slurm-1862427.out

INFO:root:called-params cls_configs/cls-in100-multi.yaml
INFO:root:loaded params....
{   'data': {   'batch_size': 128,
                'crop_size': 224,
                'model_name': 'vit_base',
                'num_classes': 100,
                'patch_size': 16,
                'probe_checkpoints': True,
                'probe_prefix': 'jepa_in100',
                'train_dataset_path': 'datasets/imagenet100/train',
                'val_dataset_path': 'datasets/imagenet100/val'},
    'logging': {   'checkpoint_freq': 1000,
                   'eval_output': 'ocls-jepa-in100-l2-ep600-seed0.out',
                   'log_dir': 'logs_IN100/in100-vitb-l2-ep600-seed0/',
                   'log_file': 'stats-in100-l2-ep600-seed0.csv',
                   'save_path': 'classifiers/jepa-stl-l2-ep600-seed0-classifier-pretrained-vitb'},
    'meta': {'device': 'cuda:0'},
    'multi_probing': ['logs_IN100/in100-vitb-l2-ep600-seed0-fulllr/'],
    'optimization': {   'epochs': 200,
                        'lr': 0.001,
                        'use_last_n_blocks': 1,
                        'use_normalization': False}}
INFO:root:working on file logs_IN100/in100-vitb-l2-ep600-seed0-fulllr/jepa_in100-ep300.pth.tar ...
Directory logs_IN100/in100-vitb-l2-ep600-seed0-fulllr/classifiers for saving the classifiers is now present
VisionTransformer(
  (patch_embed): PatchEmbed(
    (proj): Conv2d(3, 768, kernel_size=(16, 16), stride=(16, 16))
  )
  (blocks): ModuleList(
    (0-11): 12 x Block(
      (norm1): LayerNorm((768,), eps=1e-06, elementwise_affine=True)
      (attn): Attention(
        (qkv): Linear(in_features=768, out_features=2304, bias=True)
        (attn_drop): Dropout(p=0.0, inplace=False)
        (proj): Linear(in_features=768, out_features=768, bias=True)
        (proj_drop): Dropout(p=0.0, inplace=False)
      )
      (drop_path): Identity()
      (norm2): LayerNorm((768,), eps=1e-06, elementwise_affine=True)
      (mlp): MLP(
        (fc1): Linear(in_features=768, out_features=3072, bias=True)
        (act): GELU(approximate='none')
        (fc2): Linear(in_features=3072, out_features=768, bias=True)
        (drop): Dropout(p=0.0, inplace=False)
      )
    )
  )
  (norm): LayerNorm((768,), eps=1e-06, elementwise_affine=True)
)
Extracting features and saving them in memory..
Extracting features...
Epoch: 1/200 Train accuracy: 4.57808e-01 Validation accuracy: 4.92600e-01 Training loss 1.78053e-02 Validation loss 1.65053e-02 Time taken: 1.85 seconds 
Epoch: 2/200 Train accuracy: 5.81169e-01 Validation accuracy: 5.09000e-01 Training loss 1.26351e-02 Validation loss 1.51965e-02 Time taken: 2.27 seconds 
Epoch: 3/200 Train accuracy: 6.07900e-01 Validation accuracy: 5.33400e-01 Training loss 1.16011e-02 Validation loss 1.46716e-02 Time taken: 1.70 seconds 
Epoch: 4/200 Train accuracy: 6.25262e-01 Validation accuracy: 5.36000e-01 Training loss 1.10231e-02 Validation loss 1.44369e-02 Time taken: 1.65 seconds 
Epoch: 5/200 Train accuracy: 6.37308e-01 Validation accuracy: 5.41400e-01 Training loss 1.06282e-02 Validation loss 1.42139e-02 Time taken: 1.65 seconds 
Epoch: 6/200 Train accuracy: 6.45377e-01 Validation accuracy: 5.47400e-01 Training loss 1.03500e-02 Validation loss 1.41510e-02 Time taken: 1.65 seconds 
Epoch: 7/200 Train accuracy: 6.51308e-01 Validation accuracy: 5.45600e-01 Training loss 1.01163e-02 Validation loss 1.41560e-02 Time taken: 1.65 seconds 
Epoch: 8/200 Train accuracy: 6.58308e-01 Validation accuracy: 5.52000e-01 Training loss 9.92869e-03 Validation loss 1.39124e-02 Time taken: 1.65 seconds 
Epoch: 9/200 Train accuracy: 6.60646e-01 Validation accuracy: 5.52200e-01 Training loss 9.77862e-03 Validation loss 1.39715e-02 Time taken: 1.65 seconds 
Epoch: 10/200 Train accuracy: 6.64508e-01 Validation accuracy: 5.57000e-01 Training loss 9.64620e-03 Validation loss 1.38485e-02 Time taken: 1.65 seconds 
Epoch: 11/200 Train accuracy: 6.68315e-01 Validation accuracy: 5.56600e-01 Training loss 9.52860e-03 Validation loss 1.40019e-02 Time taken: 1.66 seconds 
Epoch: 12/200 Train accuracy: 6.71431e-01 Validation accuracy: 5.56600e-01 Training loss 9.42913e-03 Validation loss 1.37774e-02 Time taken: 1.93 seconds 
Epoch: 13/200 Train accuracy: 6.73485e-01 Validation accuracy: 5.60400e-01 Training loss 9.34575e-03 Validation loss 1.38257e-02 Time taken: 1.67 seconds 
Epoch: 14/200 Train accuracy: 6.75862e-01 Validation accuracy: 5.61000e-01 Training loss 9.26356e-03 Validation loss 1.37514e-02 Time taken: 1.67 seconds 
Epoch: 15/200 Train accuracy: 6.78262e-01 Validation accuracy: 5.57600e-01 Training loss 9.19253e-03 Validation loss 1.37839e-02 Time taken: 1.66 seconds 
Epoch: 16/200 Train accuracy: 6.80315e-01 Validation accuracy: 5.60800e-01 Training loss 9.12562e-03 Validation loss 1.37965e-02 Time taken: 1.67 seconds 
Epoch: 17/200 Train accuracy: 6.82292e-01 Validation accuracy: 5.64800e-01 Training loss 9.06018e-03 Validation loss 1.37250e-02 Time taken: 1.67 seconds 
Epoch: 18/200 Train accuracy: 6.82777e-01 Validation accuracy: 5.59200e-01 Training loss 9.01136e-03 Validation loss 1.39250e-02 Time taken: 1.66 seconds 
Epoch: 19/200 Train accuracy: 6.84792e-01 Validation accuracy: 5.61400e-01 Training loss 8.96555e-03 Validation loss 1.36725e-02 Time taken: 1.72 seconds 
Epoch: 20/200 Train accuracy: 6.86108e-01 Validation accuracy: 5.60000e-01 Training loss 8.92026e-03 Validation loss 1.37543e-02 Time taken: 1.69 seconds 
Epoch: 21/200 Train accuracy: 6.87392e-01 Validation accuracy: 5.61600e-01 Training loss 8.87534e-03 Validation loss 1.37847e-02 Time taken: 1.70 seconds 
Epoch: 22/200 Train accuracy: 6.88638e-01 Validation accuracy: 5.64000e-01 Training loss 8.83243e-03 Validation loss 1.37845e-02 Time taken: 1.66 seconds 
Epoch: 23/200 Train accuracy: 6.89746e-01 Validation accuracy: 5.66800e-01 Training loss 8.79884e-03 Validation loss 1.38119e-02 Time taken: 1.66 seconds 
Epoch: 24/200 Train accuracy: 6.90308e-01 Validation accuracy: 5.61000e-01 Training loss 8.76753e-03 Validation loss 1.37861e-02 Time taken: 1.66 seconds 
Epoch: 25/200 Train accuracy: 6.91377e-01 Validation accuracy: 5.62600e-01 Training loss 8.73429e-03 Validation loss 1.38129e-02 Time taken: 1.66 seconds 
Epoch: 26/200 Train accuracy: 6.92762e-01 Validation accuracy: 5.63400e-01 Training loss 8.69964e-03 Validation loss 1.37797e-02 Time taken: 1.66 seconds 
Epoch: 27/200 Train accuracy: 6.94069e-01 Validation accuracy: 5.67000e-01 Training loss 8.67347e-03 Validation loss 1.37588e-02 Time taken: 1.66 seconds 
Epoch: 28/200 Train accuracy: 6.93931e-01 Validation accuracy: 5.62000e-01 Training loss 8.64857e-03 Validation loss 1.37809e-02 Time taken: 1.66 seconds 
Epoch: 29/200 Train accuracy: 6.96346e-01 Validation accuracy: 5.61800e-01 Training loss 8.61595e-03 Validation loss 1.37687e-02 Time taken: 1.66 seconds 
Epoch: 30/200 Train accuracy: 6.95885e-01 Validation accuracy: 5.60400e-01 Training loss 8.59477e-03 Validation loss 1.38423e-02 Time taken: 1.77 seconds 
Epoch: 31/200 Train accuracy: 6.96077e-01 Validation accuracy: 5.62600e-01 Training loss 8.57420e-03 Validation loss 1.37693e-02 Time taken: 1.70 seconds 
Epoch: 32/200 Train accuracy: 6.97069e-01 Validation accuracy: 5.63800e-01 Training loss 8.54605e-03 Validation loss 1.37892e-02 Time taken: 1.66 seconds 
Epoch: 33/200 Train accuracy: 6.97992e-01 Validation accuracy: 5.62400e-01 Training loss 8.53065e-03 Validation loss 1.38239e-02 Time taken: 1.66 seconds 
Epoch: 34/200 Train accuracy: 6.99131e-01 Validation accuracy: 5.60200e-01 Training loss 8.50514e-03 Validation loss 1.38397e-02 Time taken: 1.67 seconds 
Epoch: 35/200 Train accuracy: 6.98562e-01 Validation accuracy: 5.63600e-01 Training loss 8.48860e-03 Validation loss 1.37440e-02 Time taken: 1.67 seconds 
Epoch: 36/200 Train accuracy: 6.99869e-01 Validation accuracy: 5.63600e-01 Training loss 8.47282e-03 Validation loss 1.38375e-02 Time taken: 1.67 seconds 
Epoch: 37/200 Train accuracy: 7.00138e-01 Validation accuracy: 5.64400e-01 Training loss 8.45990e-03 Validation loss 1.37645e-02 Time taken: 1.66 seconds 
Epoch: 38/200 Train accuracy: 7.00923e-01 Validation accuracy: 5.62800e-01 Training loss 8.44135e-03 Validation loss 1.37892e-02 Time taken: 1.66 seconds 
Epoch: 39/200 Train accuracy: 7.00900e-01 Validation accuracy: 5.61800e-01 Training loss 8.42773e-03 Validation loss 1.38381e-02 Time taken: 1.66 seconds 
