.5246
|
||||
19,1.5153924929046632,0.45148,1.440579479789734,0.4926
|
||||
20,1.5200670809936523,0.44844,1.35802781791687,0.5012
|
||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
1,1.9782473403930665,0.2757,1.7940137519836425,0.3604
|
||||
2,1.7881652750396728,0.34256,1.6846075788497925,0.383
|
||||
3,1.7298297366714477,0.36016,1.6570421657562255,0.3849
|
||||
4,1.701125471496582,0.36964,1.6060110397338867,0.4051
|
||||
5,1.6930271649169921,0.3764,1.5627256288528442,0.4322
|
||||
6,1.6890782552337646,0.3793,1.5718454141616822,0.4155
|
||||
7,1.6894171588134765,0.37854,1.5689407793045045,0.4244
|
||||
8,1.6838004080963134,0.37988,1.547055793952942,0.4361
|
||||
9,1.6820043857192992,0.38108,1.5525554042816163,0.4266
|
||||
10,1.6630719311523436,0.38704,1.5440392353057861,0.4309
|
||||
11,1.6606243139266967,0.38634,1.5547804042816162,0.4306
|
||||
12,1.6556413611602783,0.39148,1.5340405586242676,0.4356
|
||||
13,1.6465564861679076,0.39404,1.5331555698394776,0.4422
|
||||
14,1.6496008929824828,0.39452,1.5326438642501832,0.4355
|
||||
15,1.6501564659881591,0.39042,1.5048745851516723,0.4526
|
||||
16,1.638251790008545,0.39798,1.5019797897338867,0.4489
|
||||
17,1.6597554596710204,0.38882,1.5088586767196654,0.4484
|
||||
18,1.6430353671264648,0.39304,1.6406061777114869,0.3994
|
||||
19,1.6456201574325562,0.39314,1.516061517906189,0.4483
|
||||
20,1.6409141896820068,0.39418,1.4997223611831665,0.4508
|
||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
1,2.0717957442474364,0.23638,1.8070027614593507,0.3592
|
||||
2,1.7711991034317016,0.35626,1.544959555053711,0.4336
|
||||
3,1.6322058293914794,0.4069,1.4367220252990722,0.4826
|
||||
4,1.5630220341491698,0.43416,1.37243994140625,0.5099
|
||||
5,1.4982818214797973,0.45784,1.2836783926010131,0.5423
|
||||
6,1.4538921988677977,0.47784,1.2316193922042846,0.5584
|
||||
7,1.4066726916503907,0.4912,1.1759659088134766,0.5824
|
||||
8,1.3719631880187988,0.51076,1.150549816131592,0.5948
|
||||
9,1.3426129550933839,0.51988,1.1507357816696167,0.5881
|
||||
10,1.3073690589904785,0.53344,1.0885456802368163,0.6235
|
||||
11,1.2872175302124023,0.54074,1.0516377550125122,0.6285
|
||||
12,1.266133660888672,0.54882,1.0233188526153565,0.6413
|
||||
13,1.2529394985961915,0.55518,1.0078511615753174,0.6473
|
||||
14,1.2264000122833252,0.56462,1.0189788675308227,0.6436
|
||||
15,1.2245289393615724,0.56466,1.0103674605369568,0.6484
|
||||
16,1.208251329650879,0.56842,0.9705223019599915,0.6642
|
||||
17,1.1961261875534057,0.57536,1.0117724663734435,0.645
|
||||
18,1.1778298877716065,0.58256,0.9588415849685669,0.6629
|
||||
19,1.1742403998947144,0.58666,0.9755858589172364,0.657
|
||||
20,1.165386855278015,0.58884,0.9380706154823303,0.6736
|
||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
1,2.053392539367676,0.2443,1.8277459175109863,0.3477
|
||||
2,1.787647081413269,0.35238,1.5101178413391114,0.4583
|
||||
3,1.646120939102173,0.40544,1.4628921775817871,0.4684
|
||||
4,1.5713705833053588,0.43396,1.3796582710266114,0.5046
|
||||
5,1.5172283823394774,0.45338,1.3074881475448608,0.5348
|
||||
6,1.4627742120742797,0.47362,1.2615061752319336,0.5529
|
||||
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||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
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||||
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||||
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||||
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||||
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||||
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||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
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||||
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||||
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||||
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||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
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||||
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||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
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||||
|
@@ -0,0 +1,21 @@
|
||||
epoch,train_loss,train_acc,test_loss,test_acc
|
||||
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||||
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@@ -0,0 +1,21 @@
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||||
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||||
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||||
|
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||||
11.8
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||||
4
|
||||
NVIDIA GeForce RTX 4090
|
||||
True
|
||||
Message sent successfully!
|
||||
Namespace(batch_size=128, lr=0.01, epochs=20, analyze=False)
|
||||
SEED 42
|
||||
[sgd][none][epoch 1] train_loss=2.0043, train_acc=0.2652, test_acc=0.3901
|
||||
[sgd][none][epoch 2] train_loss=1.5483, train_acc=0.4419, test_acc=0.5058
|
||||
[sgd][none][epoch 3] train_loss=1.3662, train_acc=0.5107, test_acc=0.5433
|
||||
[sgd][none][epoch 4] train_loss=1.2579, train_acc=0.5517, test_acc=0.5871
|
||||
[sgd][none][epoch 5] train_loss=1.1643, train_acc=0.5869, test_acc=0.6003
|
||||
[sgd][none][epoch 6] train_loss=1.0922, train_acc=0.6139, test_acc=0.6099
|
||||
[sgd][none][epoch 7] train_loss=1.0241, train_acc=0.6380, test_acc=0.6553
|
||||
[sgd][none][epoch 8] train_loss=0.9711, train_acc=0.6592, test_acc=0.6620
|
||||
[sgd][none][epoch 9] train_loss=0.9307, train_acc=0.6708, test_acc=0.6742
