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hushem_5x_deit_small_rms_0001_fold1

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  1. README.md +53 -53
  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: 0.6
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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-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 3.7611
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- - Accuracy: 0.6
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  ## Model description
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@@ -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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- | 1.5779 | 1.0 | 27 | 1.3829 | 0.2444 |
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- | 1.3467 | 2.0 | 54 | 1.5035 | 0.3778 |
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- | 0.9626 | 3.0 | 81 | 2.4441 | 0.3556 |
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- | 0.7945 | 4.0 | 108 | 2.3990 | 0.3556 |
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- | 0.6604 | 5.0 | 135 | 1.2468 | 0.4667 |
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- | 0.4004 | 6.0 | 162 | 1.1567 | 0.6 |
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- | 0.275 | 7.0 | 189 | 1.1775 | 0.5556 |
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- | 0.2158 | 8.0 | 216 | 1.6538 | 0.5778 |
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- | 0.0925 | 9.0 | 243 | 2.6878 | 0.5111 |
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- | 0.0353 | 10.0 | 270 | 3.0520 | 0.5333 |
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- | 0.0379 | 11.0 | 297 | 2.6705 | 0.5333 |
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- | 0.0415 | 12.0 | 324 | 2.0632 | 0.5778 |
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- | 0.0009 | 13.0 | 351 | 2.6424 | 0.6 |
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- | 0.0044 | 14.0 | 378 | 3.1181 | 0.5778 |
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- | 0.0002 | 15.0 | 405 | 2.7922 | 0.5778 |
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- | 0.0001 | 16.0 | 432 | 2.9194 | 0.5778 |
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- | 0.0001 | 17.0 | 459 | 2.9907 | 0.5778 |
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- | 0.0001 | 18.0 | 486 | 3.0438 | 0.5778 |
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- | 0.0001 | 19.0 | 513 | 3.0900 | 0.5778 |
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- | 0.0001 | 20.0 | 540 | 3.1292 | 0.5778 |
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- | 0.0 | 21.0 | 567 | 3.1620 | 0.5778 |
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- | 0.0 | 22.0 | 594 | 3.1954 | 0.5778 |
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- | 0.0 | 23.0 | 621 | 3.2293 | 0.5778 |
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- | 0.0 | 24.0 | 648 | 3.2621 | 0.5778 |
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- | 0.0 | 25.0 | 675 | 3.2901 | 0.5778 |
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- | 0.0 | 26.0 | 702 | 3.3182 | 0.5778 |
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- | 0.0 | 27.0 | 729 | 3.3448 | 0.5778 |
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- | 0.0 | 28.0 | 756 | 3.3739 | 0.6 |
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- | 0.0 | 29.0 | 783 | 3.4020 | 0.6 |
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- | 0.0 | 30.0 | 810 | 3.4283 | 0.6 |
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- | 0.0 | 31.0 | 837 | 3.4543 | 0.6 |
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- | 0.0 | 32.0 | 864 | 3.4814 | 0.6 |
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- | 0.0 | 33.0 | 891 | 3.5064 | 0.6 |
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- | 0.0 | 34.0 | 918 | 3.5302 | 0.6 |
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- | 0.0 | 35.0 | 945 | 3.5534 | 0.6 |
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- | 0.0 | 36.0 | 972 | 3.5768 | 0.6 |
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- | 0.0 | 37.0 | 999 | 3.5999 | 0.6 |
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- | 0.0 | 38.0 | 1026 | 3.6238 | 0.6 |
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- | 0.0 | 39.0 | 1053 | 3.6454 | 0.6 |
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- | 0.0 | 40.0 | 1080 | 3.6645 | 0.6 |
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- | 0.0 | 41.0 | 1107 | 3.6837 | 0.6 |
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- | 0.0 | 42.0 | 1134 | 3.7005 | 0.6 |
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- | 0.0 | 43.0 | 1161 | 3.7163 | 0.6 |
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- | 0.0 | 44.0 | 1188 | 3.7308 | 0.6 |
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- | 0.0 | 45.0 | 1215 | 3.7425 | 0.6 |
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- | 0.0 | 46.0 | 1242 | 3.7523 | 0.6 |
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- | 0.0 | 47.0 | 1269 | 3.7587 | 0.6 |
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- | 0.0 | 48.0 | 1296 | 3.7611 | 0.6 |
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- | 0.0 | 49.0 | 1323 | 3.7611 | 0.6 |
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- | 0.0 | 50.0 | 1350 | 3.7611 | 0.6 |