Epoch: 40/200 Train accuracy: 7.02192e-01 Validation accuracy: 5.61600e-01 Training loss 8.40937e-03 Validation loss 1.38593e-02 Time taken: 1.66 seconds 
Epoch: 41/200 Train accuracy: 7.01177e-01 Validation accuracy: 5.67600e-01 Training loss 8.39469e-03 Validation loss 1.38385e-02 Time taken: 1.66 seconds 
Epoch: 42/200 Train accuracy: 7.02185e-01 Validation accuracy: 5.63200e-01 Training loss 8.38020e-03 Validation loss 1.38178e-02 Time taken: 1.66 seconds 
Epoch: 43/200 Train accuracy: 7.02769e-01 Validation accuracy: 5.63800e-01 Training loss 8.37363e-03 Validation loss 1.38917e-02 Time taken: 1.66 seconds 
Epoch: 44/200 Train accuracy: 7.02862e-01 Validation accuracy: 5.61000e-01 Training loss 8.35954e-03 Validation loss 1.38428e-02 Time taken: 1.66 seconds 
Epoch: 45/200 Train accuracy: 7.02862e-01 Validation accuracy: 5.62800e-01 Training loss 8.34459e-03 Validation loss 1.37962e-02 Time taken: 1.67 seconds 
Epoch: 46/200 Train accuracy: 7.03638e-01 Validation accuracy: 5.62600e-01 Training loss 8.33265e-03 Validation loss 1.39207e-02 Time taken: 1.67 seconds 
Epoch: 47/200 Train accuracy: 7.04631e-01 Validation accuracy: 5.61600e-01 Training loss 8.31362e-03 Validation loss 1.38407e-02 Time taken: 1.67 seconds 
Epoch: 48/200 Train accuracy: 7.04031e-01 Validation accuracy: 5.59200e-01 Training loss 8.30825e-03 Validation loss 1.39094e-02 Time taken: 1.73 seconds 
Epoch: 49/200 Train accuracy: 7.04531e-01 Validation accuracy: 5.64600e-01 Training loss 8.29997e-03 Validation loss 1.38834e-02 Time taken: 1.66 seconds 
Epoch: 50/200 Train accuracy: 7.04862e-01 Validation accuracy: 5.62800e-01 Training loss 8.29059e-03 Validation loss 1.38548e-02 Time taken: 1.67 seconds 
Epoch: 51/200 Train accuracy: 7.04469e-01 Validation accuracy: 5.62600e-01 Training loss 8.28234e-03 Validation loss 1.38568e-02 Time taken: 1.66 seconds 
Epoch: 52/200 Train accuracy: 7.05692e-01 Validation accuracy: 5.63400e-01 Training loss 8.27777e-03 Validation loss 1.39163e-02 Time taken: 1.67 seconds 
Epoch: 53/200 Train accuracy: 7.04700e-01 Validation accuracy: 5.60400e-01 Training loss 8.25810e-03 Validation loss 1.39167e-02 Time taken: 1.71 seconds 
Epoch: 54/200 Train accuracy: 7.05508e-01 Validation accuracy: 5.62400e-01 Training loss 8.25729e-03 Validation loss 1.39074e-02 Time taken: 1.68 seconds 
Epoch: 55/200 Train accuracy: 7.05577e-01 Validation accuracy: 5.62400e-01 Training loss 8.24519e-03 Validation loss 1.38631e-02 Time taken: 1.67 seconds 
Epoch: 56/200 Train accuracy: 7.05585e-01 Validation accuracy: 5.63400e-01 Training loss 8.23934e-03 Validation loss 1.39276e-02 Time taken: 1.67 seconds 
Epoch: 57/200 Train accuracy: 7.06985e-01 Validation accuracy: 5.60400e-01 Training loss 8.23246e-03 Validation loss 1.39842e-02 Time taken: 1.67 seconds 
Epoch: 58/200 Train accuracy: 7.06892e-01 Validation accuracy: 5.60400e-01 Training loss 8.22744e-03 Validation loss 1.39017e-02 Time taken: 1.67 seconds 
Epoch: 59/200 Train accuracy: 7.07615e-01 Validation accuracy: 5.65000e-01 Training loss 8.21850e-03 Validation loss 1.39064e-02 Time taken: 1.67 seconds 
Epoch: 60/200 Train accuracy: 7.07269e-01 Validation accuracy: 5.63200e-01 Training loss 8.20744e-03 Validation loss 1.38795e-02 Time taken: 1.67 seconds 
Epoch: 61/200 Train accuracy: 7.07462e-01 Validation accuracy: 5.62000e-01 Training loss 8.20270e-03 Validation loss 1.38605e-02 Time taken: 1.68 seconds 
Epoch: 62/200 Train accuracy: 7.07385e-01 Validation accuracy: 5.65600e-01 Training loss 8.19274e-03 Validation loss 1.38745e-02 Time taken: 1.67 seconds 
Epoch: 63/200 Train accuracy: 7.07869e-01 Validation accuracy: 5.63800e-01 Training loss 8.19542e-03 Validation loss 1.39380e-02 Time taken: 1.67 seconds 
Epoch: 64/200 Train accuracy: 7.08038e-01 Validation accuracy: 5.64000e-01 Training loss 8.18010e-03 Validation loss 1.38690e-02 Time taken: 1.67 seconds 
Epoch: 65/200 Train accuracy: 7.08100e-01 Validation accuracy: 5.61400e-01 Training loss 8.17620e-03 Validation loss 1.39533e-02 Time taken: 1.68 seconds 
Epoch: 66/200 Train accuracy: 7.08377e-01 Validation accuracy: 5.63800e-01 Training loss 8.16865e-03 Validation loss 1.39137e-02 Time taken: 1.67 seconds 
Epoch: 67/200 Train accuracy: 7.09192e-01 Validation accuracy: 5.64000e-01 Training loss 8.16664e-03 Validation loss 1.39131e-02 Time taken: 1.75 seconds 
Epoch: 68/200 Train accuracy: 7.08192e-01 Validation accuracy: 5.62800e-01 Training loss 8.15732e-03 Validation loss 1.39443e-02 Time taken: 1.67 seconds 
Epoch: 69/200 Train accuracy: 7.08462e-01 Validation accuracy: 5.64400e-01 Training loss 8.15426e-03 Validation loss 1.38734e-02 Time taken: 1.67 seconds 
Epoch: 70/200 Train accuracy: 7.08938e-01 Validation accuracy: 5.61800e-01 Training loss 8.14950e-03 Validation loss 1.38882e-02 Time taken: 1.68 seconds 
Epoch: 71/200 Train accuracy: 7.10654e-01 Validation accuracy: 5.62000e-01 Training loss 8.14238e-03 Validation loss 1.39256e-02 Time taken: 1.71 seconds 
Epoch: 72/200 Train accuracy: 7.09531e-01 Validation accuracy: 5.63800e-01 Training loss 8.13766e-03 Validation loss 1.39026e-02 Time taken: 1.68 seconds 
Epoch: 73/200 Train accuracy: 7.10877e-01 Validation accuracy: 5.64000e-01 Training loss 8.13160e-03 Validation loss 1.38813e-02 Time taken: 1.67 seconds 
Epoch: 74/200 Train accuracy: 7.10069e-01 Validation accuracy: 5.63600e-01 Training loss 8.13041e-03 Validation loss 1.39426e-02 Time taken: 1.67 seconds 
Epoch: 75/200 Train accuracy: 7.09015e-01 Validation accuracy: 5.62400e-01 Training loss 8.12307e-03 Validation loss 1.39839e-02 Time taken: 1.68 seconds 
Epoch: 76/200 Train accuracy: 7.10138e-01 Validation accuracy: 5.59600e-01 Training loss 8.11642e-03 Validation loss 1.39629e-02 Time taken: 1.67 seconds 
Epoch: 77/200 Train accuracy: 7.10300e-01 Validation accuracy: 5.64400e-01 Training loss 8.11500e-03 Validation loss 1.39440e-02 Time taken: 1.67 seconds 
Epoch: 78/200 Train accuracy: 7.10631e-01 Validation accuracy: 5.67200e-01 Training loss 8.11171e-03 Validation loss 1.39306e-02 Time taken: 1.67 seconds 
Epoch: 79/200 Train accuracy: 7.09469e-01 Validation accuracy: 5.61200e-01 Training loss 8.10591e-03 Validation loss 1.40014e-02 Time taken: 1.67 seconds 
Epoch: 80/200 Train accuracy: 7.09569e-01 Validation accuracy: 5.64000e-01 Training loss 8.10194e-03 Validation loss 1.40047e-02 Time taken: 1.67 seconds 
Epoch: 81/200 Train accuracy: 7.10423e-01 Validation accuracy: 5.59000e-01 Training loss 8.10448e-03 Validation loss 1.39388e-02 Time taken: 1.69 seconds 
Epoch: 82/200 Train accuracy: 7.10754e-01 Validation accuracy: 5.66000e-01 Training loss 8.09535e-03 Validation loss 1.39229e-02 Time taken: 1.67 seconds 
Epoch: 83/200 Train accuracy: 7.10492e-01 Validation accuracy: 5.65200e-01 Training loss 8.09643e-03 Validation loss 1.39240e-02 Time taken: 1.67 seconds 
Epoch: 84/200 Train accuracy: 7.10362e-01 Validation accuracy: 5.61800e-01 Training loss 8.09217e-03 Validation loss 1.39648e-02 Time taken: 1.67 seconds 
Epoch: 85/200 Train accuracy: 7.10785e-01 Validation accuracy: 5.61800e-01 Training loss 8.08765e-03 Validation loss 1.39387e-02 Time taken: 1.68 seconds 
Epoch: 86/200 Train accuracy: 7.10292e-01 Validation accuracy: 5.63800e-01 Training loss 8.08778e-03 Validation loss 1.39628e-02 Time taken: 1.67 seconds 
Epoch: 87/200 Train accuracy: 7.11238e-01 Validation accuracy: 5.63600e-01 Training loss 8.07773e-03 Validation loss 1.38718e-02 Time taken: 1.67 seconds 
Epoch: 88/200 Train accuracy: 7.12000e-01 Validation accuracy: 5.66800e-01 Training loss 8.07820e-03 Validation loss 1.38849e-02 Time taken: 1.67 seconds 
Epoch: 89/200 Train accuracy: 7.10638e-01 Validation accuracy: 5.66400e-01 Training loss 8.07879e-03 Validation loss 1.38497e-02 Time taken: 1.69 seconds 
Epoch: 90/200 Train accuracy: 7.11123e-01 Validation accuracy: 5.60200e-01 Training loss 8.07354e-03 Validation loss 1.39790e-02 Time taken: 1.68 seconds 
Epoch: 91/200 Train accuracy: 7.11323e-01 Validation accuracy: 5.65800e-01 Training loss 8.06661e-03 Validation loss 1.39943e-02 Time taken: 1.68 seconds 
Epoch: 92/200 Train accuracy: 7.12362e-01 Validation accuracy: 5.65600e-01 Training loss 8.06848e-03 Validation loss 1.39020e-02 Time taken: 1.68 seconds 
Epoch: 93/200 Train accuracy: 7.11615e-01 Validation accuracy: 5.63600e-01 Training loss 8.05914e-03 Validation loss 1.38852e-02 Time taken: 1.67 seconds 