|
||||
[sgd][none][epoch 10] train_loss=0.8810, train_acc=0.6894, test_acc=0.6750
|
||||
[sgd][none][epoch 11] train_loss=0.8455, train_acc=0.7029, test_acc=0.6799
|
||||
[sgd][none][epoch 12] train_loss=0.8025, train_acc=0.7183, test_acc=0.6893
|
||||
[sgd][none][epoch 13] train_loss=0.7720, train_acc=0.7281, test_acc=0.6880
|
||||
[sgd][none][epoch 14] train_loss=0.7396, train_acc=0.7403, test_acc=0.6870
|
||||
[sgd][none][epoch 15] train_loss=0.7045, train_acc=0.7509, test_acc=0.6827
|
||||
[sgd][none][epoch 16] train_loss=0.6759, train_acc=0.7637, test_acc=0.6987
|
||||
[sgd][none][epoch 17] train_loss=0.6473, train_acc=0.7725, test_acc=0.7049
|
||||
[sgd][none][epoch 18] train_loss=0.6272, train_acc=0.7775, test_acc=0.6964
|
||||
[sgd][none][epoch 19] train_loss=0.5973, train_acc=0.7895, test_acc=0.6974
|
||||
[sgd][none][epoch 20] train_loss=0.5727, train_acc=0.7991, test_acc=0.7017
|
||||
[sgd][standard][epoch 1] train_loss=2.0175, train_acc=0.2628, test_acc=0.3998
|
||||
[sgd][standard][epoch 2] train_loss=1.6904, train_acc=0.3880, test_acc=0.4740
|
||||
[sgd][standard][epoch 3] train_loss=1.5346, train_acc=0.4427, test_acc=0.5145
|
||||
[sgd][standard][epoch 4] train_loss=1.4618, train_acc=0.4689, test_acc=0.5426
|
||||
[sgd][standard][epoch 5] train_loss=1.3889, train_acc=0.4969, test_acc=0.5703
|
||||
[sgd][standard][epoch 6] train_loss=1.3289, train_acc=0.5219, test_acc=0.6004
|
||||
[sgd][standard][epoch 7] train_loss=1.2710, train_acc=0.5442, test_acc=0.6111
|
||||
[sgd][standard][epoch 8] train_loss=1.2280, train_acc=0.5619, test_acc=0.6270
|
||||
[sgd][standard][epoch 9] train_loss=1.1939, train_acc=0.5735, test_acc=0.6264
|
||||
[sgd][standard][epoch 10] train_loss=1.1654, train_acc=0.5873, test_acc=0.6489
|
||||
[sgd][standard][epoch 11] train_loss=1.1431, train_acc=0.5929, test_acc=0.6440
|
||||
[sgd][standard][epoch 12] train_loss=1.1233, train_acc=0.6007, test_acc=0.6712
|
||||
[sgd][standard][epoch 13] train_loss=1.1012, train_acc=0.6088, test_acc=0.6751
|
||||
[sgd][standard][epoch 14] train_loss=1.0850, train_acc=0.6153, test_acc=0.6806
|
||||
[sgd][standard][epoch 15] train_loss=1.0652, train_acc=0.6227, test_acc=0.6784
|
||||
[sgd][standard][epoch 16] train_loss=1.0540, train_acc=0.6272, test_acc=0.6883
|
||||
[sgd][standard][epoch 17] train_loss=1.0403, train_acc=0.6325, test_acc=0.6792
|
||||
[sgd][standard][epoch 18] train_loss=1.0297, train_acc=0.6359, test_acc=0.6907
|
||||
[sgd][standard][epoch 19] train_loss=1.0156, train_acc=0.6437, test_acc=0.6983
|
||||
[sgd][standard][epoch 20] train_loss=1.0131, train_acc=0.6407, test_acc=0.6983
|
||||
[sgd][aggressive][epoch 1] train_loss=2.0534, train_acc=0.2443, test_acc=0.3477
|
||||
[sgd][aggressive][epoch 2] train_loss=1.7876, train_acc=0.3524, test_acc=0.4583
|
||||
[sgd][aggressive][epoch 3] train_loss=1.6461, train_acc=0.4054, test_acc=0.4684
|
||||
[sgd][aggressive][epoch 4] train_loss=1.5714, train_acc=0.4340, test_acc=0.5046
|
||||
[sgd][aggressive][epoch 5] train_loss=1.5172, train_acc=0.4534, test_acc=0.5348
|
||||
[sgd][aggressive][epoch 6] train_loss=1.4628, train_acc=0.4736, test_acc=0.5529
|
||||
[sgd][aggressive][epoch 7] train_loss=1.4181, train_acc=0.4933, test_acc=0.5795
|
||||
[sgd][aggressive][epoch 8] train_loss=1.3875, train_acc=0.5027, test_acc=0.5967
|
||||
[sgd][aggressive][epoch 9] train_loss=1.3532, train_acc=0.5146, test_acc=0.5977
|
||||
[sgd][aggressive][epoch 10] train_loss=1.3283, train_acc=0.5265, test_acc=0.6028
|
||||
[sgd][aggressive][epoch 11] train_loss=1.3050, train_acc=0.5333, test_acc=0.6133
|
||||
[sgd][aggressive][epoch 12] train_loss=1.2840, train_acc=0.5430, test_acc=0.6329
|
||||
[sgd][aggressive][epoch 13] train_loss=1.2662, train_acc=0.5505, test_acc=0.6011
|
||||
[sgd][aggressive][epoch 14] train_loss=1.2491, train_acc=0.5545, test_acc=0.6490
|
||||
[sgd][aggressive][epoch 15] train_loss=1.2334, train_acc=0.5621, test_acc=0.6452
|
||||
[sgd][aggressive][epoch 16] train_loss=1.2266, train_acc=0.5656, test_acc=0.6381
|
||||
[sgd][aggressive][epoch 17] train_loss=1.2157, train_acc=0.5678, test_acc=0.6482
|
||||
[sgd][aggressive][epoch 18] train_loss=1.2051, train_acc=0.5745, test_acc=0.6619
|
||||
[sgd][aggressive][epoch 19] train_loss=1.1854, train_acc=0.5793, test_acc=0.6701
|
||||
[sgd][aggressive][epoch 20] train_loss=1.1799, train_acc=0.5823, test_acc=0.6529
|
||||
[adam][none][epoch 1] train_loss=1.7539, train_acc=0.3666, test_acc=0.4474
|
||||
[adam][none][epoch 2] train_loss=1.5013, train_acc=0.4559, test_acc=0.4801
|
||||
[adam][none][epoch 3] train_loss=1.4560, train_acc=0.4740, test_acc=0.5110
|
||||
[adam][none][epoch 4] train_loss=1.4221, train_acc=0.4882, test_acc=0.5162
|
||||
[adam][none][epoch 5] train_loss=1.3943, train_acc=0.4997, test_acc=0.5221
|
||||
[adam][none][epoch 6] train_loss=1.3840, train_acc=0.5037, test_acc=0.5295
|
||||
[adam][none][epoch 7] train_loss=1.3604, train_acc=0.5146, test_acc=0.5269
|
||||
[adam][none][epoch 8] train_loss=1.3529, train_acc=0.5131, test_acc=0.5478
|
||||
[adam][none][epoch 9] train_loss=1.3496, train_acc=0.5150, test_acc=0.5602
|
||||
[adam][none][epoch 10] train_loss=1.3384, train_acc=0.5199, test_acc=0.5414
|
||||
[adam][none][epoch 11] train_loss=1.3299, train_acc=0.5230, test_acc=0.5535
|
||||
[adam][none][epoch 12] train_loss=1.3380, train_acc=0.5231, test_acc=0.5783
|
||||
[adam][none][epoch 13] train_loss=1.3283, train_acc=0.5238, test_acc=0.5622
|
||||
[adam][none][epoch 14] train_loss=1.3241, train_acc=0.5305, test_acc=0.5585
|
||||
