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hushem_1x_deit_tiny_adamax_001_fold1

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  1. README.md +54 -54
  2. model.safetensors +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.4
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 5.8178
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- - Accuracy: 0.4
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  ## Model description
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@@ -52,7 +52,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 0.001
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  - train_batch_size: 32
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  - eval_batch_size: 32
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  - seed: 42
@@ -65,56 +65,56 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 6 | 1.6382 | 0.2444 |
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- | 2.1568 | 2.0 | 12 | 1.3466 | 0.3111 |
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- | 2.1568 | 3.0 | 18 | 1.4826 | 0.3333 |
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- | 1.204 | 4.0 | 24 | 1.8194 | 0.3778 |
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- | 0.8919 | 5.0 | 30 | 1.8241 | 0.4 |
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- | 0.8919 | 6.0 | 36 | 2.0897 | 0.4222 |
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- | 0.5779 | 7.0 | 42 | 1.2520 | 0.5111 |
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- | 0.5779 | 8.0 | 48 | 1.1793 | 0.5333 |
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- | 0.6575 | 9.0 | 54 | 1.7606 | 0.4222 |
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- | 0.5042 | 10.0 | 60 | 2.4732 | 0.3778 |
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- | 0.5042 | 11.0 | 66 | 1.6162 | 0.3778 |
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- | 0.4425 | 12.0 | 72 | 1.9786 | 0.3778 |
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- | 0.4425 | 13.0 | 78 | 3.2416 | 0.3556 |
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- | 0.376 | 14.0 | 84 | 2.0876 | 0.3778 |
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- | 0.2172 | 15.0 | 90 | 3.6129 | 0.5111 |
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- | 0.2172 | 16.0 | 96 | 5.8826 | 0.3556 |
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- | 0.3867 | 17.0 | 102 | 1.7748 | 0.5111 |
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- | 0.3867 | 18.0 | 108 | 4.3640 | 0.4 |
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- | 0.118 | 19.0 | 114 | 3.4995 | 0.4 |
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- | 0.0493 | 20.0 | 120 | 3.8698 | 0.4444 |
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- | 0.0493 | 21.0 | 126 | 3.6078 | 0.4889 |
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- | 0.0212 | 22.0 | 132 | 5.2731 | 0.4 |
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- | 0.0212 | 23.0 | 138 | 4.8918 | 0.4222 |
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- | 0.003 | 24.0 | 144 | 5.3873 | 0.4444 |
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- | 0.0004 | 25.0 | 150 | 5.6456 | 0.4 |
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- | 0.0004 | 26.0 | 156 | 5.7626 | 0.4 |
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- | 0.0001 | 27.0 | 162 | 5.8114 | 0.4 |
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- | 0.0001 | 28.0 | 168 | 5.8330 | 0.3778 |
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- | 0.0001 | 29.0 | 174 | 5.8388 | 0.3778 |
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- | 0.0001 | 30.0 | 180 | 5.8388 | 0.3778 |
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- | 0.0001 | 31.0 | 186 | 5.8374 | 0.4 |
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- | 0.0001 | 32.0 | 192 | 5.8320 | 0.4 |
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- | 0.0001 | 33.0 | 198 | 5.8279 | 0.4 |
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- | 0.0001 | 34.0 | 204 | 5.8253 | 0.4 |
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- | 0.0001 | 35.0 | 210 | 5.8210 | 0.4 |
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- | 0.0001 | 36.0 | 216 | 5.8195 | 0.4 |
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- | 0.0001 | 37.0 | 222 | 5.8189 | 0.4 |
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- | 0.0001 | 38.0 | 228 | 5.8188 | 0.4 |
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- | 0.0001 | 39.0 | 234 | 5.8188 | 0.4 |
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- | 0.0001 | 40.0 | 240 | 5.8180 | 0.4 |
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- | 0.0001 | 41.0 | 246 | 5.8178 | 0.4 |
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- | 0.0001 | 42.0 | 252 | 5.8178 | 0.4 |
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- | 0.0001 | 43.0 | 258 | 5.8178 | 0.4 |
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- | 0.0001 | 44.0 | 264 | 5.8178 | 0.4 |
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- | 0.0001 | 45.0 | 270 | 5.8178 | 0.4 |
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- | 0.0001 | 46.0 | 276 | 5.8178 | 0.4 |
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- | 0.0001 | 47.0 | 282 | 5.8178 | 0.4 |
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- | 0.0001 | 48.0 | 288 | 5.8178 | 0.4 |
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- | 0.0001 | 49.0 | 294 | 5.8178 | 0.4 |