Epoch: 94/200 Train accuracy: 7.11362e-01 Validation accuracy: 5.68000e-01 Training loss 8.05908e-03 Validation loss 1.39454e-02 Time taken: 1.68 seconds 
Epoch: 95/200 Train accuracy: 7.10754e-01 Validation accuracy: 5.61600e-01 Training loss 8.05799e-03 Validation loss 1.40028e-02 Time taken: 1.73 seconds 
Epoch: 96/200 Train accuracy: 7.11508e-01 Validation accuracy: 5.63800e-01 Training loss 8.06012e-03 Validation loss 1.38786e-02 Time taken: 1.67 seconds 
Epoch: 97/200 Train accuracy: 7.11592e-01 Validation accuracy: 5.61800e-01 Training loss 8.05724e-03 Validation loss 1.40153e-02 Time taken: 1.68 seconds 
Epoch: 98/200 Train accuracy: 7.11900e-01 Validation accuracy: 5.67600e-01 Training loss 8.04517e-03 Validation loss 1.39347e-02 Time taken: 1.67 seconds 
Epoch: 99/200 Train accuracy: 7.11454e-01 Validation accuracy: 5.64600e-01 Training loss 8.04799e-03 Validation loss 1.39970e-02 Time taken: 1.68 seconds 
Epoch: 100/200 Train accuracy: 7.12254e-01 Validation accuracy: 5.62800e-01 Training loss 8.04798e-03 Validation loss 1.40595e-02 Time taken: 1.73 seconds 
Epoch: 101/200 Train accuracy: 7.12608e-01 Validation accuracy: 5.61000e-01 Training loss 8.04497e-03 Validation loss 1.39780e-02 Time taken: 1.68 seconds 
Epoch: 102/200 Train accuracy: 7.12192e-01 Validation accuracy: 5.64600e-01 Training loss 8.04582e-03 Validation loss 1.40296e-02 Time taken: 1.68 seconds 
Epoch: 103/200 Train accuracy: 7.12031e-01 Validation accuracy: 5.61800e-01 Training loss 8.03810e-03 Validation loss 1.40427e-02 Time taken: 1.68 seconds 
Epoch: 104/200 Train accuracy: 7.11785e-01 Validation accuracy: 5.63600e-01 Training loss 8.03739e-03 Validation loss 1.39465e-02 Time taken: 1.68 seconds 
Epoch: 105/200 Train accuracy: 7.12369e-01 Validation accuracy: 5.63800e-01 Training loss 8.03198e-03 Validation loss 1.40181e-02 Time taken: 1.67 seconds 
Epoch: 106/200 Train accuracy: 7.12185e-01 Validation accuracy: 5.62200e-01 Training loss 8.03749e-03 Validation loss 1.40040e-02 Time taken: 1.67 seconds 
Epoch: 107/200 Train accuracy: 7.12838e-01 Validation accuracy: 5.62000e-01 Training loss 8.03390e-03 Validation loss 1.40038e-02 Time taken: 1.67 seconds 
Epoch: 108/200 Train accuracy: 7.12454e-01 Validation accuracy: 5.63800e-01 Training loss 8.02632e-03 Validation loss 1.39334e-02 Time taken: 1.68 seconds 
Epoch: 109/200 Train accuracy: 7.12615e-01 Validation accuracy: 5.61600e-01 Training loss 8.02989e-03 Validation loss 1.40188e-02 Time taken: 1.67 seconds 
Epoch: 110/200 Train accuracy: 7.12754e-01 Validation accuracy: 5.62200e-01 Training loss 8.02100e-03 Validation loss 1.40302e-02 Time taken: 1.70 seconds 
Epoch: 111/200 Train accuracy: 7.12485e-01 Validation accuracy: 5.64400e-01 Training loss 8.02875e-03 Validation loss 1.39917e-02 Time taken: 1.67 seconds 
Epoch: 112/200 Train accuracy: 7.13600e-01 Validation accuracy: 5.60800e-01 Training loss 8.02327e-03 Validation loss 1.39886e-02 Time taken: 1.67 seconds 
Epoch: 113/200 Train accuracy: 7.13077e-01 Validation accuracy: 5.63600e-01 Training loss 8.02336e-03 Validation loss 1.39512e-02 Time taken: 1.67 seconds 
Epoch: 114/200 Train accuracy: 7.13354e-01 Validation accuracy: 5.58800e-01 Training loss 8.01462e-03 Validation loss 1.39982e-02 Time taken: 1.67 seconds 
Epoch: 115/200 Train accuracy: 7.12177e-01 Validation accuracy: 5.65800e-01 Training loss 8.02080e-03 Validation loss 1.40136e-02 Time taken: 1.67 seconds 
Epoch: 116/200 Train accuracy: 7.13646e-01 Validation accuracy: 5.63600e-01 Training loss 8.01616e-03 Validation loss 1.39550e-02 Time taken: 1.67 seconds 
Epoch: 117/200 Train accuracy: 7.13438e-01 Validation accuracy: 5.62400e-01 Training loss 8.01873e-03 Validation loss 1.39935e-02 Time taken: 1.68 seconds 
Epoch: 118/200 Train accuracy: 7.13792e-01 Validation accuracy: 5.59600e-01 Training loss 8.01366e-03 Validation loss 1.39671e-02 Time taken: 1.68 seconds 
Epoch: 119/200 Train accuracy: 7.13277e-01 Validation accuracy: 5.61000e-01 Training loss 8.00892e-03 Validation loss 1.40330e-02 Time taken: 1.67 seconds 
Epoch: 120/200 Train accuracy: 7.12992e-01 Validation accuracy: 5.65000e-01 Training loss 8.00480e-03 Validation loss 1.39784e-02 Time taken: 1.69 seconds 
Epoch: 121/200 Train accuracy: 7.13746e-01 Validation accuracy: 5.61000e-01 Training loss 8.00852e-03 Validation loss 1.39900e-02 Time taken: 1.68 seconds 
Epoch: 122/200 Train accuracy: 7.13346e-01 Validation accuracy: 5.62600e-01 Training loss 8.00616e-03 Validation loss 1.40057e-02 Time taken: 1.68 seconds 
Epoch: 123/200 Train accuracy: 7.13685e-01 Validation accuracy: 5.61200e-01 Training loss 8.01017e-03 Validation loss 1.39029e-02 Time taken: 1.68 seconds 
Epoch: 124/200 Train accuracy: 7.13277e-01 Validation accuracy: 5.67400e-01 Training loss 8.01100e-03 Validation loss 1.39307e-02 Time taken: 1.68 seconds 
Epoch: 125/200 Train accuracy: 7.13700e-01 Validation accuracy: 5.59000e-01 Training loss 8.00370e-03 Validation loss 1.40152e-02 Time taken: 1.73 seconds 
Epoch: 126/200 Train accuracy: 7.12892e-01 Validation accuracy: 5.62400e-01 Training loss 8.00623e-03 Validation loss 1.39621e-02 Time taken: 1.71 seconds 
Epoch: 127/200 Train accuracy: 7.14338e-01 Validation accuracy: 5.64400e-01 Training loss 8.00182e-03 Validation loss 1.40133e-02 Time taken: 1.67 seconds 
Epoch: 128/200 Train accuracy: 7.12785e-01 Validation accuracy: 5.62000e-01 Training loss 7.99815e-03 Validation loss 1.39472e-02 Time taken: 1.68 seconds 
Epoch: 129/200 Train accuracy: 7.13738e-01 Validation accuracy: 5.64600e-01 Training loss 7.99669e-03 Validation loss 1.40655e-02 Time taken: 1.68 seconds 
Epoch: 130/200 Train accuracy: 7.13292e-01 Validation accuracy: 5.64800e-01 Training loss 7.99022e-03 Validation loss 1.39458e-02 Time taken: 1.83 seconds 
Epoch: 131/200 Train accuracy: 7.13662e-01 Validation accuracy: 5.63400e-01 Training loss 7.99867e-03 Validation loss 1.39919e-02 Time taken: 2.11 seconds 
Epoch: 132/200 Train accuracy: 7.13715e-01 Validation accuracy: 5.59400e-01 Training loss 7.99652e-03 Validation loss 1.40304e-02 Time taken: 1.64 seconds 
Epoch: 133/200 Train accuracy: 7.14123e-01 Validation accuracy: 5.62400e-01 Training loss 7.99581e-03 Validation loss 1.39726e-02 Time taken: 1.64 seconds 
Epoch: 134/200 Train accuracy: 7.13585e-01 Validation accuracy: 5.65400e-01 Training loss 7.99308e-03 Validation loss 1.39334e-02 Time taken: 1.65 seconds 
Epoch: 135/200 Train accuracy: 7.14215e-01 Validation accuracy: 5.61000e-01 Training loss 7.99742e-03 Validation loss 1.39630e-02 Time taken: 1.73 seconds 
Epoch: 136/200 Train accuracy: 7.13731e-01 Validation accuracy: 5.64000e-01 Training loss 7.99418e-03 Validation loss 1.40077e-02 Time taken: 1.67 seconds 
Epoch: 137/200 Train accuracy: 7.13385e-01 Validation accuracy: 5.56200e-01 Training loss 7.98822e-03 Validation loss 1.40896e-02 Time taken: 1.65 seconds 
Epoch: 138/200 Train accuracy: 7.14523e-01 Validation accuracy: 5.60400e-01 Training loss 7.98614e-03 Validation loss 1.39713e-02 Time taken: 1.65 seconds 
Epoch: 139/200 Train accuracy: 7.13231e-01 Validation accuracy: 5.61600e-01 Training loss 7.99033e-03 Validation loss 1.39948e-02 Time taken: 1.65 seconds 
Epoch: 140/200 Train accuracy: 7.13638e-01 Validation accuracy: 5.62000e-01 Training loss 7.98484e-03 Validation loss 1.41351e-02 Time taken: 1.66 seconds 
Epoch: 141/200 Train accuracy: 7.13608e-01 Validation accuracy: 5.60800e-01 Training loss 7.98759e-03 Validation loss 1.40037e-02 Time taken: 1.66 seconds 
Epoch: 142/200 Train accuracy: 7.13715e-01 Validation accuracy: 5.68200e-01 Training loss 7.98502e-03 Validation loss 1.39951e-02 Time taken: 1.68 seconds 
Epoch: 143/200 Train accuracy: 7.14408e-01 Validation accuracy: 5.59800e-01 Training loss 7.98862e-03 Validation loss 1.40015e-02 Time taken: 1.67 seconds 
Epoch: 144/200 Train accuracy: 7.14154e-01 Validation accuracy: 5.58200e-01 Training loss 7.98390e-03 Validation loss 1.40645e-02 Time taken: 1.66 seconds 
Epoch: 145/200 Train accuracy: 7.13700e-01 Validation accuracy: 5.60400e-01 Training loss 7.98145e-03 Validation loss 1.40731e-02 Time taken: 1.67 seconds 
Epoch: 146/200 Train accuracy: 7.14092e-01 Validation accuracy: 5.60800e-01 Training loss 7.98277e-03 Validation loss 1.40279e-02 Time taken: 1.67 seconds 
Epoch: 147/200 Train accuracy: 7.13546e-01 Validation accuracy: 5.63000e-01 Training loss 7.98620e-03 Validation loss 1.41066e-02 Time taken: 1.67 seconds 