[adam][none][epoch 15] train_loss=1.3172, train_acc=0.5315, test_acc=0.5775
|
||||
[adam][none][epoch 16] train_loss=1.3192, train_acc=0.5301, test_acc=0.5694
|
||||
[adam][none][epoch 17] train_loss=1.3199, train_acc=0.5286, test_acc=0.5755
|
||||
[adam][none][epoch 18] train_loss=1.3246, train_acc=0.5278, test_acc=0.5589
|
||||
[adam][none][epoch 19] train_loss=1.3320, train_acc=0.5294, test_acc=0.5715
|
||||
[adam][none][epoch 20] train_loss=1.3130, train_acc=0.5311, test_acc=0.5754
|
||||
[adam][standard][epoch 1] train_loss=1.9662, train_acc=0.2817, test_acc=0.4059
|
||||
[adam][standard][epoch 2] train_loss=1.6907, train_acc=0.3810, test_acc=0.4608
|
||||
[adam][standard][epoch 3] train_loss=1.6306, train_acc=0.4023, test_acc=0.4703
|
||||
[adam][standard][epoch 4] train_loss=1.5946, train_acc=0.4130, test_acc=0.4582
|
||||
[adam][standard][epoch 5] train_loss=1.5847, train_acc=0.4194, test_acc=0.4656
|
||||
[adam][standard][epoch 6] train_loss=1.5700, train_acc=0.4245, test_acc=0.4742
|
||||
[adam][standard][epoch 7] train_loss=1.5597, train_acc=0.4317, test_acc=0.4815
|
||||
[adam][standard][epoch 8] train_loss=1.5501, train_acc=0.4339, test_acc=0.4736
|
||||
[adam][standard][epoch 9] train_loss=1.5521, train_acc=0.4347, test_acc=0.4965
|
||||
[adam][standard][epoch 10] train_loss=1.5406, train_acc=0.4394, test_acc=0.4963
|
||||
[adam][standard][epoch 11] train_loss=1.5427, train_acc=0.4397, test_acc=0.5065
|
||||
[adam][standard][epoch 12] train_loss=1.5427, train_acc=0.4380, test_acc=0.4952
|
||||
[adam][standard][epoch 13] train_loss=1.5383, train_acc=0.4385, test_acc=0.5190
|
||||
[adam][standard][epoch 14] train_loss=1.5358, train_acc=0.4394, test_acc=0.4922
|
||||
[adam][standard][epoch 15] train_loss=1.5209, train_acc=0.4479, test_acc=0.5174
|
||||
[adam][standard][epoch 16] train_loss=1.5207, train_acc=0.4429, test_acc=0.5318
|
||||
[adam][standard][epoch 17] train_loss=1.5428, train_acc=0.4420, test_acc=0.5101
|
||||
[adam][standard][epoch 18] train_loss=1.5282, train_acc=0.4421, test_acc=0.5246
|
||||
[adam][standard][epoch 19] train_loss=1.5154, train_acc=0.4515, test_acc=0.4926
|
||||
[adam][standard][epoch 20] train_loss=1.5201, train_acc=0.4484, test_acc=0.5012
|
||||
[adam][aggressive][epoch 1] train_loss=1.9946, train_acc=0.2655, test_acc=0.3420
|
||||
[adam][aggressive][epoch 2] train_loss=1.7975, train_acc=0.3353, test_acc=0.4064
|
||||
[adam][aggressive][epoch 3] train_loss=1.7743, train_acc=0.3444, test_acc=0.4200
|
||||
[adam][aggressive][epoch 4] train_loss=1.7372, train_acc=0.3579, test_acc=0.4113
|
||||
[adam][aggressive][epoch 5] train_loss=1.7270, train_acc=0.3684, test_acc=0.4221
|
||||
[adam][aggressive][epoch 6] train_loss=1.7161, train_acc=0.3704, test_acc=0.4449
|
||||
[adam][aggressive][epoch 7] train_loss=1.6962, train_acc=0.3799, test_acc=0.4352
|
||||
[adam][aggressive][epoch 8] train_loss=1.6957, train_acc=0.3808, test_acc=0.4409
|
||||
[adam][aggressive][epoch 9] train_loss=1.6931, train_acc=0.3804, test_acc=0.4434
|
||||
[adam][aggressive][epoch 10] train_loss=1.6858, train_acc=0.3787, test_acc=0.4671
|
||||
[adam][aggressive][epoch 11] train_loss=1.6876, train_acc=0.3814, test_acc=0.4560
|
||||
[adam][aggressive][epoch 12] train_loss=1.6893, train_acc=0.3837, test_acc=0.4288
|
||||
[adam][aggressive][epoch 13] train_loss=1.6795, train_acc=0.3832, test_acc=0.4422
|
||||
[adam][aggressive][epoch 14] train_loss=1.6710, train_acc=0.3851, test_acc=0.4082
|
||||
[adam][aggressive][epoch 15] train_loss=1.6753, train_acc=0.3846, test_acc=0.4628
|
||||
[adam][aggressive][epoch 16] train_loss=1.6733, train_acc=0.3831, test_acc=0.4370
|
||||
[adam][aggressive][epoch 17] train_loss=1.6646, train_acc=0.3890, test_acc=0.4529
|
||||
[adam][aggressive][epoch 18] train_loss=1.6783, train_acc=0.3829, test_acc=0.4649
|
||||
[adam][aggressive][epoch 19] train_loss=1.6775, train_acc=0.3857, test_acc=0.4383
|
||||
[adam][aggressive][epoch 20] train_loss=1.6718, train_acc=0.3821, test_acc=0.4534
|
||||
SEED 123
|
||||
[sgd][none][epoch 1] train_loss=1.9311, train_acc=0.2982, test_acc=0.4331
|
||||
[sgd][none][epoch 2] train_loss=1.5091, train_acc=0.4602, test_acc=0.5060
|
||||
[sgd][none][epoch 3] train_loss=1.3347, train_acc=0.5203, test_acc=0.5345
|
||||
[sgd][none][epoch 4] train_loss=1.2469, train_acc=0.5554, test_acc=0.5855
|
||||
[sgd][none][epoch 5] train_loss=1.1582, train_acc=0.5873, test_acc=0.6146
|
||||
[sgd][none][epoch 6] train_loss=1.0869, train_acc=0.6134, test_acc=0.6336
|
||||
[sgd][none][epoch 7] train_loss=1.0187, train_acc=0.6405, test_acc=0.6517
|
||||
[sgd][none][epoch 8] train_loss=0.9732, train_acc=0.6563, test_acc=0.6470
|
||||
[sgd][none][epoch 9] train_loss=0.9221, train_acc=0.6754, test_acc=0.6732
|
||||
[sgd][none][epoch 10] train_loss=0.8899, train_acc=0.6855, test_acc=0.6785
|
||||
[sgd][none][epoch 11] train_loss=0.8532, train_acc=0.6995, test_acc=0.6832
|
||||
[sgd][none][epoch 12] train_loss=0.8089, train_acc=0.7154, test_acc=0.6861
|
||||
[sgd][none][epoch 13] train_loss=0.7808, train_acc=0.7241, test_acc=0.6775
|
||||
[sgd][none][epoch 14] train_loss=0.7539, train_acc=0.7348, test_acc=0.6845
|
||||
[sgd][none][epoch 15] train_loss=0.7263, train_acc=0.7432, test_acc=0.6986
|
||||
[sgd][none][epoch 16] train_loss=0.6967, train_acc=0.7529, test_acc=0.6930
|
||||
[sgd][none][epoch 17] train_loss=0.6710, train_acc=0.7639, test_acc=0.6845
|
||||
[sgd][none][epoch 18] train_loss=0.6452, train_acc=0.7724, test_acc=0.7039
|
||||
[sgd][none][epoch 19] train_loss=0.6094, train_acc=0.7859, test_acc=0.7033
