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hkivancoral
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hushem_1x_deit_tiny_sgd_00001_fold1

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  1. README.md +56 -56
  2. model.safetensors +1 -1
  3. runs/Nov17_06-36-56_395c52d28269/events.out.tfevents.1700203023.395c52d28269.215637.0 +2 -2
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: 0.26666666666666666
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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: 1.6650
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- - Accuracy: 0.2667
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  ## Model description
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@@ -65,61 +65,61 @@ 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 | 1.6807 | 0.2667 |
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- | 1.7256 | 2.0 | 12 | 1.6798 | 0.2667 |
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- | 1.7256 | 3.0 | 18 | 1.6790 | 0.2667 |
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- | 1.715 | 4.0 | 24 | 1.6783 | 0.2667 |
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- | 1.7579 | 5.0 | 30 | 1.6775 | 0.2667 |
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- | 1.7579 | 6.0 | 36 | 1.6768 | 0.2667 |
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- | 1.7037 | 7.0 | 42 | 1.6761 | 0.2667 |
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- | 1.7037 | 8.0 | 48 | 1.6755 | 0.2667 |
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- | 1.6916 | 9.0 | 54 | 1.6748 | 0.2667 |
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- | 1.7402 | 10.0 | 60 | 1.6742 | 0.2667 |
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- | 1.7402 | 11.0 | 66 | 1.6736 | 0.2667 |
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- | 1.7036 | 12.0 | 72 | 1.6730 | 0.2667 |
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- | 1.7036 | 13.0 | 78 | 1.6724 | 0.2667 |
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- | 1.8164 | 14.0 | 84 | 1.6718 | 0.2667 |
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- | 1.7198 | 15.0 | 90 | 1.6713 | 0.2667 |
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- | 1.7198 | 16.0 | 96 | 1.6708 | 0.2667 |
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- | 1.7047 | 17.0 | 102 | 1.6704 | 0.2667 |
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- | 1.7047 | 18.0 | 108 | 1.6699 | 0.2667 |
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- | 1.7105 | 19.0 | 114 | 1.6695 | 0.2667 |
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- | 1.6839 | 20.0 | 120 | 1.6691 | 0.2667 |
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- | 1.6839 | 21.0 | 126 | 1.6687 | 0.2667 |
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- | 1.6768 | 22.0 | 132 | 1.6683 | 0.2667 |
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- | 1.6768 | 23.0 | 138 | 1.6679 | 0.2667 |
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- | 1.7332 | 24.0 | 144 | 1.6676 | 0.2667 |
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- | 1.69 | 25.0 | 150 | 1.6673 | 0.2667 |
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- | 1.69 | 26.0 | 156 | 1.6670 | 0.2667 |
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- | 1.6919 | 27.0 | 162 | 1.6668 | 0.2667 |
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- | 1.6919 | 28.0 | 168 | 1.6665 | 0.2667 |
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- | 1.713 | 29.0 | 174 | 1.6663 | 0.2667 |
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- | 1.7082 | 30.0 | 180 | 1.6661 | 0.2667 |
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- | 1.7082 | 31.0 | 186 | 1.6659 | 0.2667 |
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- | 1.7547 | 32.0 | 192 | 1.6657 | 0.2667 |
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- | 1.7547 | 33.0 | 198 | 1.6656 | 0.2667 |
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- | 1.6513 | 34.0 | 204 | 1.6654 | 0.2667 |
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- | 1.7419 | 35.0 | 210 | 1.6653 | 0.2667 |
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- | 1.7419 | 36.0 | 216 | 1.6652 | 0.2667 |
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- | 1.7087 | 37.0 | 222 | 1.6652 | 0.2667 |
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- | 1.7087 | 38.0 | 228 | 1.6651 | 0.2667 |
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- | 1.6162 | 39.0 | 234 | 1.6651 | 0.2667 |
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- | 1.6974 | 40.0 | 240 | 1.6651 | 0.2667 |
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- | 1.6974 | 41.0 | 246 | 1.6650 | 0.2667 |
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- | 1.7234 | 42.0 | 252 | 1.6650 | 0.2667 |
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- | 1.7234 | 43.0 | 258 | 1.6650 | 0.2667 |
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- | 1.7326 | 44.0 | 264 | 1.6650 | 0.2667 |
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- | 1.6725 | 45.0 | 270 | 1.6650 | 0.2667 |
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- | 1.6725 | 46.0 | 276 | 1.6650 | 0.2667 |
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- | 1.6993 | 47.0 | 282 | 1.6650 | 0.2667 |
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- | 1.6993 | 48.0 | 288 | 1.6650 | 0.2667 |
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- | 1.6816 | 49.0 | 294 | 1.6650 | 0.2667 |
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- | 1.7255 | 50.0 | 300 | 1.6650 | 0.2667 |
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  ### Framework versions