Epoch: 148/200 Train accuracy: 7.13908e-01 Validation accuracy: 5.65400e-01 Training loss 7.98387e-03 Validation loss 1.40196e-02 Time taken: 1.67 seconds 
Epoch: 149/200 Train accuracy: 7.14623e-01 Validation accuracy: 5.63400e-01 Training loss 7.98407e-03 Validation loss 1.41034e-02 Time taken: 1.67 seconds 
Epoch: 150/200 Train accuracy: 7.14462e-01 Validation accuracy: 5.65200e-01 Training loss 7.97790e-03 Validation loss 1.40098e-02 Time taken: 1.68 seconds 
Epoch: 151/200 Train accuracy: 7.13954e-01 Validation accuracy: 5.59600e-01 Training loss 7.97972e-03 Validation loss 1.40408e-02 Time taken: 1.88 seconds 
Epoch: 152/200 Train accuracy: 7.14454e-01 Validation accuracy: 5.65000e-01 Training loss 7.97465e-03 Validation loss 1.39515e-02 Time taken: 1.69 seconds 
Epoch: 153/200 Train accuracy: 7.14254e-01 Validation accuracy: 5.64600e-01 Training loss 7.98393e-03 Validation loss 1.40307e-02 Time taken: 1.68 seconds 
Epoch: 154/200 Train accuracy: 7.14515e-01 Validation accuracy: 5.67800e-01 Training loss 7.97826e-03 Validation loss 1.39687e-02 Time taken: 1.68 seconds 
Epoch: 155/200 Train accuracy: 7.14492e-01 Validation accuracy: 5.62800e-01 Training loss 7.96927e-03 Validation loss 1.39595e-02 Time taken: 1.67 seconds 
Epoch: 156/200 Train accuracy: 7.13677e-01 Validation accuracy: 5.65600e-01 Training loss 7.97398e-03 Validation loss 1.40047e-02 Time taken: 1.68 seconds 
Epoch: 157/200 Train accuracy: 7.14700e-01 Validation accuracy: 5.59200e-01 Training loss 7.97472e-03 Validation loss 1.41053e-02 Time taken: 1.67 seconds 
Epoch: 158/200 Train accuracy: 7.14362e-01 Validation accuracy: 5.65200e-01 Training loss 7.97774e-03 Validation loss 1.39461e-02 Time taken: 1.68 seconds 
Epoch: 159/200 Train accuracy: 7.14215e-01 Validation accuracy: 5.60200e-01 Training loss 7.97321e-03 Validation loss 1.40247e-02 Time taken: 1.69 seconds 
Epoch: 160/200 Train accuracy: 7.13623e-01 Validation accuracy: 5.61800e-01 Training loss 7.97313e-03 Validation loss 1.40501e-02 Time taken: 1.78 seconds 
Epoch: 161/200 Train accuracy: 7.14215e-01 Validation accuracy: 5.65600e-01 Training loss 7.97885e-03 Validation loss 1.40286e-02 Time taken: 1.69 seconds 
Epoch: 162/200 Train accuracy: 7.14469e-01 Validation accuracy: 5.64800e-01 Training loss 7.96624e-03 Validation loss 1.39927e-02 Time taken: 1.68 seconds 
Epoch: 163/200 Train accuracy: 7.14323e-01 Validation accuracy: 5.63000e-01 Training loss 7.97195e-03 Validation loss 1.39920e-02 Time taken: 1.67 seconds 
Epoch: 164/200 Train accuracy: 7.14177e-01 Validation accuracy: 5.65200e-01 Training loss 7.97019e-03 Validation loss 1.39517e-02 Time taken: 1.67 seconds 
Epoch: 165/200 Train accuracy: 7.13977e-01 Validation accuracy: 5.63000e-01 Training loss 7.96751e-03 Validation loss 1.39695e-02 Time taken: 1.68 seconds 
Epoch: 166/200 Train accuracy: 7.14200e-01 Validation accuracy: 5.59600e-01 Training loss 7.96740e-03 Validation loss 1.40722e-02 Time taken: 1.78 seconds 
Epoch: 167/200 Train accuracy: 7.14885e-01 Validation accuracy: 5.62000e-01 Training loss 7.96327e-03 Validation loss 1.40080e-02 Time taken: 1.71 seconds 
Epoch: 168/200 Train accuracy: 7.14285e-01 Validation accuracy: 5.60400e-01 Training loss 7.97180e-03 Validation loss 1.40212e-02 Time taken: 1.68 seconds 
Epoch: 169/200 Train accuracy: 7.14323e-01 Validation accuracy: 5.61200e-01 Training loss 7.96448e-03 Validation loss 1.40851e-02 Time taken: 1.68 seconds 
Epoch: 170/200 Train accuracy: 7.14531e-01 Validation accuracy: 5.63000e-01 Training loss 7.96606e-03 Validation loss 1.40670e-02 Time taken: 1.68 seconds 
Epoch: 171/200 Train accuracy: 7.13946e-01 Validation accuracy: 5.60200e-01 Training loss 7.96738e-03 Validation loss 1.40851e-02 Time taken: 1.68 seconds 
Epoch: 172/200 Train accuracy: 7.14277e-01 Validation accuracy: 5.60200e-01 Training loss 7.96800e-03 Validation loss 1.40044e-02 Time taken: 1.68 seconds 
Epoch: 173/200 Train accuracy: 7.14654e-01 Validation accuracy: 5.62400e-01 Training loss 7.96490e-03 Validation loss 1.40802e-02 Time taken: 1.68 seconds 
Epoch: 174/200 Train accuracy: 7.14277e-01 Validation accuracy: 5.66400e-01 Training loss 7.96666e-03 Validation loss 1.39918e-02 Time taken: 1.68 seconds 
Epoch: 175/200 Train accuracy: 7.14562e-01 Validation accuracy: 5.63800e-01 Training loss 7.96590e-03 Validation loss 1.39545e-02 Time taken: 1.68 seconds 
Epoch: 176/200 Train accuracy: 7.14000e-01 Validation accuracy: 5.62800e-01 Training loss 7.96247e-03 Validation loss 1.40078e-02 Time taken: 1.68 seconds 
Epoch: 177/200 Train accuracy: 7.14846e-01 Validation accuracy: 5.64000e-01 Training loss 7.96367e-03 Validation loss 1.40881e-02 Time taken: 1.68 seconds 
Epoch: 178/200 Train accuracy: 7.14823e-01 Validation accuracy: 5.62000e-01 Training loss 7.96014e-03 Validation loss 1.39782e-02 Time taken: 1.67 seconds 
Epoch: 179/200 Train accuracy: 7.14223e-01 Validation accuracy: 5.66400e-01 Training loss 7.96336e-03 Validation loss 1.40021e-02 Time taken: 1.68 seconds 
Epoch: 180/200 Train accuracy: 7.14692e-01 Validation accuracy: 5.62200e-01 Training loss 7.96614e-03 Validation loss 1.39590e-02 Time taken: 1.68 seconds 
Epoch: 181/200 Train accuracy: 7.15023e-01 Validation accuracy: 5.65400e-01 Training loss 7.96343e-03 Validation loss 1.39959e-02 Time taken: 1.68 seconds 
Epoch: 182/200 Train accuracy: 7.14508e-01 Validation accuracy: 5.61000e-01 Training loss 7.96329e-03 Validation loss 1.40197e-02 Time taken: 1.68 seconds 
Epoch: 183/200 Train accuracy: 7.14308e-01 Validation accuracy: 5.65200e-01 Training loss 7.96202e-03 Validation loss 1.40218e-02 Time taken: 1.67 seconds 
Epoch: 184/200 Train accuracy: 7.14192e-01 Validation accuracy: 5.59600e-01 Training loss 7.96258e-03 Validation loss 1.40584e-02 Time taken: 1.69 seconds 
Epoch: 185/200 Train accuracy: 7.14308e-01 Validation accuracy: 5.63800e-01 Training loss 7.96320e-03 Validation loss 1.40248e-02 Time taken: 1.71 seconds 
Epoch: 186/200 Train accuracy: 7.13462e-01 Validation accuracy: 5.59600e-01 Training loss 7.96607e-03 Validation loss 1.40408e-02 Time taken: 1.71 seconds 
Epoch: 187/200 Train accuracy: 7.14662e-01 Validation accuracy: 5.60600e-01 Training loss 7.95501e-03 Validation loss 1.39946e-02 Time taken: 1.73 seconds 
Epoch: 188/200 Train accuracy: 7.13908e-01 Validation accuracy: 5.58000e-01 Training loss 7.96038e-03 Validation loss 1.39104e-02 Time taken: 1.68 seconds 
Epoch: 189/200 Train accuracy: 7.14308e-01 Validation accuracy: 5.60800e-01 Training loss 7.95943e-03 Validation loss 1.39864e-02 Time taken: 1.68 seconds 
Epoch: 190/200 Train accuracy: 7.14992e-01 Validation accuracy: 5.66200e-01 Training loss 7.96414e-03 Validation loss 1.39665e-02 Time taken: 1.68 seconds 
Epoch: 191/200 Train accuracy: 7.13577e-01 Validation accuracy: 5.64400e-01 Training loss 7.96168e-03 Validation loss 1.39791e-02 Time taken: 1.68 seconds 
Epoch: 192/200 Train accuracy: 7.13446e-01 Validation accuracy: 5.60800e-01 Training loss 7.96472e-03 Validation loss 1.39808e-02 Time taken: 1.68 seconds 
Epoch: 193/200 Train accuracy: 7.14369e-01 Validation accuracy: 5.63600e-01 Training loss 7.95579e-03 Validation loss 1.40386e-02 Time taken: 1.69 seconds 
Epoch: 194/200 Train accuracy: 7.15308e-01 Validation accuracy: 5.62400e-01 Training loss 7.96188e-03 Validation loss 1.40075e-02 Time taken: 1.68 seconds 
Epoch: 195/200 Train accuracy: 7.14554e-01 Validation accuracy: 5.59000e-01 Training loss 7.96222e-03 Validation loss 1.40664e-02 Time taken: 1.68 seconds 
Epoch: 196/200 Train accuracy: 7.13815e-01 Validation accuracy: 5.61200e-01 Training loss 7.95691e-03 Validation loss 1.40272e-02 Time taken: 1.68 seconds 
Epoch: 197/200 Train accuracy: 7.15038e-01 Validation accuracy: 5.59400e-01 Training loss 7.95291e-03 Validation loss 1.40569e-02 Time taken: 1.68 seconds 
Epoch: 198/200 Train accuracy: 7.15115e-01 Validation accuracy: 5.65400e-01 Training loss 7.95492e-03 Validation loss 1.40380e-02 Time taken: 1.68 seconds 
Epoch: 199/200 Train accuracy: 7.14400e-01 Validation accuracy: 5.65400e-01 Training loss 7.95281e-03 Validation loss 1.40771e-02 Time taken: 1.69 seconds 
Epoch: 200/200 Train accuracy: 7.15438e-01 Validation accuracy: 5.62600e-01 Training loss 7.95709e-03 Validation loss 1.39836e-02 Time taken: 1.69 seconds 
Total time taken 0:05:40.227392
Cleaning up intermediate feature (.pt) files
Done


working on file logs_IN100/in100-vitb-l2-ep600-seed0-fulllr/jepa_in100-ep600.pth.tar ...