|
||||
[sgd][none][epoch 20] train_loss=0.5979, train_acc=0.7868, test_acc=0.7018
|
||||
[sgd][standard][epoch 1] train_loss=2.0551, train_acc=0.2467, test_acc=0.3644
|
||||
[sgd][standard][epoch 2] train_loss=1.7425, train_acc=0.3696, test_acc=0.4334
|
||||
[sgd][standard][epoch 3] train_loss=1.5560, train_acc=0.4329, test_acc=0.5017
|
||||
[sgd][standard][epoch 4] train_loss=1.4621, train_acc=0.4680, test_acc=0.5380
|
||||
[sgd][standard][epoch 5] train_loss=1.3934, train_acc=0.4952, test_acc=0.5701
|
||||
[sgd][standard][epoch 6] train_loss=1.3294, train_acc=0.5213, test_acc=0.5866
|
||||
[sgd][standard][epoch 7] train_loss=1.2766, train_acc=0.5421, test_acc=0.6181
|
||||
[sgd][standard][epoch 8] train_loss=1.2316, train_acc=0.5569, test_acc=0.6213
|
||||
[sgd][standard][epoch 9] train_loss=1.2074, train_acc=0.5672, test_acc=0.6211
|
||||
[sgd][standard][epoch 10] train_loss=1.1776, train_acc=0.5785, test_acc=0.6330
|
||||
[sgd][standard][epoch 11] train_loss=1.1488, train_acc=0.5902, test_acc=0.6505
|
||||
[sgd][standard][epoch 12] train_loss=1.1336, train_acc=0.5979, test_acc=0.6629
|
||||
[sgd][standard][epoch 13] train_loss=1.1190, train_acc=0.5994, test_acc=0.6655
|
||||
[sgd][standard][epoch 14] train_loss=1.0946, train_acc=0.6125, test_acc=0.6774
|
||||
[sgd][standard][epoch 15] train_loss=1.0848, train_acc=0.6134, test_acc=0.6762
|
||||
[sgd][standard][epoch 16] train_loss=1.0732, train_acc=0.6182, test_acc=0.6788
|
||||
[sgd][standard][epoch 17] train_loss=1.0666, train_acc=0.6216, test_acc=0.6879
|
||||
[sgd][standard][epoch 18] train_loss=1.0515, train_acc=0.6270, test_acc=0.6872
|
||||
[sgd][standard][epoch 19] train_loss=1.0466, train_acc=0.6275, test_acc=0.6877
|
||||
[sgd][standard][epoch 20] train_loss=1.0256, train_acc=0.6372, test_acc=0.6987
|
||||
[sgd][aggressive][epoch 1] train_loss=2.0718, train_acc=0.2364, test_acc=0.3592
|
||||
[sgd][aggressive][epoch 2] train_loss=1.7712, train_acc=0.3563, test_acc=0.4336
|
||||
[sgd][aggressive][epoch 3] train_loss=1.6322, train_acc=0.4069, test_acc=0.4826
|
||||
[sgd][aggressive][epoch 4] train_loss=1.5630, train_acc=0.4342, test_acc=0.5099
|
||||
[sgd][aggressive][epoch 5] train_loss=1.4983, train_acc=0.4578, test_acc=0.5423
|
||||
[sgd][aggressive][epoch 6] train_loss=1.4539, train_acc=0.4778, test_acc=0.5584
|
||||
[sgd][aggressive][epoch 7] train_loss=1.4067, train_acc=0.4912, test_acc=0.5824
|
||||
[sgd][aggressive][epoch 8] train_loss=1.3720, train_acc=0.5108, test_acc=0.5948
|
||||
[sgd][aggressive][epoch 9] train_loss=1.3426, train_acc=0.5199, test_acc=0.5881
|
||||
[sgd][aggressive][epoch 10] train_loss=1.3074, train_acc=0.5334, test_acc=0.6235
|
||||
[sgd][aggressive][epoch 11] train_loss=1.2872, train_acc=0.5407, test_acc=0.6285
|
||||
[sgd][aggressive][epoch 12] train_loss=1.2661, train_acc=0.5488, test_acc=0.6413
|
||||
[sgd][aggressive][epoch 13] train_loss=1.2529, train_acc=0.5552, test_acc=0.6473
|
||||
[sgd][aggressive][epoch 14] train_loss=1.2264, train_acc=0.5646, test_acc=0.6436
|
||||
[sgd][aggressive][epoch 15] train_loss=1.2245, train_acc=0.5647, test_acc=0.6484
|
||||
[sgd][aggressive][epoch 16] train_loss=1.2083, train_acc=0.5684, test_acc=0.6642
|
||||
[sgd][aggressive][epoch 17] train_loss=1.1961, train_acc=0.5754, test_acc=0.6450
|
||||
[sgd][aggressive][epoch 18] train_loss=1.1778, train_acc=0.5826, test_acc=0.6629
|
||||
[sgd][aggressive][epoch 19] train_loss=1.1742, train_acc=0.5867, test_acc=0.6570
|
||||
[sgd][aggressive][epoch 20] train_loss=1.1654, train_acc=0.5888, test_acc=0.6736
|
||||
[adam][none][epoch 1] train_loss=1.7930, train_acc=0.3436, test_acc=0.4587
|
||||
[adam][none][epoch 2] train_loss=1.5388, train_acc=0.4398, test_acc=0.4631
|
||||
[adam][none][epoch 3] train_loss=1.4963, train_acc=0.4578, test_acc=0.4876
|
||||
[adam][none][epoch 4] train_loss=1.4608, train_acc=0.4701, test_acc=0.5141
|
||||
[adam][none][epoch 5] train_loss=1.4432, train_acc=0.4794, test_acc=0.5123
|
||||
[adam][none][epoch 6] train_loss=1.4211, train_acc=0.4871, test_acc=0.5290
|
||||
[adam][none][epoch 7] train_loss=1.4216, train_acc=0.4891, test_acc=0.5334
|
||||
[adam][none][epoch 8] train_loss=1.4136, train_acc=0.4890, test_acc=0.5363
|
||||
[adam][none][epoch 9] train_loss=1.4088, train_acc=0.4921, test_acc=0.5187
|
||||
[adam][none][epoch 10] train_loss=1.4120, train_acc=0.4949, test_acc=0.5335
|
||||
[adam][none][epoch 11] train_loss=1.3871, train_acc=0.5001, test_acc=0.5329
|
||||
[adam][none][epoch 12] train_loss=1.4000, train_acc=0.4951, test_acc=0.5462
|
||||
[adam][none][epoch 13] train_loss=1.3897, train_acc=0.5010, test_acc=0.5448
|
||||
[adam][none][epoch 14] train_loss=1.3929, train_acc=0.4987, test_acc=0.5352
|
||||
[adam][none][epoch 15] train_loss=1.3816, train_acc=0.5039, test_acc=0.5380
|
||||
[adam][none][epoch 16] train_loss=1.3859, train_acc=0.5033, test_acc=0.5447
|
||||
[adam][none][epoch 17] train_loss=1.3742, train_acc=0.5099, test_acc=0.5518
|
||||
[adam][none][epoch 18] train_loss=1.3722, train_acc=0.5071, test_acc=0.5568
|
||||
[adam][none][epoch 19] train_loss=1.3785, train_acc=0.5065, test_acc=0.5513
|
||||
[adam][none][epoch 20] train_loss=1.3660, train_acc=0.5107, test_acc=0.5414
|
||||
[adam][standard][epoch 1] train_loss=1.9765, train_acc=0.2750, test_acc=0.3317
|
||||
[adam][standard][epoch 2] train_loss=1.7586, train_acc=0.3564, test_acc=0.4192
|
||||
[adam][standard][epoch 3] train_loss=1.7183, train_acc=0.3688, test_acc=0.3962
|
||||
[adam][standard][epoch 4] train_loss=1.6878, train_acc=0.3778, test_acc=0.4209
