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hushem_5x_deit_tiny_rms_001_fold4

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  1. README.md +50 -50
  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: 0.7619047619047619
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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: 1.0081
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- - Accuracy: 0.7619
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  ## Model description
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@@ -68,53 +68,53 @@ The following hyperparameters were used during training:
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  | 2.1506 | 1.0 | 28 | 2.1514 | 0.2381 |
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  | 1.4805 | 2.0 | 56 | 1.6187 | 0.2619 |
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  | 1.4792 | 3.0 | 84 | 1.5112 | 0.2619 |
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- | 1.5148 | 4.0 | 112 | 1.3547 | 0.3095 |
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- | 1.3547 | 5.0 | 140 | 1.2950 | 0.4524 |
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- | 1.3383 | 6.0 | 168 | 1.9263 | 0.3095 |
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- | 1.1739 | 7.0 | 196 | 1.3815 | 0.4524 |
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- | 1.1304 | 8.0 | 224 | 1.0369 | 0.4524 |
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- | 1.0728 | 9.0 | 252 | 1.2115 | 0.3095 |
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- | 1.0918 | 10.0 | 280 | 1.2637 | 0.5476 |
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- | 0.9652 | 11.0 | 308 | 0.7655 | 0.7381 |
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- | 1.031 | 12.0 | 336 | 0.8541 | 0.5952 |
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- | 1.015 | 13.0 | 364 | 0.9556 | 0.6905 |
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- | 0.9433 | 14.0 | 392 | 0.7779 | 0.7381 |
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- | 0.8903 | 15.0 | 420 | 0.6510 | 0.7381 |
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- | 0.9021 | 16.0 | 448 | 0.7083 | 0.7857 |
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- | 0.8924 | 17.0 | 476 | 0.7764 | 0.7857 |
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- | 0.8626 | 18.0 | 504 | 0.7087 | 0.7619 |
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- | 1.0202 | 19.0 | 532 | 0.6940 | 0.7143 |
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- | 0.9027 | 20.0 | 560 | 0.8920 | 0.5 |
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- | 0.8032 | 21.0 | 588 | 0.7287 | 0.6429 |
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- | 0.8326 | 22.0 | 616 | 0.8725 | 0.5952 |
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- | 0.8471 | 23.0 | 644 | 0.6940 | 0.7381 |
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- | 0.8195 | 24.0 | 672 | 0.7230 | 0.7619 |
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- | 0.7476 | 25.0 | 700 | 0.7783 | 0.6905 |
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- | 0.7904 | 26.0 | 728 | 0.8597 | 0.6429 |
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- | 0.8241 | 27.0 | 756 | 0.7608 | 0.7381 |
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- | 0.7804 | 28.0 | 784 | 0.6937 | 0.7619 |
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- | 0.7557 | 29.0 | 812 | 0.9018 | 0.5952 |
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- | 0.7596 | 30.0 | 840 | 0.7813 | 0.7381 |
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- | 0.7112 | 31.0 | 868 | 0.7351 | 0.7143 |
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- | 0.7283 | 32.0 | 896 | 0.7485 | 0.7381 |
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- | 0.7264 | 33.0 | 924 | 0.8754 | 0.6905 |
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- | 0.7551 | 34.0 | 952 | 0.8169 | 0.7381 |
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- | 0.7766 | 35.0 | 980 | 0.7354 | 0.7619 |
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- | 0.6605 | 36.0 | 1008 | 0.7382 | 0.7857 |
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- | 0.6749 | 37.0 | 1036 | 0.7891 | 0.7143 |
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- | 0.6581 | 38.0 | 1064 | 0.8904 | 0.7381 |
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- | 0.6626 | 39.0 | 1092 | 0.8840 | 0.7381 |
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- | 0.5939 | 40.0 | 1120 | 0.7986 | 0.7619 |
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- | 0.5616 | 41.0 | 1148 | 0.8596 | 0.7381 |
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- | 0.6192 | 42.0 | 1176 | 0.8032 | 0.7857 |
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- | 0.4997 | 43.0 | 1204 | 0.9424 | 0.7857 |
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- | 0.4722 | 44.0 | 1232 | 0.8405 | 0.7619 |
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- | 0.3642 | 45.0 | 1260 | 1.0078 | 0.8095 |
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- | 0.4374 | 46.0 | 1288 | 0.9552 | 0.7381 |
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- | 0.4002 | 47.0 | 1316 | 0.9711 | 0.7381 |
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- | 0.3914 | 48.0 | 1344 | 1.0075 | 0.7619 |
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- | 0.3271 | 49.0 | 1372 | 1.0081 | 0.7619 |