Directory logs_IN100/in100-vitb-l2-ep600-seed0-fulllr/classifiers for saving the classifiers is now present
VisionTransformer(
  (patch_embed): PatchEmbed(
    (proj): Conv2d(3, 768, kernel_size=(16, 16), stride=(16, 16))
  )
  (blocks): ModuleList(
    (0-11): 12 x Block(
      (norm1): LayerNorm((768,), eps=1e-06, elementwise_affine=True)
      (attn): Attention(
        (qkv): Linear(in_features=768, out_features=2304, bias=True)
        (attn_drop): Dropout(p=0.0, inplace=False)
        (proj): Linear(in_features=768, out_features=768, bias=True)
        (proj_drop): Dropout(p=0.0, inplace=False)
      )
      (drop_path): Identity()
      (norm2): LayerNorm((768,), eps=1e-06, elementwise_affine=True)
      (mlp): MLP(
        (fc1): Linear(in_features=768, out_features=3072, bias=True)
        (act): GELU(approximate='none')
        (fc2): Linear(in_features=3072, out_features=768, bias=True)
        (drop): Dropout(p=0.0, inplace=False)
      )
    )
  )
  (norm): LayerNorm((768,), eps=1e-06, elementwise_affine=True)
)
Extracting features and saving them in memory..
Extracting features...
Epoch: 1/200 Train accuracy: 3.65100e-01 Validation accuracy: 3.94200e-01 Training loss 2.08752e-02 Validation loss 1.96007e-02 Time taken: 1.79 seconds 
Epoch: 2/200 Train accuracy: 4.98585e-01 Validation accuracy: 4.35400e-01 Training loss 1.54646e-02 Validation loss 1.80275e-02 Time taken: 1.68 seconds 
Epoch: 3/200 Train accuracy: 5.32569e-01 Validation accuracy: 4.51000e-01 Training loss 1.41986e-02 Validation loss 1.72989e-02 Time taken: 1.84 seconds 
Epoch: 4/200 Train accuracy: 5.51523e-01 Validation accuracy: 4.62200e-01 Training loss 1.34869e-02 Validation loss 1.69157e-02 Time taken: 1.66 seconds 
Epoch: 5/200 Train accuracy: 5.64331e-01 Validation accuracy: 4.71400e-01 Training loss 1.29960e-02 Validation loss 1.65656e-02 Time taken: 1.64 seconds 
Epoch: 6/200 Train accuracy: 5.76523e-01 Validation accuracy: 4.71800e-01 Training loss 1.26331e-02 Validation loss 1.64599e-02 Time taken: 1.64 seconds 
Epoch: 7/200 Train accuracy: 5.83277e-01 Validation accuracy: 4.80600e-01 Training loss 1.23520e-02 Validation loss 1.62537e-02 Time taken: 1.64 seconds 
Epoch: 8/200 Train accuracy: 5.90923e-01 Validation accuracy: 4.82200e-01 Training loss 1.21290e-02 Validation loss 1.61730e-02 Time taken: 1.64 seconds 
Epoch: 9/200 Train accuracy: 5.95846e-01 Validation accuracy: 4.87200e-01 Training loss 1.19324e-02 Validation loss 1.61660e-02 Time taken: 1.65 seconds 
Epoch: 10/200 Train accuracy: 6.01492e-01 Validation accuracy: 4.85800e-01 Training loss 1.17749e-02 Validation loss 1.59917e-02 Time taken: 1.64 seconds 
Epoch: 11/200 Train accuracy: 6.05177e-01 Validation accuracy: 4.87800e-01 Training loss 1.16332e-02 Validation loss 1.59411e-02 Time taken: 1.64 seconds 
Epoch: 12/200 Train accuracy: 6.08623e-01 Validation accuracy: 4.90600e-01 Training loss 1.15065e-02 Validation loss 1.59572e-02 Time taken: 1.64 seconds 
Epoch: 13/200 Train accuracy: 6.11054e-01 Validation accuracy: 4.89600e-01 Training loss 1.13978e-02 Validation loss 1.58350e-02 Time taken: 1.64 seconds 
Epoch: 14/200 Train accuracy: 6.14969e-01 Validation accuracy: 4.91000e-01 Training loss 1.13049e-02 Validation loss 1.57618e-02 Time taken: 1.64 seconds 
Epoch: 15/200 Train accuracy: 6.16792e-01 Validation accuracy: 4.95600e-01 Training loss 1.12191e-02 Validation loss 1.57089e-02 Time taken: 1.64 seconds 
Epoch: 16/200 Train accuracy: 6.19269e-01 Validation accuracy: 4.89200e-01 Training loss 1.11364e-02 Validation loss 1.56683e-02 Time taken: 1.65 seconds 
Epoch: 17/200 Train accuracy: 6.22138e-01 Validation accuracy: 4.99400e-01 Training loss 1.10619e-02 Validation loss 1.57224e-02 Time taken: 1.65 seconds 
Epoch: 18/200 Train accuracy: 6.23438e-01 Validation accuracy: 4.92600e-01 Training loss 1.09987e-02 Validation loss 1.57742e-02 Time taken: 1.64 seconds 
Epoch: 19/200 Train accuracy: 6.25823e-01 Validation accuracy: 4.96200e-01 Training loss 1.09358e-02 Validation loss 1.57373e-02 Time taken: 1.64 seconds 
Epoch: 20/200 Train accuracy: 6.27492e-01 Validation accuracy: 4.92200e-01 Training loss 1.08836e-02 Validation loss 1.57521e-02 Time taken: 1.64 seconds 
Epoch: 21/200 Train accuracy: 6.28508e-01 Validation accuracy: 4.96400e-01 Training loss 1.08294e-02 Validation loss 1.56097e-02 Time taken: 1.64 seconds 
Epoch: 22/200 Train accuracy: 6.29969e-01 Validation accuracy: 4.97800e-01 Training loss 1.07795e-02 Validation loss 1.57420e-02 Time taken: 1.64 seconds 
Epoch: 23/200 Train accuracy: 6.30300e-01 Validation accuracy: 4.93000e-01 Training loss 1.07339e-02 Validation loss 1.56984e-02 Time taken: 1.64 seconds 
Epoch: 24/200 Train accuracy: 6.33223e-01 Validation accuracy: 4.96800e-01 Training loss 1.06923e-02 Validation loss 1.56724e-02 Time taken: 1.64 seconds 
Epoch: 25/200 Train accuracy: 6.33623e-01 Validation accuracy: 4.99200e-01 Training loss 1.06554e-02 Validation loss 1.55703e-02 Time taken: 1.64 seconds 
Epoch: 26/200 Train accuracy: 6.35262e-01 Validation accuracy: 5.00000e-01 Training loss 1.06175e-02 Validation loss 1.55946e-02 Time taken: 1.65 seconds 
Epoch: 27/200 Train accuracy: 6.35092e-01 Validation accuracy: 5.05200e-01 Training loss 1.05842e-02 Validation loss 1.56261e-02 Time taken: 1.65 seconds 
Epoch: 28/200 Train accuracy: 6.36146e-01 Validation accuracy: 5.01200e-01 Training loss 1.05503e-02 Validation loss 1.56024e-02 Time taken: 1.68 seconds 
Epoch: 29/200 Train accuracy: 6.38400e-01 Validation accuracy: 5.00200e-01 Training loss 1.05179e-02 Validation loss 1.55308e-02 Time taken: 1.71 seconds 
Epoch: 30/200 Train accuracy: 6.39246e-01 Validation accuracy: 4.97400e-01 Training loss 1.04851e-02 Validation loss 1.55971e-02 Time taken: 1.65 seconds 
Epoch: 31/200 Train accuracy: 6.39292e-01 Validation accuracy: 5.03600e-01 Training loss 1.04641e-02 Validation loss 1.55000e-02 Time taken: 1.65 seconds 
Epoch: 32/200 Train accuracy: 6.40023e-01 Validation accuracy: 5.03200e-01 Training loss 1.04306e-02 Validation loss 1.55526e-02 Time taken: 1.64 seconds 
Epoch: 33/200 Train accuracy: 6.40808e-01 Validation accuracy: 5.04000e-01 Training loss 1.04072e-02 Validation loss 1.55335e-02 Time taken: 1.61 seconds 
Epoch: 34/200 Train accuracy: 6.41715e-01 Validation accuracy: 5.05800e-01 Training loss 1.03840e-02 Validation loss 1.55703e-02 Time taken: 1.65 seconds 
Epoch: 35/200 Train accuracy: 6.42485e-01 Validation accuracy: 5.01400e-01 Training loss 1.03583e-02 Validation loss 1.56059e-02 Time taken: 1.65 seconds 
Epoch: 36/200 Train accuracy: 6.42954e-01 Validation accuracy: 5.00400e-01 Training loss 1.03417e-02 Validation loss 1.55311e-02 Time taken: 1.65 seconds 
Epoch: 37/200 Train accuracy: 6.43277e-01 Validation accuracy: 5.03000e-01 Training loss 1.03193e-02 Validation loss 1.55807e-02 Time taken: 1.65 seconds 
Epoch: 38/200 Train accuracy: 6.43708e-01 Validation accuracy: 5.02600e-01 Training loss 1.03017e-02 Validation loss 1.55883e-02 Time taken: 1.65 seconds 
Epoch: 39/200 Train accuracy: 6.44654e-01 Validation accuracy: 4.98200e-01 Training loss 1.02770e-02 Validation loss 1.55168e-02 Time taken: 1.65 seconds 
Epoch: 40/200 Train accuracy: 6.45554e-01 Validation accuracy: 4.99800e-01 Training loss 1.02631e-02 Validation loss 1.55368e-02 Time taken: 1.65 seconds 
Epoch: 41/200 Train accuracy: 6.45800e-01 Validation accuracy: 5.04200e-01 Training loss 1.02430e-02 Validation loss 1.55375e-02 Time taken: 1.64 seconds 
Epoch: 42/200 Train accuracy: 6.46523e-01 Validation accuracy: 5.02200e-01 Training loss 1.02257e-02 Validation loss 1.56039e-02 Time taken: 1.65 seconds 
Epoch: 43/200 Train accuracy: 6.47846e-01 Validation accuracy: 5.01000e-01 Training loss 1.02139e-02 Validation loss 1.56833e-02 Time taken: 1.64 seconds 
Epoch: 44/200 Train accuracy: 6.47000e-01 Validation accuracy: 5.03600e-01 Training loss 1.01990e-02 Validation loss 1.55745e-02 Time taken: 1.65 seconds 
Epoch: 45/200 Train accuracy: 6.46423e-01 Validation accuracy: 5.05200e-01 Training loss 1.01799e-02 Validation loss 1.55758e-02 Time taken: 1.65 seconds 