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- - Transformers 4.35.0
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  - Pytorch 2.1.0+cu118
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- - Datasets 2.14.6
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- - Tokenizers 0.14.1
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.2
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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: 1.6938
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+ - Accuracy: 0.2
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 6 | 1.6986 | 0.2 |
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+ | 1.6333 | 2.0 | 12 | 1.6983 | 0.2 |
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+ | 1.6333 | 3.0 | 18 | 1.6981 | 0.2 |
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+ | 1.6088 | 4.0 | 24 | 1.6979 | 0.2 |
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+ | 1.6296 | 5.0 | 30 | 1.6976 | 0.2 |
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+ | 1.6296 | 6.0 | 36 | 1.6974 | 0.2 |
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+ | 1.6252 | 7.0 | 42 | 1.6972 | 0.2 |
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+ | 1.6252 | 8.0 | 48 | 1.6970 | 0.2 |
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+ | 1.6833 | 9.0 | 54 | 1.6968 | 0.2 |
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+ | 1.5983 | 10.0 | 60 | 1.6965 | 0.2 |
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+ | 1.5983 | 11.0 | 66 | 1.6964 | 0.2 |
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+ | 1.61 | 12.0 | 72 | 1.6962 | 0.2 |
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+ | 1.61 | 13.0 | 78 | 1.6960 | 0.2 |
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+ | 1.6125 | 14.0 | 84 | 1.6958 | 0.2 |
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+ | 1.6595 | 15.0 | 90 | 1.6957 | 0.2 |
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+ | 1.6595 | 16.0 | 96 | 1.6956 | 0.2 |
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+ | 1.6372 | 17.0 | 102 | 1.6954 | 0.2 |
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+ | 1.6372 | 18.0 | 108 | 1.6953 | 0.2 |
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+ | 1.6292 | 19.0 | 114 | 1.6951 | 0.2 |
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+ | 1.6414 | 20.0 | 120 | 1.6950 | 0.2 |
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+ | 1.6414 | 21.0 | 126 | 1.6949 | 0.2 |
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+ | 1.6168 | 22.0 | 132 | 1.6948 | 0.2 |
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+ | 1.6168 | 23.0 | 138 | 1.6947 | 0.2 |
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+ | 1.6445 | 24.0 | 144 | 1.6946 | 0.2 |
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+ | 1.6172 | 25.0 | 150 | 1.6945 | 0.2 |
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+ | 1.6172 | 26.0 | 156 | 1.6944 | 0.2 |
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+ | 1.5925 | 27.0 | 162 | 1.6944 | 0.2 |
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+ | 1.5925 | 28.0 | 168 | 1.6943 | 0.2 |
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+ | 1.6351 | 29.0 | 174 | 1.6942 | 0.2 |
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+ | 1.6161 | 30.0 | 180 | 1.6941 | 0.2 |
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+ | 1.6161 | 31.0 | 186 | 1.6941 | 0.2 |
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+ | 1.6095 | 32.0 | 192 | 1.6940 | 0.2 |
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+ | 1.6095 | 33.0 | 198 | 1.6940 | 0.2 |
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+ | 1.6215 | 34.0 | 204 | 1.6939 | 0.2 |
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+ | 1.6213 | 35.0 | 210 | 1.6939 | 0.2 |
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+ | 1.6213 | 36.0 | 216 | 1.6939 | 0.2 |
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+ | 1.6372 | 37.0 | 222 | 1.6938 | 0.2 |
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+ | 1.6372 | 38.0 | 228 | 1.6938 | 0.2 |
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+ | 1.6199 | 39.0 | 234 | 1.6938 | 0.2 |
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+ | 1.6087 | 40.0 | 240 | 1.6938 | 0.2 |
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+ | 1.6087 | 41.0 | 246 | 1.6938 | 0.2 |
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+ | 1.6309 | 42.0 | 252 | 1.6938 | 0.2 |
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+ | 1.6309 | 43.0 | 258 | 1.6938 | 0.2 |
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+ | 1.6203 | 44.0 | 264 | 1.6938 | 0.2 |
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+ | 1.6564 | 45.0 | 270 | 1.6938 | 0.2 |
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+ | 1.6564 | 46.0 | 276 | 1.6938 | 0.2 |
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+ | 1.6178 | 47.0 | 282 | 1.6938 | 0.2 |
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+ | 1.6178 | 48.0 | 288 | 1.6938 | 0.2 |
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+ | 1.6557 | 49.0 | 294 | 1.6938 | 0.2 |
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+ | 1.6181 | 50.0 | 300 | 1.6938 | 0.2 |
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  ### Framework versions
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+ - Transformers 4.35.2
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  - Pytorch 2.1.0+cu118
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+ - Datasets 2.15.0
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+ - Tokenizers 0.15.0
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