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- | 0.0001 | 50.0 | 300 | 5.8178 | 0.4 |
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  ### Framework versions
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.5777777777777777
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.8804
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+ - Accuracy: 0.5778
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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  - train_batch_size: 32
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  - eval_batch_size: 32
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 6 | 1.3266 | 0.3778 |
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+ | 1.1956 | 2.0 | 12 | 1.1674 | 0.4667 |
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+ | 1.1956 | 3.0 | 18 | 1.1849 | 0.4889 |
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+ | 0.4784 | 4.0 | 24 | 1.2723 | 0.4667 |
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+ | 0.1535 | 5.0 | 30 | 1.2811 | 0.4889 |
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+ | 0.1535 | 6.0 | 36 | 1.5643 | 0.4667 |
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+ | 0.0259 | 7.0 | 42 | 1.3477 | 0.5556 |
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+ | 0.0259 | 8.0 | 48 | 1.7927 | 0.4889 |
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+ | 0.0051 | 9.0 | 54 | 1.7277 | 0.5556 |
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+ | 0.0016 | 10.0 | 60 | 1.5795 | 0.6222 |
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+ | 0.0016 | 11.0 | 66 | 1.6103 | 0.6 |
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+ | 0.0008 | 12.0 | 72 | 1.7043 | 0.5778 |
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+ | 0.0008 | 13.0 | 78 | 1.7832 | 0.5778 |
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+ | 0.0005 | 14.0 | 84 | 1.8224 | 0.5778 |
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+ | 0.0004 | 15.0 | 90 | 1.8294 | 0.5778 |
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+ | 0.0004 | 16.0 | 96 | 1.8185 | 0.5778 |
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+ | 0.0004 | 17.0 | 102 | 1.8150 | 0.5778 |
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+ | 0.0004 | 18.0 | 108 | 1.8206 | 0.5778 |
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+ | 0.0004 | 19.0 | 114 | 1.8349 | 0.5778 |
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+ | 0.0003 | 20.0 | 120 | 1.8491 | 0.5778 |
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+ | 0.0003 | 21.0 | 126 | 1.8590 | 0.5778 |
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+ | 0.0003 | 22.0 | 132 | 1.8667 | 0.5556 |
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+ | 0.0003 | 23.0 | 138 | 1.8640 | 0.5556 |
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+ | 0.0003 | 24.0 | 144 | 1.8624 | 0.5556 |
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+ | 0.0003 | 25.0 | 150 | 1.8632 | 0.5778 |
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+ | 0.0003 | 26.0 | 156 | 1.8651 | 0.5556 |
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+ | 0.0003 | 27.0 | 162 | 1.8642 | 0.5778 |
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+ | 0.0003 | 28.0 | 168 | 1.8659 | 0.5778 |
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+ | 0.0003 | 29.0 | 174 | 1.8666 | 0.5778 |
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+ | 0.0003 | 30.0 | 180 | 1.8680 | 0.5778 |
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+ | 0.0003 | 31.0 | 186 | 1.8684 | 0.5778 |
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+ | 0.0002 | 32.0 | 192 | 1.8677 | 0.5778 |
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+ | 0.0002 | 33.0 | 198 | 1.8709 | 0.5778 |
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+ | 0.0002 | 34.0 | 204 | 1.8723 | 0.5778 |
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+ | 0.0002 | 35.0 | 210 | 1.8730 | 0.5778 |
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+ | 0.0002 | 36.0 | 216 | 1.8757 | 0.5778 |
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+ | 0.0002 | 37.0 | 222 | 1.8766 | 0.5778 |
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+ | 0.0002 | 38.0 | 228 | 1.8780 | 0.5778 |
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+ | 0.0002 | 39.0 | 234 | 1.8793 | 0.5778 |
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+ | 0.0002 | 40.0 | 240 | 1.8801 | 0.5778 |
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+ | 0.0002 | 41.0 | 246 | 1.8804 | 0.5778 |
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+ | 0.0002 | 42.0 | 252 | 1.8804 | 0.5778 |
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+ | 0.0002 | 43.0 | 258 | 1.8804 | 0.5778 |
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+ | 0.0002 | 44.0 | 264 | 1.8804 | 0.5778 |
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+ | 0.0002 | 45.0 | 270 | 1.8804 | 0.5778 |
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+ | 0.0002 | 46.0 | 276 | 1.8804 | 0.5778 |
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+ | 0.0002 | 47.0 | 282 | 1.8804 | 0.5778 |
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+ | 0.0002 | 48.0 | 288 | 1.8804 | 0.5778 |
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+ | 0.0002 | 49.0 | 294 | 1.8804 | 0.5778 |
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+ | 0.0002 | 50.0 | 300 | 1.8804 | 0.5778 |
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  ### Framework versions
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