Epoch: 46/200 Train accuracy: 6.48138e-01 Validation accuracy: 5.09600e-01 Training loss 1.01726e-02 Validation loss 1.54719e-02 Time taken: 1.65 seconds 
Epoch: 47/200 Train accuracy: 6.48500e-01 Validation accuracy: 5.02200e-01 Training loss 1.01509e-02 Validation loss 1.55553e-02 Time taken: 1.65 seconds 
Epoch: 48/200 Train accuracy: 6.49254e-01 Validation accuracy: 5.03600e-01 Training loss 1.01409e-02 Validation loss 1.55621e-02 Time taken: 1.65 seconds 
Epoch: 49/200 Train accuracy: 6.49192e-01 Validation accuracy: 5.08000e-01 Training loss 1.01266e-02 Validation loss 1.55160e-02 Time taken: 1.65 seconds 
Epoch: 50/200 Train accuracy: 6.49715e-01 Validation accuracy: 5.04000e-01 Training loss 1.01175e-02 Validation loss 1.55051e-02 Time taken: 1.64 seconds 
Epoch: 51/200 Train accuracy: 6.50362e-01 Validation accuracy: 5.06400e-01 Training loss 1.01050e-02 Validation loss 1.55632e-02 Time taken: 1.64 seconds 
Epoch: 52/200 Train accuracy: 6.49638e-01 Validation accuracy: 5.05600e-01 Training loss 1.00959e-02 Validation loss 1.55280e-02 Time taken: 1.65 seconds 
Epoch: 53/200 Train accuracy: 6.50485e-01 Validation accuracy: 5.04600e-01 Training loss 1.00856e-02 Validation loss 1.55040e-02 Time taken: 1.64 seconds 
Epoch: 54/200 Train accuracy: 6.51023e-01 Validation accuracy: 5.04600e-01 Training loss 1.00699e-02 Validation loss 1.55276e-02 Time taken: 1.64 seconds 
Epoch: 55/200 Train accuracy: 6.51123e-01 Validation accuracy: 5.04600e-01 Training loss 1.00627e-02 Validation loss 1.55748e-02 Time taken: 1.64 seconds 
Epoch: 56/200 Train accuracy: 6.51523e-01 Validation accuracy: 5.01400e-01 Training loss 1.00489e-02 Validation loss 1.56868e-02 Time taken: 1.65 seconds 
Epoch: 57/200 Train accuracy: 6.51323e-01 Validation accuracy: 5.02200e-01 Training loss 1.00436e-02 Validation loss 1.55375e-02 Time taken: 1.65 seconds 
Epoch: 58/200 Train accuracy: 6.51215e-01 Validation accuracy: 5.06600e-01 Training loss 1.00351e-02 Validation loss 1.55297e-02 Time taken: 1.64 seconds 
Epoch: 59/200 Train accuracy: 6.53192e-01 Validation accuracy: 5.04800e-01 Training loss 1.00250e-02 Validation loss 1.55153e-02 Time taken: 1.64 seconds 
Epoch: 60/200 Train accuracy: 6.52454e-01 Validation accuracy: 5.06600e-01 Training loss 1.00172e-02 Validation loss 1.55281e-02 Time taken: 1.65 seconds 
Epoch: 61/200 Train accuracy: 6.53146e-01 Validation accuracy: 5.03000e-01 Training loss 1.00026e-02 Validation loss 1.55632e-02 Time taken: 1.64 seconds 
Epoch: 62/200 Train accuracy: 6.52969e-01 Validation accuracy: 5.04800e-01 Training loss 1.00021e-02 Validation loss 1.55467e-02 Time taken: 1.65 seconds 
Epoch: 63/200 Train accuracy: 6.53062e-01 Validation accuracy: 5.01200e-01 Training loss 9.98961e-03 Validation loss 1.55880e-02 Time taken: 1.65 seconds 
Epoch: 64/200 Train accuracy: 6.52038e-01 Validation accuracy: 5.05800e-01 Training loss 9.98391e-03 Validation loss 1.55191e-02 Time taken: 1.65 seconds 
Epoch: 65/200 Train accuracy: 6.53277e-01 Validation accuracy: 5.06000e-01 Training loss 9.97608e-03 Validation loss 1.55951e-02 Time taken: 1.65 seconds 
Epoch: 66/200 Train accuracy: 6.53077e-01 Validation accuracy: 5.03600e-01 Training loss 9.97205e-03 Validation loss 1.55423e-02 Time taken: 1.65 seconds 
Epoch: 67/200 Train accuracy: 6.53969e-01 Validation accuracy: 5.05200e-01 Training loss 9.96304e-03 Validation loss 1.54707e-02 Time taken: 1.65 seconds 
Epoch: 68/200 Train accuracy: 6.53946e-01 Validation accuracy: 5.05800e-01 Training loss 9.95706e-03 Validation loss 1.54850e-02 Time taken: 1.66 seconds 
Epoch: 69/200 Train accuracy: 6.54715e-01 Validation accuracy: 5.03400e-01 Training loss 9.94752e-03 Validation loss 1.55803e-02 Time taken: 1.65 seconds 
Epoch: 70/200 Train accuracy: 6.54069e-01 Validation accuracy: 5.05600e-01 Training loss 9.94416e-03 Validation loss 1.54860e-02 Time taken: 1.65 seconds 
Epoch: 71/200 Train accuracy: 6.55038e-01 Validation accuracy: 5.08800e-01 Training loss 9.93421e-03 Validation loss 1.54996e-02 Time taken: 1.65 seconds 
Epoch: 72/200 Train accuracy: 6.54746e-01 Validation accuracy: 5.05000e-01 Training loss 9.92933e-03 Validation loss 1.54769e-02 Time taken: 1.65 seconds 
Epoch: 73/200 Train accuracy: 6.55569e-01 Validation accuracy: 5.08000e-01 Training loss 9.92236e-03 Validation loss 1.55412e-02 Time taken: 1.65 seconds 
Epoch: 74/200 Train accuracy: 6.54785e-01 Validation accuracy: 5.05600e-01 Training loss 9.92049e-03 Validation loss 1.55385e-02 Time taken: 1.65 seconds 
Epoch: 75/200 Train accuracy: 6.56138e-01 Validation accuracy: 5.07400e-01 Training loss 9.91370e-03 Validation loss 1.55735e-02 Time taken: 1.65 seconds 
Epoch: 76/200 Train accuracy: 6.55362e-01 Validation accuracy: 5.07600e-01 Training loss 9.90421e-03 Validation loss 1.55402e-02 Time taken: 1.69 seconds 
Epoch: 77/200 Train accuracy: 6.56023e-01 Validation accuracy: 5.05800e-01 Training loss 9.89778e-03 Validation loss 1.55440e-02 Time taken: 1.67 seconds 
Epoch: 78/200 Train accuracy: 6.55385e-01 Validation accuracy: 5.05800e-01 Training loss 9.89554e-03 Validation loss 1.55960e-02 Time taken: 1.65 seconds 
Epoch: 79/200 Train accuracy: 6.55954e-01 Validation accuracy: 5.03400e-01 Training loss 9.89325e-03 Validation loss 1.56315e-02 Time taken: 1.65 seconds 
Epoch: 80/200 Train accuracy: 6.56315e-01 Validation accuracy: 5.02800e-01 Training loss 9.88609e-03 Validation loss 1.56760e-02 Time taken: 1.65 seconds 
Epoch: 81/200 Train accuracy: 6.57123e-01 Validation accuracy: 5.03200e-01 Training loss 9.88448e-03 Validation loss 1.56147e-02 Time taken: 1.65 seconds 
Epoch: 82/200 Train accuracy: 6.57377e-01 Validation accuracy: 5.02400e-01 Training loss 9.87443e-03 Validation loss 1.56221e-02 Time taken: 1.65 seconds 
Epoch: 83/200 Train accuracy: 6.57038e-01 Validation accuracy: 5.07000e-01 Training loss 9.87190e-03 Validation loss 1.55471e-02 Time taken: 1.66 seconds 
Epoch: 84/200 Train accuracy: 6.56762e-01 Validation accuracy: 5.12000e-01 Training loss 9.86534e-03 Validation loss 1.54935e-02 Time taken: 1.67 seconds 
Epoch: 85/200 Train accuracy: 6.56769e-01 Validation accuracy: 4.97800e-01 Training loss 9.86189e-03 Validation loss 1.56456e-02 Time taken: 1.66 seconds 
Epoch: 86/200 Train accuracy: 6.56592e-01 Validation accuracy: 5.04600e-01 Training loss 9.85745e-03 Validation loss 1.55068e-02 Time taken: 1.65 seconds 
Epoch: 87/200 Train accuracy: 6.57662e-01 Validation accuracy: 5.03800e-01 Training loss 9.85807e-03 Validation loss 1.55395e-02 Time taken: 1.65 seconds 
Epoch: 88/200 Train accuracy: 6.57108e-01 Validation accuracy: 5.03200e-01 Training loss 9.85518e-03 Validation loss 1.55497e-02 Time taken: 1.66 seconds 
Epoch: 89/200 Train accuracy: 6.57554e-01 Validation accuracy: 5.09600e-01 Training loss 9.84696e-03 Validation loss 1.54822e-02 Time taken: 1.65 seconds 
Epoch: 90/200 Train accuracy: 6.57377e-01 Validation accuracy: 5.07000e-01 Training loss 9.84010e-03 Validation loss 1.55115e-02 Time taken: 1.65 seconds 
Epoch: 91/200 Train accuracy: 6.57723e-01 Validation accuracy: 5.08200e-01 Training loss 9.83919e-03 Validation loss 1.55138e-02 Time taken: 1.65 seconds 
Epoch: 92/200 Train accuracy: 6.57515e-01 Validation accuracy: 5.07800e-01 Training loss 9.83913e-03 Validation loss 1.56444e-02 Time taken: 1.65 seconds 
Epoch: 93/200 Train accuracy: 6.57531e-01 Validation accuracy: 5.09200e-01 Training loss 9.83736e-03 Validation loss 1.55842e-02 Time taken: 1.65 seconds 
Epoch: 94/200 Train accuracy: 6.58362e-01 Validation accuracy: 5.03800e-01 Training loss 9.83133e-03 Validation loss 1.56276e-02 Time taken: 1.65 seconds 
Epoch: 95/200 Train accuracy: 6.57108e-01 Validation accuracy: 5.12800e-01 Training loss 9.83284e-03 Validation loss 1.54673e-02 Time taken: 1.65 seconds 
Epoch: 96/200 Train accuracy: 6.58254e-01 Validation accuracy: 5.09400e-01 Training loss 9.82325e-03 Validation loss 1.56156e-02 Time taken: 1.65 seconds 
Epoch: 97/200 Train accuracy: 6.58192e-01 Validation accuracy: 5.06000e-01 Training loss 9.82070e-03 Validation loss 1.56059e-02 Time taken: 1.65 seconds 