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- | 0.3394 | 50.0 | 1400 | 1.0081 | 0.7619 |
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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: 0.6904761904761905
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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: 1.2679
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+ - Accuracy: 0.6905
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  ## Model description
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  | 2.1506 | 1.0 | 28 | 2.1514 | 0.2381 |
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  | 1.4805 | 2.0 | 56 | 1.6187 | 0.2619 |
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  | 1.4792 | 3.0 | 84 | 1.5112 | 0.2619 |
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+ | 1.5148 | 4.0 | 112 | 1.3546 | 0.3095 |
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+ | 1.3804 | 5.0 | 140 | 1.3723 | 0.4286 |
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+ | 1.4296 | 6.0 | 168 | 1.1490 | 0.4048 |
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+ | 1.1847 | 7.0 | 196 | 1.3299 | 0.4524 |
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+ | 1.1564 | 8.0 | 224 | 1.0799 | 0.4762 |
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+ | 1.0992 | 9.0 | 252 | 1.1631 | 0.5 |
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+ | 1.0863 | 10.0 | 280 | 1.1300 | 0.4524 |
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+ | 1.0126 | 11.0 | 308 | 0.9131 | 0.5 |
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+ | 1.0272 | 12.0 | 336 | 0.9239 | 0.5 |
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+ | 0.9747 | 13.0 | 364 | 0.9521 | 0.6667 |
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+ | 0.9219 | 14.0 | 392 | 0.8729 | 0.7619 |
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+ | 0.8522 | 15.0 | 420 | 0.6286 | 0.7381 |
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+ | 0.8968 | 16.0 | 448 | 0.8515 | 0.6429 |
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+ | 0.8266 | 17.0 | 476 | 0.8301 | 0.6429 |
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+ | 0.8581 | 18.0 | 504 | 1.0046 | 0.5476 |
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+ | 0.8265 | 19.0 | 532 | 0.8082 | 0.6429 |
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+ | 0.8594 | 20.0 | 560 | 0.8196 | 0.6190 |
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+ | 0.7439 | 21.0 | 588 | 0.7591 | 0.6190 |
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+ | 0.7899 | 22.0 | 616 | 0.8303 | 0.5952 |
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+ | 0.8223 | 23.0 | 644 | 0.6299 | 0.7143 |
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+ | 0.8203 | 24.0 | 672 | 0.7361 | 0.7143 |
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+ | 0.7414 | 25.0 | 700 | 0.7251 | 0.7143 |
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+ | 0.6879 | 26.0 | 728 | 0.8771 | 0.6905 |
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+ | 0.8008 | 27.0 | 756 | 0.8469 | 0.5714 |
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+ | 0.7402 | 28.0 | 784 | 0.6058 | 0.7857 |
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+ | 0.7223 | 29.0 | 812 | 0.8210 | 0.6905 |
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+ | 0.7302 | 30.0 | 840 | 0.8614 | 0.7143 |
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+ | 0.7098 | 31.0 | 868 | 0.9312 | 0.7143 |
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+ | 0.7044 | 32.0 | 896 | 0.8159 | 0.7143 |
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+ | 0.7096 | 33.0 | 924 | 0.9197 | 0.6905 |
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+ | 0.6854 | 34.0 | 952 | 0.8631 | 0.6190 |
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+ | 0.7442 | 35.0 | 980 | 0.8324 | 0.6667 |
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+ | 0.6271 | 36.0 | 1008 | 0.8632 | 0.7381 |
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+ | 0.6052 | 37.0 | 1036 | 0.8753 | 0.7143 |
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+ | 0.6189 | 38.0 | 1064 | 1.0917 | 0.7381 |
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+ | 0.5817 | 39.0 | 1092 | 0.9635 | 0.6429 |
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+ | 0.5324 | 40.0 | 1120 | 1.0245 | 0.6667 |
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+ | 0.5312 | 41.0 | 1148 | 1.1733 | 0.6905 |
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+ | 0.5538 | 42.0 | 1176 | 1.0809 | 0.7143 |
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+ | 0.4355 | 43.0 | 1204 | 1.0395 | 0.6667 |
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+ | 0.3909 | 44.0 | 1232 | 1.1631 | 0.6667 |
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+ | 0.301 | 45.0 | 1260 | 1.2110 | 0.6667 |
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+ | 0.3678 | 46.0 | 1288 | 1.2357 | 0.6905 |
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+ | 0.3355 | 47.0 | 1316 | 1.2487 | 0.7143 |
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+ | 0.2983 | 48.0 | 1344 | 1.2713 | 0.6905 |
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+ | 0.2527 | 49.0 | 1372 | 1.2679 | 0.6905 |
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+ | 0.2761 | 50.0 | 1400 | 1.2679 | 0.6905 |
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  ### Framework versions
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