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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: 0.5333333333333333
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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-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 4.0359
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+ - Accuracy: 0.5333
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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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+ | 1.4419 | 1.0 | 27 | 1.3907 | 0.2444 |
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+ | 1.4324 | 2.0 | 54 | 1.5348 | 0.4222 |
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+ | 1.2448 | 3.0 | 81 | 1.2892 | 0.4444 |
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+ | 1.2278 | 4.0 | 108 | 2.0615 | 0.4222 |
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+ | 0.8744 | 5.0 | 135 | 1.2150 | 0.4 |
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+ | 0.7002 | 6.0 | 162 | 1.5857 | 0.4 |
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+ | 0.6664 | 7.0 | 189 | 1.1206 | 0.5111 |
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+ | 0.5543 | 8.0 | 216 | 2.0902 | 0.4 |
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+ | 0.4511 | 9.0 | 243 | 1.5223 | 0.5111 |
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+ | 0.3889 | 10.0 | 270 | 2.0931 | 0.4667 |
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+ | 0.3279 | 11.0 | 297 | 2.0153 | 0.5778 |
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+ | 0.1636 | 12.0 | 324 | 3.2794 | 0.4444 |
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+ | 0.1375 | 13.0 | 351 | 2.4712 | 0.5333 |
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+ | 0.0773 | 14.0 | 378 | 2.1584 | 0.5333 |
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+ | 0.0482 | 15.0 | 405 | 2.9775 | 0.4889 |
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+ | 0.022 | 16.0 | 432 | 3.2342 | 0.5111 |
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+ | 0.0125 | 17.0 | 459 | 3.3088 | 0.4889 |
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+ | 0.0285 | 18.0 | 486 | 2.2599 | 0.5556 |
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+ | 0.0004 | 19.0 | 513 | 3.3514 | 0.5111 |
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+ | 0.0002 | 20.0 | 540 | 3.3934 | 0.5111 |
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+ | 0.0001 | 21.0 | 567 | 3.4412 | 0.5111 |
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+ | 0.0001 | 22.0 | 594 | 3.4801 | 0.5111 |
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+ | 0.0001 | 23.0 | 621 | 3.5191 | 0.5111 |
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+ | 0.0001 | 24.0 | 648 | 3.5572 | 0.5111 |
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+ | 0.0001 | 25.0 | 675 | 3.5826 | 0.5333 |
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+ | 0.0001 | 26.0 | 702 | 3.6119 | 0.5333 |
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+ | 0.0001 | 27.0 | 729 | 3.6375 | 0.5333 |
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+ | 0.0 | 28.0 | 756 | 3.6635 | 0.5333 |
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+ | 0.0 | 29.0 | 783 | 3.6928 | 0.5333 |
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+ | 0.0 | 30.0 | 810 | 3.7145 | 0.5333 |
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+ | 0.0 | 31.0 | 837 | 3.7399 | 0.5333 |
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+ | 0.0 | 32.0 | 864 | 3.7653 | 0.5333 |
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+ | 0.0 | 33.0 | 891 | 3.7908 | 0.5333 |
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+ | 0.0 | 34.0 | 918 | 3.8148 | 0.5333 |
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+ | 0.0 | 35.0 | 945 | 3.8372 | 0.5333 |
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+ | 0.0 | 36.0 | 972 | 3.8570 | 0.5333 |
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+ | 0.0 | 37.0 | 999 | 3.8804 | 0.5333 |
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+ | 0.0 | 38.0 | 1026 | 3.9044 | 0.5333 |
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+ | 0.0 | 39.0 | 1053 | 3.9261 | 0.5333 |
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+ | 0.0 | 40.0 | 1080 | 3.9442 | 0.5333 |
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+ | 0.0 | 41.0 | 1107 | 3.9608 | 0.5333 |
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+ | 0.0 | 42.0 | 1134 | 3.9774 | 0.5333 |
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+ | 0.0 | 43.0 | 1161 | 3.9927 | 0.5333 |
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+ | 0.0 | 44.0 | 1188 | 4.0067 | 0.5333 |
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+ | 0.0 | 45.0 | 1215 | 4.0181 | 0.5333 |
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+ | 0.0 | 46.0 | 1242 | 4.0275 | 0.5333 |
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+ | 0.0 | 47.0 | 1269 | 4.0337 | 0.5333 |
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+ | 0.0 | 48.0 | 1296 | 4.0359 | 0.5333 |
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+ | 0.0 | 49.0 | 1323 | 4.0359 | 0.5333 |
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+ | 0.0 | 50.0 | 1350 | 4.0359 | 0.5333 |
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  ### Framework versions
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