Epoch: 98/200 Train accuracy: 6.58546e-01 Validation accuracy: 5.04600e-01 Training loss 9.81768e-03 Validation loss 1.55750e-02 Time taken: 1.65 seconds 
Epoch: 99/200 Train accuracy: 6.58600e-01 Validation accuracy: 5.08600e-01 Training loss 9.81802e-03 Validation loss 1.55111e-02 Time taken: 1.65 seconds 
Epoch: 100/200 Train accuracy: 6.58515e-01 Validation accuracy: 5.01200e-01 Training loss 9.81479e-03 Validation loss 1.55253e-02 Time taken: 1.66 seconds 
Epoch: 101/200 Train accuracy: 6.59315e-01 Validation accuracy: 5.09000e-01 Training loss 9.80891e-03 Validation loss 1.55674e-02 Time taken: 1.66 seconds 
Epoch: 102/200 Train accuracy: 6.58677e-01 Validation accuracy: 5.07000e-01 Training loss 9.80859e-03 Validation loss 1.55753e-02 Time taken: 1.65 seconds 
Epoch: 103/200 Train accuracy: 6.58508e-01 Validation accuracy: 5.06200e-01 Training loss 9.80088e-03 Validation loss 1.55747e-02 Time taken: 1.65 seconds 
Epoch: 104/200 Train accuracy: 6.59092e-01 Validation accuracy: 5.07000e-01 Training loss 9.79501e-03 Validation loss 1.54950e-02 Time taken: 1.65 seconds 
Epoch: 105/200 Train accuracy: 6.59215e-01 Validation accuracy: 5.04800e-01 Training loss 9.80351e-03 Validation loss 1.56079e-02 Time taken: 1.66 seconds 
Epoch: 106/200 Train accuracy: 6.59154e-01 Validation accuracy: 5.06400e-01 Training loss 9.79870e-03 Validation loss 1.55633e-02 Time taken: 1.65 seconds 
Epoch: 107/200 Train accuracy: 6.58400e-01 Validation accuracy: 5.06800e-01 Training loss 9.79823e-03 Validation loss 1.55114e-02 Time taken: 1.65 seconds 
Epoch: 108/200 Train accuracy: 6.58962e-01 Validation accuracy: 5.07400e-01 Training loss 9.79491e-03 Validation loss 1.54925e-02 Time taken: 1.65 seconds 
Epoch: 109/200 Train accuracy: 6.59292e-01 Validation accuracy: 5.06600e-01 Training loss 9.78701e-03 Validation loss 1.54939e-02 Time taken: 1.66 seconds 
Epoch: 110/200 Train accuracy: 6.58908e-01 Validation accuracy: 5.05600e-01 Training loss 9.79271e-03 Validation loss 1.55792e-02 Time taken: 1.66 seconds 
Epoch: 111/200 Train accuracy: 6.59769e-01 Validation accuracy: 5.06400e-01 Training loss 9.77976e-03 Validation loss 1.55274e-02 Time taken: 1.65 seconds 
Epoch: 112/200 Train accuracy: 6.59192e-01 Validation accuracy: 5.08000e-01 Training loss 9.78904e-03 Validation loss 1.55876e-02 Time taken: 1.65 seconds 
Epoch: 113/200 Train accuracy: 6.59362e-01 Validation accuracy: 5.09400e-01 Training loss 9.77937e-03 Validation loss 1.55540e-02 Time taken: 1.65 seconds 
Epoch: 114/200 Train accuracy: 6.58892e-01 Validation accuracy: 5.05800e-01 Training loss 9.78178e-03 Validation loss 1.55747e-02 Time taken: 1.67 seconds 
Epoch: 115/200 Train accuracy: 6.59154e-01 Validation accuracy: 5.07000e-01 Training loss 9.78015e-03 Validation loss 1.54966e-02 Time taken: 1.73 seconds 
Epoch: 116/200 Train accuracy: 6.59777e-01 Validation accuracy: 5.08600e-01 Training loss 9.77303e-03 Validation loss 1.55420e-02 Time taken: 1.67 seconds 
Epoch: 117/200 Train accuracy: 6.59669e-01 Validation accuracy: 5.09200e-01 Training loss 9.77638e-03 Validation loss 1.55333e-02 Time taken: 1.65 seconds 
Epoch: 118/200 Train accuracy: 6.59715e-01 Validation accuracy: 5.01400e-01 Training loss 9.76956e-03 Validation loss 1.55810e-02 Time taken: 1.65 seconds 
Epoch: 119/200 Train accuracy: 6.60285e-01 Validation accuracy: 5.04400e-01 Training loss 9.76554e-03 Validation loss 1.55143e-02 Time taken: 1.65 seconds 
Epoch: 120/200 Train accuracy: 6.59862e-01 Validation accuracy: 5.05800e-01 Training loss 9.76458e-03 Validation loss 1.55480e-02 Time taken: 1.65 seconds 
Epoch: 121/200 Train accuracy: 6.58900e-01 Validation accuracy: 5.08000e-01 Training loss 9.76923e-03 Validation loss 1.56549e-02 Time taken: 1.66 seconds 
Epoch: 122/200 Train accuracy: 6.59646e-01 Validation accuracy: 5.03200e-01 Training loss 9.75738e-03 Validation loss 1.55737e-02 Time taken: 1.65 seconds 
Epoch: 123/200 Train accuracy: 6.58823e-01 Validation accuracy: 5.07800e-01 Training loss 9.76585e-03 Validation loss 1.55093e-02 Time taken: 1.65 seconds 
Epoch: 124/200 Train accuracy: 6.60431e-01 Validation accuracy: 5.06400e-01 Training loss 9.76465e-03 Validation loss 1.55319e-02 Time taken: 1.65 seconds 
Epoch: 125/200 Train accuracy: 6.60031e-01 Validation accuracy: 5.08600e-01 Training loss 9.75788e-03 Validation loss 1.55672e-02 Time taken: 1.65 seconds 
Epoch: 126/200 Train accuracy: 6.60369e-01 Validation accuracy: 5.06800e-01 Training loss 9.75728e-03 Validation loss 1.55278e-02 Time taken: 1.65 seconds 
Epoch: 127/200 Train accuracy: 6.60800e-01 Validation accuracy: 5.04600e-01 Training loss 9.75591e-03 Validation loss 1.56034e-02 Time taken: 1.66 seconds 
Epoch: 128/200 Train accuracy: 6.60700e-01 Validation accuracy: 5.11400e-01 Training loss 9.75725e-03 Validation loss 1.54839e-02 Time taken: 1.65 seconds 
Epoch: 129/200 Train accuracy: 6.60069e-01 Validation accuracy: 5.08000e-01 Training loss 9.75183e-03 Validation loss 1.56550e-02 Time taken: 1.65 seconds 
Epoch: 130/200 Train accuracy: 6.60092e-01 Validation accuracy: 5.08000e-01 Training loss 9.74922e-03 Validation loss 1.55738e-02 Time taken: 1.65 seconds 
Epoch: 131/200 Train accuracy: 6.60131e-01 Validation accuracy: 5.07400e-01 Training loss 9.74981e-03 Validation loss 1.55895e-02 Time taken: 1.65 seconds 
Epoch: 132/200 Train accuracy: 6.60031e-01 Validation accuracy: 5.06000e-01 Training loss 9.74384e-03 Validation loss 1.55653e-02 Time taken: 1.66 seconds 
Epoch: 133/200 Train accuracy: 6.60431e-01 Validation accuracy: 5.11000e-01 Training loss 9.75158e-03 Validation loss 1.55355e-02 Time taken: 1.66 seconds 
Epoch: 134/200 Train accuracy: 6.60769e-01 Validation accuracy: 5.06200e-01 Training loss 9.73827e-03 Validation loss 1.55042e-02 Time taken: 1.67 seconds 
Epoch: 135/200 Train accuracy: 6.60246e-01 Validation accuracy: 5.07400e-01 Training loss 9.74163e-03 Validation loss 1.55252e-02 Time taken: 1.72 seconds 
Epoch: 136/200 Train accuracy: 6.60954e-01 Validation accuracy: 5.09600e-01 Training loss 9.74371e-03 Validation loss 1.54989e-02 Time taken: 1.68 seconds 
Epoch: 137/200 Train accuracy: 6.59854e-01 Validation accuracy: 5.07600e-01 Training loss 9.74348e-03 Validation loss 1.55419e-02 Time taken: 1.65 seconds 
Epoch: 138/200 Train accuracy: 6.59554e-01 Validation accuracy: 5.10400e-01 Training loss 9.73993e-03 Validation loss 1.55475e-02 Time taken: 1.65 seconds 
Epoch: 139/200 Train accuracy: 6.60954e-01 Validation accuracy: 5.06000e-01 Training loss 9.74088e-03 Validation loss 1.55546e-02 Time taken: 1.65 seconds 
Epoch: 140/200 Train accuracy: 6.60354e-01 Validation accuracy: 5.17000e-01 Training loss 9.73985e-03 Validation loss 1.54591e-02 Time taken: 1.66 seconds 
Epoch: 141/200 Train accuracy: 6.60685e-01 Validation accuracy: 5.15000e-01 Training loss 9.73539e-03 Validation loss 1.56497e-02 Time taken: 1.65 seconds 
Epoch: 142/200 Train accuracy: 6.61023e-01 Validation accuracy: 5.02600e-01 Training loss 9.73615e-03 Validation loss 1.55846e-02 Time taken: 1.65 seconds 
Epoch: 143/200 Train accuracy: 6.60785e-01 Validation accuracy: 5.05200e-01 Training loss 9.73974e-03 Validation loss 1.55313e-02 Time taken: 1.65 seconds 
Epoch: 144/200 Train accuracy: 6.60962e-01 Validation accuracy: 5.05800e-01 Training loss 9.73632e-03 Validation loss 1.55639e-02 Time taken: 1.66 seconds 
Epoch: 145/200 Train accuracy: 6.61769e-01 Validation accuracy: 5.05600e-01 Training loss 9.72793e-03 Validation loss 1.55656e-02 Time taken: 1.66 seconds 
Epoch: 146/200 Train accuracy: 6.60554e-01 Validation accuracy: 5.05400e-01 Training loss 9.72879e-03 Validation loss 1.55269e-02 Time taken: 1.65 seconds 
Epoch: 147/200 Train accuracy: 6.60223e-01 Validation accuracy: 5.07400e-01 Training loss 9.73580e-03 Validation loss 1.54854e-02 Time taken: 1.65 seconds 
Epoch: 148/200 Train accuracy: 6.61369e-01 Validation accuracy: 5.07200e-01 Training loss 9.72637e-03 Validation loss 1.55567e-02 Time taken: 1.65 seconds 
Epoch: 149/200 Train accuracy: 6.60208e-01 Validation accuracy: 5.04800e-01 Training loss 9.72771e-03 Validation loss 1.55796e-02 Time taken: 1.65 seconds 