|
||||
[adam][standard][epoch 5] train_loss=1.6783, train_acc=0.3823, test_acc=0.4596
|
||||
[adam][standard][epoch 6] train_loss=1.6618, train_acc=0.3878, test_acc=0.4273
|
||||
[adam][standard][epoch 7] train_loss=1.6519, train_acc=0.3927, test_acc=0.4477
|
||||
[adam][standard][epoch 8] train_loss=1.6319, train_acc=0.3978, test_acc=0.4640
|
||||
[adam][standard][epoch 9] train_loss=1.6272, train_acc=0.4000, test_acc=0.4671
|
||||
[adam][standard][epoch 10] train_loss=1.6193, train_acc=0.4039, test_acc=0.4555
|
||||
[adam][standard][epoch 11] train_loss=1.6237, train_acc=0.4038, test_acc=0.4712
|
||||
[adam][standard][epoch 12] train_loss=1.6257, train_acc=0.3990, test_acc=0.4606
|
||||
[adam][standard][epoch 13] train_loss=1.6252, train_acc=0.4029, test_acc=0.4628
|
||||
[adam][standard][epoch 14] train_loss=1.6406, train_acc=0.4009, test_acc=0.4417
|
||||
[adam][standard][epoch 15] train_loss=1.6137, train_acc=0.4072, test_acc=0.4691
|
||||
[adam][standard][epoch 16] train_loss=1.6059, train_acc=0.4090, test_acc=0.4535
|
||||
[adam][standard][epoch 17] train_loss=1.6091, train_acc=0.4086, test_acc=0.4407
|
||||
[adam][standard][epoch 18] train_loss=1.5937, train_acc=0.4106, test_acc=0.4711
|
||||
[adam][standard][epoch 19] train_loss=1.6146, train_acc=0.4040, test_acc=0.4599
|
||||
[adam][standard][epoch 20] train_loss=1.6015, train_acc=0.4094, test_acc=0.4439
|
||||
[adam][aggressive][epoch 1] train_loss=2.0220, train_acc=0.2568, test_acc=0.3374
|
||||
[adam][aggressive][epoch 2] train_loss=1.7999, train_acc=0.3355, test_acc=0.4133
|
||||
[adam][aggressive][epoch 3] train_loss=1.7349, train_acc=0.3581, test_acc=0.4205
|
||||
[adam][aggressive][epoch 4] train_loss=1.7072, train_acc=0.3690, test_acc=0.4260
|
||||
[adam][aggressive][epoch 5] train_loss=1.6942, train_acc=0.3751, test_acc=0.4365
|
||||
[adam][aggressive][epoch 6] train_loss=1.6825, train_acc=0.3806, test_acc=0.4198
|
||||
[adam][aggressive][epoch 7] train_loss=1.6737, train_acc=0.3837, test_acc=0.4576
|
||||
[adam][aggressive][epoch 8] train_loss=1.6662, train_acc=0.3874, test_acc=0.4461
|
||||
[adam][aggressive][epoch 9] train_loss=1.6690, train_acc=0.3842, test_acc=0.4494
|
||||
[adam][aggressive][epoch 10] train_loss=1.6586, train_acc=0.3910, test_acc=0.4718
|
||||
[adam][aggressive][epoch 11] train_loss=1.6606, train_acc=0.3920, test_acc=0.4709
|
||||
[adam][aggressive][epoch 12] train_loss=1.6647, train_acc=0.3915, test_acc=0.4603
|
||||
[adam][aggressive][epoch 13] train_loss=1.6484, train_acc=0.3987, test_acc=0.4381
|
||||
[adam][aggressive][epoch 14] train_loss=1.6552, train_acc=0.3902, test_acc=0.4754
|
||||
[adam][aggressive][epoch 15] train_loss=1.6531, train_acc=0.3944, test_acc=0.4632
|
||||
[adam][aggressive][epoch 16] train_loss=1.6465, train_acc=0.3957, test_acc=0.4774
|
||||
[adam][aggressive][epoch 17] train_loss=1.6686, train_acc=0.3903, test_acc=0.4495
|
||||
[adam][aggressive][epoch 18] train_loss=1.6486, train_acc=0.3973, test_acc=0.4583
|
||||
[adam][aggressive][epoch 19] train_loss=1.6871, train_acc=0.3846, test_acc=0.4529
|
||||
[adam][aggressive][epoch 20] train_loss=1.6608, train_acc=0.3928, test_acc=0.4519
|
||||
SEED 999
|
||||
[sgd][none][epoch 1] train_loss=1.9648, train_acc=0.2823, test_acc=0.4082
|
||||
[sgd][none][epoch 2] train_loss=1.5440, train_acc=0.4426, test_acc=0.4967
|
||||
[sgd][none][epoch 3] train_loss=1.3841, train_acc=0.5031, test_acc=0.5481
|
||||
[sgd][none][epoch 4] train_loss=1.2708, train_acc=0.5468, test_acc=0.5698
|
||||
[sgd][none][epoch 5] train_loss=1.1830, train_acc=0.5788, test_acc=0.6024
|
||||
[sgd][none][epoch 6] train_loss=1.0973, train_acc=0.6119, test_acc=0.6247
|
||||
[sgd][none][epoch 7] train_loss=1.0351, train_acc=0.6321, test_acc=0.6337
|
||||
[sgd][none][epoch 8] train_loss=0.9852, train_acc=0.6519, test_acc=0.6516
|
||||
[sgd][none][epoch 9] train_loss=0.9321, train_acc=0.6699, test_acc=0.6519
|
||||
[sgd][none][epoch 10] train_loss=0.8937, train_acc=0.6880, test_acc=0.6659
|
||||
[sgd][none][epoch 11] train_loss=0.8555, train_acc=0.6975, test_acc=0.6739
|
||||
[sgd][none][epoch 12] train_loss=0.8128, train_acc=0.7147, test_acc=0.6714
|
||||
[sgd][none][epoch 13] train_loss=0.7774, train_acc=0.7244, test_acc=0.6844
|
||||
[sgd][none][epoch 14] train_loss=0.7446, train_acc=0.7378, test_acc=0.6712
|
||||
[sgd][none][epoch 15] train_loss=0.7130, train_acc=0.7504, test_acc=0.6967
|
||||
[sgd][none][epoch 16] train_loss=0.6769, train_acc=0.7616, test_acc=0.6910
|
||||
[sgd][none][epoch 17] train_loss=0.6570, train_acc=0.7681, test_acc=0.6931
|
||||
[sgd][none][epoch 18] train_loss=0.6386, train_acc=0.7762, test_acc=0.7021
|
||||
[sgd][none][epoch 19] train_loss=0.6080, train_acc=0.7853, test_acc=0.6982
|
||||
[sgd][none][epoch 20] train_loss=0.5840, train_acc=0.7949, test_acc=0.6778
|
||||
[sgd][standard][epoch 1] train_loss=2.0407, train_acc=0.2494, test_acc=0.3775
|
||||
[sgd][standard][epoch 2] train_loss=1.6937, train_acc=0.3859, test_acc=0.4468
|
||||
[sgd][standard][epoch 3] train_loss=1.5486, train_acc=0.4374, test_acc=0.4884
|
||||
[sgd][standard][epoch 4] train_loss=1.4723, train_acc=0.4689, test_acc=0.5155
|
||||
[sgd][standard][epoch 5] train_loss=1.4086, train_acc=0.4926, test_acc=0.5603
|
||||
[sgd][standard][epoch 6] train_loss=1.3517, train_acc=0.5127, test_acc=0.5646
|
||||
[sgd][standard][epoch 7] train_loss=1.3047, train_acc=0.5300, test_acc=0.5974
|
||||
[sgd][standard][epoch 8] train_loss=1.2650, train_acc=0.5454, test_acc=0.6163
|
||||