Epoch: 150/200 Train accuracy: 6.60377e-01 Validation accuracy: 5.08800e-01 Training loss 9.73015e-03 Validation loss 1.55124e-02 Time taken: 1.67 seconds 
Epoch: 151/200 Train accuracy: 6.61346e-01 Validation accuracy: 5.08400e-01 Training loss 9.72760e-03 Validation loss 1.56093e-02 Time taken: 1.65 seconds 
Epoch: 152/200 Train accuracy: 6.61531e-01 Validation accuracy: 5.07000e-01 Training loss 9.72806e-03 Validation loss 1.55567e-02 Time taken: 1.65 seconds 
Epoch: 153/200 Train accuracy: 6.61462e-01 Validation accuracy: 5.07400e-01 Training loss 9.72544e-03 Validation loss 1.55650e-02 Time taken: 1.65 seconds 
Epoch: 154/200 Train accuracy: 6.61838e-01 Validation accuracy: 5.15000e-01 Training loss 9.72352e-03 Validation loss 1.55441e-02 Time taken: 1.66 seconds 
Epoch: 155/200 Train accuracy: 6.60623e-01 Validation accuracy: 5.06600e-01 Training loss 9.72429e-03 Validation loss 1.55089e-02 Time taken: 1.65 seconds 
Epoch: 156/200 Train accuracy: 6.61285e-01 Validation accuracy: 5.07000e-01 Training loss 9.71762e-03 Validation loss 1.56140e-02 Time taken: 1.66 seconds 
Epoch: 157/200 Train accuracy: 6.60585e-01 Validation accuracy: 5.08600e-01 Training loss 9.72206e-03 Validation loss 1.55454e-02 Time taken: 1.65 seconds 
Epoch: 158/200 Train accuracy: 6.61531e-01 Validation accuracy: 5.07800e-01 Training loss 9.72170e-03 Validation loss 1.55234e-02 Time taken: 1.65 seconds 
Epoch: 159/200 Train accuracy: 6.60631e-01 Validation accuracy: 5.05800e-01 Training loss 9.71841e-03 Validation loss 1.55932e-02 Time taken: 1.67 seconds 
Epoch: 160/200 Train accuracy: 6.61038e-01 Validation accuracy: 5.07200e-01 Training loss 9.71615e-03 Validation loss 1.55095e-02 Time taken: 1.71 seconds 
Epoch: 161/200 Train accuracy: 6.60777e-01 Validation accuracy: 5.05800e-01 Training loss 9.72008e-03 Validation loss 1.56027e-02 Time taken: 1.68 seconds 
Epoch: 162/200 Train accuracy: 6.60438e-01 Validation accuracy: 5.08200e-01 Training loss 9.71553e-03 Validation loss 1.55736e-02 Time taken: 1.66 seconds 
Epoch: 163/200 Train accuracy: 6.60985e-01 Validation accuracy: 5.06000e-01 Training loss 9.71185e-03 Validation loss 1.55557e-02 Time taken: 1.65 seconds 
Epoch: 164/200 Train accuracy: 6.60938e-01 Validation accuracy: 5.08000e-01 Training loss 9.71435e-03 Validation loss 1.56209e-02 Time taken: 1.65 seconds 
Epoch: 165/200 Train accuracy: 6.60615e-01 Validation accuracy: 5.09000e-01 Training loss 9.71543e-03 Validation loss 1.54698e-02 Time taken: 1.65 seconds 
Epoch: 166/200 Train accuracy: 6.61785e-01 Validation accuracy: 5.08600e-01 Training loss 9.71088e-03 Validation loss 1.55450e-02 Time taken: 1.65 seconds 
Epoch: 167/200 Train accuracy: 6.60446e-01 Validation accuracy: 5.04400e-01 Training loss 9.71210e-03 Validation loss 1.55442e-02 Time taken: 1.65 seconds 
Epoch: 168/200 Train accuracy: 6.61708e-01 Validation accuracy: 5.06000e-01 Training loss 9.71220e-03 Validation loss 1.55247e-02 Time taken: 1.65 seconds 
Epoch: 169/200 Train accuracy: 6.61200e-01 Validation accuracy: 5.04200e-01 Training loss 9.70736e-03 Validation loss 1.55666e-02 Time taken: 1.65 seconds 
Epoch: 170/200 Train accuracy: 6.60569e-01 Validation accuracy: 5.07000e-01 Training loss 9.71268e-03 Validation loss 1.56003e-02 Time taken: 1.66 seconds 
Epoch: 171/200 Train accuracy: 6.61246e-01 Validation accuracy: 5.11400e-01 Training loss 9.70669e-03 Validation loss 1.55432e-02 Time taken: 1.65 seconds 
Epoch: 172/200 Train accuracy: 6.61015e-01 Validation accuracy: 5.10000e-01 Training loss 9.70939e-03 Validation loss 1.55600e-02 Time taken: 1.65 seconds 
Epoch: 173/200 Train accuracy: 6.60285e-01 Validation accuracy: 5.03800e-01 Training loss 9.71452e-03 Validation loss 1.55474e-02 Time taken: 1.65 seconds 
Epoch: 174/200 Train accuracy: 6.61354e-01 Validation accuracy: 5.04800e-01 Training loss 9.70911e-03 Validation loss 1.55736e-02 Time taken: 1.65 seconds 
Epoch: 175/200 Train accuracy: 6.61438e-01 Validation accuracy: 5.08200e-01 Training loss 9.71346e-03 Validation loss 1.55234e-02 Time taken: 1.65 seconds 
Epoch: 176/200 Train accuracy: 6.61292e-01 Validation accuracy: 5.07800e-01 Training loss 9.70425e-03 Validation loss 1.55444e-02 Time taken: 1.65 seconds 
Epoch: 177/200 Train accuracy: 6.61485e-01 Validation accuracy: 5.07000e-01 Training loss 9.70706e-03 Validation loss 1.55631e-02 Time taken: 1.67 seconds 
Epoch: 178/200 Train accuracy: 6.61885e-01 Validation accuracy: 5.05400e-01 Training loss 9.70692e-03 Validation loss 1.56168e-02 Time taken: 1.66 seconds 
Epoch: 179/200 Train accuracy: 6.61962e-01 Validation accuracy: 5.07200e-01 Training loss 9.70964e-03 Validation loss 1.56121e-02 Time taken: 1.66 seconds 
Epoch: 180/200 Train accuracy: 6.61585e-01 Validation accuracy: 5.04400e-01 Training loss 9.70082e-03 Validation loss 1.55544e-02 Time taken: 1.66 seconds 
Epoch: 181/200 Train accuracy: 6.60785e-01 Validation accuracy: 5.09400e-01 Training loss 9.70775e-03 Validation loss 1.55496e-02 Time taken: 1.65 seconds 
Epoch: 182/200 Train accuracy: 6.61454e-01 Validation accuracy: 5.04200e-01 Training loss 9.69882e-03 Validation loss 1.55626e-02 Time taken: 1.65 seconds 
Epoch: 183/200 Train accuracy: 6.61846e-01 Validation accuracy: 5.04400e-01 Training loss 9.70184e-03 Validation loss 1.56305e-02 Time taken: 1.65 seconds 
Epoch: 184/200 Train accuracy: 6.60654e-01 Validation accuracy: 5.09800e-01 Training loss 9.70792e-03 Validation loss 1.55798e-02 Time taken: 1.72 seconds 
Epoch: 185/200 Train accuracy: 6.61554e-01 Validation accuracy: 5.06600e-01 Training loss 9.70773e-03 Validation loss 1.54897e-02 Time taken: 1.65 seconds 
Epoch: 186/200 Train accuracy: 6.61131e-01 Validation accuracy: 5.07600e-01 Training loss 9.70066e-03 Validation loss 1.55166e-02 Time taken: 1.65 seconds 
Epoch: 187/200 Train accuracy: 6.61862e-01 Validation accuracy: 5.06800e-01 Training loss 9.70042e-03 Validation loss 1.56685e-02 Time taken: 1.65 seconds 
Epoch: 188/200 Train accuracy: 6.60808e-01 Validation accuracy: 5.07600e-01 Training loss 9.70297e-03 Validation loss 1.55013e-02 Time taken: 1.66 seconds 
Epoch: 189/200 Train accuracy: 6.63038e-01 Validation accuracy: 5.10000e-01 Training loss 9.69850e-03 Validation loss 1.55480e-02 Time taken: 1.65 seconds 
Epoch: 190/200 Train accuracy: 6.62069e-01 Validation accuracy: 5.07200e-01 Training loss 9.70031e-03 Validation loss 1.54908e-02 Time taken: 1.65 seconds 
Epoch: 191/200 Train accuracy: 6.61254e-01 Validation accuracy: 5.07000e-01 Training loss 9.70223e-03 Validation loss 1.56101e-02 Time taken: 1.65 seconds 
Epoch: 192/200 Train accuracy: 6.61338e-01 Validation accuracy: 5.10800e-01 Training loss 9.70009e-03 Validation loss 1.55410e-02 Time taken: 1.67 seconds 
Epoch: 193/200 Train accuracy: 6.61908e-01 Validation accuracy: 5.08000e-01 Training loss 9.70107e-03 Validation loss 1.56754e-02 Time taken: 1.66 seconds 
Epoch: 194/200 Train accuracy: 6.61969e-01 Validation accuracy: 5.07600e-01 Training loss 9.69898e-03 Validation loss 1.55266e-02 Time taken: 1.65 seconds 
Epoch: 195/200 Train accuracy: 6.61615e-01 Validation accuracy: 5.12600e-01 Training loss 9.69791e-03 Validation loss 1.55501e-02 Time taken: 1.65 seconds 
Epoch: 196/200 Train accuracy: 6.62315e-01 Validation accuracy: 5.09000e-01 Training loss 9.69557e-03 Validation loss 1.55800e-02 Time taken: 1.65 seconds 
Epoch: 197/200 Train accuracy: 6.60323e-01 Validation accuracy: 5.09600e-01 Training loss 9.70248e-03 Validation loss 1.54973e-02 Time taken: 1.65 seconds 
Epoch: 198/200 Train accuracy: 6.61685e-01 Validation accuracy: 5.09600e-01 Training loss 9.69940e-03 Validation loss 1.55890e-02 Time taken: 1.66 seconds 
Epoch: 199/200 Train accuracy: 6.62638e-01 Validation accuracy: 5.11800e-01 Training loss 9.69877e-03 Validation loss 1.55138e-02 Time taken: 1.65 seconds 
Epoch: 200/200 Train accuracy: 6.61631e-01 Validation accuracy: 5.06600e-01 Training loss 9.69669e-03 Validation loss 1.55650e-02 Time taken: 1.66 seconds 
Total time taken 0:05:34.132101
Cleaning up intermediate feature (.pt) files
Done