[sgd][standard][epoch 9] train_loss=1.2220, train_acc=0.5641, test_acc=0.6208
|
||||
[sgd][standard][epoch 10] train_loss=1.1993, train_acc=0.5716, test_acc=0.6378
|
||||
[sgd][standard][epoch 11] train_loss=1.1627, train_acc=0.5833, test_acc=0.6552
|
||||
[sgd][standard][epoch 12] train_loss=1.1434, train_acc=0.5901, test_acc=0.6500
|
||||
[sgd][standard][epoch 13] train_loss=1.1314, train_acc=0.5986, test_acc=0.6619
|
||||
[sgd][standard][epoch 14] train_loss=1.1073, train_acc=0.6054, test_acc=0.6635
|
||||
[sgd][standard][epoch 15] train_loss=1.0958, train_acc=0.6111, test_acc=0.6747
|
||||
[sgd][standard][epoch 16] train_loss=1.0843, train_acc=0.6131, test_acc=0.6678
|
||||
[sgd][standard][epoch 17] train_loss=1.0639, train_acc=0.6221, test_acc=0.6751
|
||||
[sgd][standard][epoch 18] train_loss=1.0448, train_acc=0.6305, test_acc=0.6828
|
||||
[sgd][standard][epoch 19] train_loss=1.0394, train_acc=0.6302, test_acc=0.6652
|
||||
[sgd][standard][epoch 20] train_loss=1.0273, train_acc=0.6353, test_acc=0.6961
|
||||
[sgd][aggressive][epoch 1] train_loss=2.0646, train_acc=0.2437, test_acc=0.3856
|
||||
[sgd][aggressive][epoch 2] train_loss=1.7912, train_acc=0.3552, test_acc=0.4649
|
||||
[sgd][aggressive][epoch 3] train_loss=1.6363, train_acc=0.4080, test_acc=0.4622
|
||||
[sgd][aggressive][epoch 4] train_loss=1.5608, train_acc=0.4355, test_acc=0.4828
|
||||
[sgd][aggressive][epoch 5] train_loss=1.5063, train_acc=0.4545, test_acc=0.5366
|
||||
[sgd][aggressive][epoch 6] train_loss=1.4610, train_acc=0.4755, test_acc=0.5395
|
||||
[sgd][aggressive][epoch 7] train_loss=1.4184, train_acc=0.4916, test_acc=0.5608
|
||||
[sgd][aggressive][epoch 8] train_loss=1.3873, train_acc=0.5043, test_acc=0.5799
|
||||
[sgd][aggressive][epoch 9] train_loss=1.3462, train_acc=0.5190, test_acc=0.6037
|
||||
[sgd][aggressive][epoch 10] train_loss=1.3189, train_acc=0.5313, test_acc=0.6135
|
||||
[sgd][aggressive][epoch 11] train_loss=1.2964, train_acc=0.5383, test_acc=0.6157
|
||||
[sgd][aggressive][epoch 12] train_loss=1.2798, train_acc=0.5443, test_acc=0.6221
|
||||
[sgd][aggressive][epoch 13] train_loss=1.2447, train_acc=0.5550, test_acc=0.6303
|
||||
[sgd][aggressive][epoch 14] train_loss=1.2455, train_acc=0.5583, test_acc=0.6474
|
||||
[sgd][aggressive][epoch 15] train_loss=1.2229, train_acc=0.5663, test_acc=0.6583
|
||||
[sgd][aggressive][epoch 16] train_loss=1.2149, train_acc=0.5711, test_acc=0.6548
|
||||
[sgd][aggressive][epoch 17] train_loss=1.1953, train_acc=0.5769, test_acc=0.6514
|
||||
[sgd][aggressive][epoch 18] train_loss=1.1797, train_acc=0.5802, test_acc=0.6521
|
||||
[sgd][aggressive][epoch 19] train_loss=1.1690, train_acc=0.5845, test_acc=0.6624
|
||||
[sgd][aggressive][epoch 20] train_loss=1.1596, train_acc=0.5901, test_acc=0.6623
|
||||
[adam][none][epoch 1] train_loss=1.7632, train_acc=0.3531, test_acc=0.4299
|
||||
[adam][none][epoch 2] train_loss=1.5243, train_acc=0.4486, test_acc=0.4979
|
||||
[adam][none][epoch 3] train_loss=1.4566, train_acc=0.4711, test_acc=0.5188
|
||||
[adam][none][epoch 4] train_loss=1.4304, train_acc=0.4808, test_acc=0.5000
|
||||
[adam][none][epoch 5] train_loss=1.4109, train_acc=0.4907, test_acc=0.5087
|
||||
[adam][none][epoch 6] train_loss=1.4031, train_acc=0.4983, test_acc=0.5271
|
||||
[adam][none][epoch 7] train_loss=1.3831, train_acc=0.5013, test_acc=0.5123
|
||||
[adam][none][epoch 8] train_loss=1.3821, train_acc=0.5024, test_acc=0.5529
|
||||
[adam][none][epoch 9] train_loss=1.3669, train_acc=0.5103, test_acc=0.5251
|
||||
[adam][none][epoch 10] train_loss=1.3697, train_acc=0.5087, test_acc=0.5277
|
||||
[adam][none][epoch 11] train_loss=1.3734, train_acc=0.5077, test_acc=0.5407
|
||||
[adam][none][epoch 12] train_loss=1.3641, train_acc=0.5121, test_acc=0.5310
|
||||
[adam][none][epoch 13] train_loss=1.3571, train_acc=0.5137, test_acc=0.5501
|
||||
[adam][none][epoch 14] train_loss=1.3592, train_acc=0.5151, test_acc=0.5302
|
||||
[adam][none][epoch 15] train_loss=1.3578, train_acc=0.5142, test_acc=0.5569
|
||||
[adam][none][epoch 16] train_loss=1.3404, train_acc=0.5190, test_acc=0.5500
|
||||
[adam][none][epoch 17] train_loss=1.3544, train_acc=0.5151, test_acc=0.5515
|
||||
[adam][none][epoch 18] train_loss=1.3483, train_acc=0.5184, test_acc=0.5486
|
||||
[adam][none][epoch 19] train_loss=1.3437, train_acc=0.5180, test_acc=0.5480
|
||||
[adam][none][epoch 20] train_loss=1.3356, train_acc=0.5202, test_acc=0.5477
|
||||
[adam][standard][epoch 1] train_loss=1.9782, train_acc=0.2757, test_acc=0.3604
|
||||
[adam][standard][epoch 2] train_loss=1.7882, train_acc=0.3426, test_acc=0.3830
|
||||
[adam][standard][epoch 3] train_loss=1.7298, train_acc=0.3602, test_acc=0.3849
|
||||
[adam][standard][epoch 4] train_loss=1.7011, train_acc=0.3696, test_acc=0.4051
|
||||
[adam][standard][epoch 5] train_loss=1.6930, train_acc=0.3764, test_acc=0.4322
|
||||
[adam][standard][epoch 6] train_loss=1.6891, train_acc=0.3793, test_acc=0.4155
|
||||
[adam][standard][epoch 7] train_loss=1.6894, train_acc=0.3785, test_acc=0.4244
|
||||
[adam][standard][epoch 8] train_loss=1.6838, train_acc=0.3799, test_acc=0.4361
|
||||
[adam][standard][epoch 9] train_loss=1.6820, train_acc=0.3811, test_acc=0.4266
|
||||
[adam][standard][epoch 10] train_loss=1.6631, train_acc=0.3870, test_acc=0.4309
|
||||
[adam][standard][epoch 11] train_loss=1.6606, train_acc=0.3863, test_acc=0.4306
|
||||
[adam][standard][epoch 12] train_loss=1.6556, train_acc=0.3915, test_acc=0.4356
|
||||
[adam][standard][epoch 13] train_loss=1.6466, train_acc=0.3940, test_acc=0.4422
|
||||
[adam][standard][epoch 14] train_loss=1.6496, train_acc=0.3945, test_acc=0.4355
|
||||
[adam][standard][epoch 15] train_loss=1.6502, train_acc=0.3904, test_acc=0.4526
|
||||
[adam][standard][epoch 16] train_loss=1.6383, train_acc=0.3980, test_acc=0.4489
|
||||
[adam][standard][epoch 17] train_loss=1.6598, train_acc=0.3888, test_acc=0.4484
|
||||
[adam][standard][epoch 18] train_loss=1.6430, train_acc=0.3930, test_acc=0.3994
|
||||
[adam][standard][epoch 19] train_loss=1.6456, train_acc=0.3931, test_acc=0.4483
|
||||
[adam][standard][epoch 20] train_loss=1.6409, train_acc=0.3942, test_acc=0.4508
|
||||
[adam][aggressive][epoch 1] train_loss=2.0724, train_acc=0.2302, test_acc=0.3199
|
||||
[adam][aggressive][epoch 2] train_loss=1.9161, train_acc=0.2906, test_acc=0.3617
|
||||
[adam][aggressive][epoch 3] train_loss=1.8448, train_acc=0.3195, test_acc=0.3999
|
||||
[adam][aggressive][epoch 4] train_loss=1.8053, train_acc=0.3348, test_acc=0.4099
|
||||
[adam][aggressive][epoch 5] train_loss=1.7892, train_acc=0.3404, test_acc=0.4121
|
||||
[adam][aggressive][epoch 6] train_loss=1.7877, train_acc=0.3387, test_acc=0.3256
|
||||
[adam][aggressive][epoch 7] train_loss=1.7722, train_acc=0.3472, test_acc=0.4181
|
||||
[adam][aggressive][epoch 8] train_loss=1.7613, train_acc=0.3479, test_acc=0.3857
|
||||
[adam][aggressive][epoch 9] train_loss=1.7486, train_acc=0.3553, test_acc=0.3986
|
||||
[adam][aggressive][epoch 10] train_loss=1.7620, train_acc=0.3498, test_acc=0.3982
|
||||
[adam][aggressive][epoch 11] train_loss=1.7493, train_acc=0.3537, test_acc=0.4078
|
||||
[adam][aggressive][epoch 12] train_loss=1.7450, train_acc=0.3541, test_acc=0.4106
|
||||
[adam][aggressive][epoch 13] train_loss=1.7524, train_acc=0.3513, test_acc=0.4204
|
||||
[adam][aggressive][epoch 14] train_loss=1.7393, train_acc=0.3585, test_acc=0.4125
|
||||
[adam][aggressive][epoch 15] train_loss=1.7469, train_acc=0.3586, test_acc=0.3921
|
||||
[adam][aggressive][epoch 16] train_loss=1.7383, train_acc=0.3580, test_acc=0.3887
|
||||
[adam][aggressive][epoch 17] train_loss=1.7540, train_acc=0.3518, test_acc=0.3902
|
||||
[adam][aggressive][epoch 18] train_loss=1.7417, train_acc=0.3536, test_acc=0.4027
|
||||
[adam][aggressive][epoch 19] train_loss=1.7406, train_acc=0.3585, test_acc=0.4284
|
||||
[adam][aggressive][epoch 20] train_loss=1.7528, train_acc=0.3491, test_acc=0.4209
|
||||
saved results to results.json
|
||||
anova on test accuracy:
|
||||
sum_sq df F PR(>F)
|
||||
C(optimizer) 0.175350 1.0 541.527205 2.363959e-11
|
||||
C(augmentation) 0.015656 2.0 24.175125 6.180350e-05
|
||||
C(optimizer):C(augmentation) 0.007791 2.0 12.030388 1.357929e-03
|
||||
Residual 0.003886 12.0 NaN NaN
|
||||
saved plot to test_acc_comparison.png
|
||||
Message sent successfully!
|
||||
@@ -0,0 +1,200 @@
|
||||
[
|
||||
{
|
||||
"seed": 42,
|
||||
"optimizer": "sgd",
|
||||
"augmentation": "none",
|
||||
"test_acc": 0.7017,
|
||||
"robustness": {
|
||||
"0.1": 0.6874,
|
||||
"0.2": 0.6539,
|
||||
"0.3": 0.573
|
||||
}
|
||||
},
|
||||
{
|
||||
"seed": 42,
|
||||
"optimizer": "sgd",
|
||||
"augmentation": "standard",
|
||||
"test_acc": 0.6983,
|
||||
"robustness": {
|
||||
"0.1": 0.685,
|
||||
"0.2": 0.6393,
|
||||
"0.3": 0.5324
|
||||
}
|
||||
},
|
||||
{
|
||||
"seed": 42,
|
||||
"optimizer": "sgd",
|
||||
"augmentation": "aggressive",
|
||||
"test_acc": 0.6529,
|
||||
"robustness": {
|
||||
"0.1": 0.6441,
|
||||
"0.2": 0.5905,
|
||||
"0.3": 0.5073
|
||||
}
|
||||
},
|
||||
{
|
||||
"seed": 42,
|
||||
"optimizer": "adam",
|
||||
"augmentation": "none",
|
||||
"test_acc": 0.5754,
|
||||
"robustness": {
|
||||
"0.1": 0.5688,
|
||||
"0.2": 0.5225,
|
||||
"0.3": 0.461
|
||||
}
|
||||
},
|
||||
{
|
||||
"seed": 42,
|
||||
"optimizer": "adam",
|
||||
"augmentation": "standard",
|
||||
"test_acc": 0.5012,
|
||||
"robustness": {
|
||||
"0.1": 0.5008,
|
||||
"0.2": 0.4696,
|
||||
"0.3": 0.3933
|
||||
}
|
||||
},
|
||||
{
|
||||
"seed": 42,
|
||||
"optimizer": "adam",
|
||||
"augmentation": "aggressive",
|
||||
"test_acc": 0.4534,
|
||||
"robustness": {
|
||||
"0.1": 0.443,
|
||||
"0.2": 0.4074,
|
||||
"0.3": 0.3669
|
||||
}
|
||||
},
|
||||
{
|
||||
"seed": 123,
|
||||
"optimizer": "sgd",
|
||||
"augmentation": "none",
|
||||
"test_acc": 0.7018,
|
||||
"robustness": {
|
||||
"0.1": 0.6907,
|
||||
"0.2": 0.6513,
|
||||
"0.3": 0.5808
|
||||
}
|
||||
},
|
||||
{
|
||||
"seed": 123,
|
||||
"optimizer": "sgd",
|
||||
"augmentation": "standard",
|
||||
"test_acc": 0.6987,
|
||||
"robustness": {
|
||||
"0.1": 0.688,
|
||||
"0.2": 0.6378,
|
||||
"0.3": 0.5488
|
||||
}
|
||||
},
|
||||
{
|
||||
"seed": 123,
|
||||
"optimizer": "sgd",
|
||||
"augmentation": "aggressive",
|
||||
"test_acc": 0.6736,
|
||||
"robustness": {
|
||||
"0.1": 0.6591,
|
||||
"0.2": 0.6077,
|
||||
"0.3": 0.5265
|
||||
}
|
||||
},
|
||||
{
|
||||
"seed": 123,
|
||||
"optimizer": "adam",
|
||||
"augmentation": "none",
|
||||
"test_acc": 0.5414,
|
||||
"robustness": {
|
||||
"0.1": 0.5207,
|
||||
"0.2": 0.4721,
|
||||
"0.3": 0.3951
|
||||
}
|
||||
},
|
||||
{
|
||||
"seed": 123,
|
||||
"optimizer": "adam",
|
||||
"augmentation": "standard",
|
||||
"test_acc": 0.4439,
|
||||
"robustness": {
|
||||
"0.1": 0.4509,
|
||||
"0.2": 0.4256,
|
||||
"0.3": 0.3567
|
||||
}
|
||||
},
|
||||
{
|
||||
"seed": 123,
|
||||
"optimizer": "adam",
|
||||
"augmentation": "aggressive",
|
||||
"test_acc": 0.4519,
|
||||
"robustness": {
|
||||
"0.1": 0.4502,
|
||||
"0.2": 0.4266,
|
||||
"0.3": 0.3584
|
||||
}
|
||||
},
|
||||
{
|
||||
"seed": 999,
|
||||
"optimizer": "sgd",
|
||||
"augmentation": "none",
|
||||
"test_acc": 0.6778,
|
||||
"robustness": {
|
||||
"0.1": 0.669,
|
||||
"0.2": 0.6288,
|
||||
"0.3": 0.5506
|
||||
}
|
||||
},
|
||||
{
|
||||
"seed": 999,
|
||||
"optimizer": "sgd",
|
||||
"augmentation": "standard",
|
||||
"test_acc": 0.6961,
|
||||
"robustness": {
|
||||
"0.1": 0.6862,
|
||||
"0.2": 0.6491,
|
||||
"0.3": 0.5655
|
||||
}
|
||||
},
|
||||
{
|
||||
"seed": 999,
|
||||
"optimizer": "sgd",
|
||||
"augmentation": "aggressive",
|
||||
"test_acc": 0.6623,
|
||||
"robustness": {
|
||||
"0.1": 0.6504,
|
||||
"0.2": 0.5934,
|
||||
"0.3": 0.5163
|
||||
}
|
||||
},
|
||||
{
|
||||
"seed": 999,
|
||||
"optimizer": "adam",
|
||||
"augmentation": "none",
|
||||
"test_acc": 0.5477,
|
||||
"robustness": {
|
||||
"0.1": 0.5394,
|
||||
"0.2": 0.4983,
|
||||
"0.3": 0.4188
|
||||
}
|
||||
},
|
||||
{
|
||||
"seed": 999,
|
||||
"optimizer": "adam",
|
||||
"augmentation": "standard",
|
||||
"test_acc": 0.4508,
|
||||
"robustness": {
|
||||
"0.1": 0.4455,
|
||||
"0.2": 0.3987,
|
||||
"0.3": 0.308
|
||||
}
|
||||
},
|
||||
{
|
||||
"seed": 999,
|
||||
"optimizer": "adam",
|
||||
"augmentation": "aggressive",
|
||||
"test_acc": 0.4209,
|
||||
"robustness": {
|
||||
"0.1": 0.4268,
|
||||
"0.2": 0.4071,
|
||||
"0.3": 0.3368
|
||||
}
|
||||
}
|
||||
]
|
||||
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+31
-13
@@ -3,42 +3,58 @@ import json
|
||||
import pandas as pd
|
||||
import matplotlib.pyplot as plt
|
||||
|
||||
BASE_DIR = "./on_GPU"
|
||||
|
||||
# training diagnostics
|
||||
histories = []
|
||||
for csv in glob.glob("analytics/history_*.csv"):
|
||||
df = pd.read_csv(csv) # epochs × metrics
|
||||
for csv in glob.glob(f"{BASE_DIR}/analytics/history_*.csv"):
|
||||
df = pd.read_csv(csv) # epochs x metrics
|
||||
tag = "_".join(csv.split("_")[1:4]) # like sgd_none_42.csv
|
||||
df['condition'] = tag.replace(".csv", "")
|
||||
histories.append(df)
|
||||
|
||||
logs = pd.concat(histories, ignore_index=True)
|
||||
|
||||
# average across seeds, optimiser, augmentation for clarity
|
||||
mean_log = logs.groupby('epoch').mean(numeric_only=True)
|
||||
|
||||
plt.figure()
|
||||
plt.plot(mean_log.index, mean_log['train_acc'], label='train')
|
||||
plt.plot(mean_log.index, mean_log['test_acc'], label='validation')
|
||||
plt.plot(mean_log.index, mean_log['train_acc'],
|
||||
color='tab:blue', label='train')
|
||||
plt.plot(mean_log.index, mean_log['test_acc'],
|
||||
color='tab:orange', label='validation')
|
||||
plt.xlabel("epoch")
|
||||
plt.ylabel("accuracy")
|
||||
plt.legend()
|
||||
plt.grid(True)
|
||||
ax = plt.gca()
|
||||
ax.spines['top'].set_visible(False)
|
||||
ax.spines['right'].set_visible(False)
|
||||
plt.tight_layout()
|
||||
plt.savefig("train_val_accuracy.png")
|
||||
plt.savefig(f"{BASE_DIR}/train_val_accuracy.png")
|
||||
|
||||
# Plot train vs validation loss
|
||||
plt.figure()
|
||||
plt.plot(mean_log.index, mean_log['train_loss'], label='train')
|
||||
plt.plot(mean_log.index, mean_log['test_loss'], label='validation')
|
||||
plt.plot(mean_log.index, mean_log['train_loss'],
|
||||
color='tab:blue', label='train')
|
||||
plt.plot(mean_log.index, mean_log['test_loss'],
|
||||
color='tab:orange', label='validation')
|
||||
plt.xlabel("epoch")
|
||||
plt.ylabel("cross‑entropy loss")
|
||||
plt.legend()
|
||||
plt.grid(True)
|
||||
ax = plt.gca()
|
||||
ax.spines['top'].set_visible(False)
|
||||
ax.spines['right'].set_visible(False)
|
||||
plt.tight_layout()
|
||||
plt.savefig("train_val_loss.png")
|
||||
plt.savefig(f"{BASE_DIR}/train_val_loss.png")
|
||||
|
||||
# robustness curves
|
||||
with open("results.json") as f:
|
||||
with open(f"{BASE_DIR}/results.json") as f:
|
||||
res = json.load(f)
|
||||
|
||||
df = pd.DataFrame(res)
|
||||
records = [] # one row per sigma
|
||||
records = [] # one row per sigma
|
||||
|
||||
for _, row in df.iterrows():
|
||||
for sigma, acc in row['robustness'].items():
|
||||
@@ -52,11 +68,13 @@ for _, row in df.iterrows():
|
||||
rob_df = pd.DataFrame(records)
|
||||
pivot = rob_df.groupby(['optimizer', 'sigma']).acc.mean().unstack(0)
|
||||
|
||||
# sigma on x‑axis, one line per optimiser
|
||||
pivot.plot(marker='o')
|
||||
ax = pivot.plot(marker='o', linestyle='-', color=['#0072B2', '#D55E00'])
|
||||
plt.xlabel("Gaussian noise sigma")
|
||||
plt.ylabel("accuracy")
|
||||
plt.title("Noise robustness")
|
||||
plt.grid(True)
|
||||
ax.spines['top'].set_visible(False)
|
||||
ax.spines['right'].set_visible(False)
|
||||
plt.tight_layout()
|
||||
plt.savefig("robustness_curve.png")
|
||||
plt.savefig(f"{BASE_DIR}/robustness_curve.png")
|
||||
print("saved robustness_curve.png")
|
||||
|
||||
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|
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@@ -0,0 +1,16 @@
|
||||
import torchvision, torch, random
|
||||
from torchvision import transforms
|
||||
import matplotlib.pyplot as plt
|
||||
|
||||
clean_tf = transforms.ToTensor();
|
||||
noise = lambda x,s: torch.clamp(x + s*torch.randn_like(x),0,1);
|
||||
|
||||
ds = torchvision.datasets.CIFAR10('data',train=False,download=True,transform=clean_tf);
|
||||
idxs = random.sample(range(len(ds)),3);
|
||||
sigmas = [0.0,0.1,0.2,0.3];
|
||||
|
||||
# fuzzy!
|
||||
for k in idxs:
|
||||
img,_ = ds[k];
|
||||
grid = torch.stack([noise(img,s) for s in sigmas]);
|
||||
torchvision.utils.save_image(grid, f'example_{k}.png', nrow=len(sigmas));
|
||||
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Reference in New Issue
Block a user