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Prot10
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vit-base-patch16-224-for-pre_evaluation

Image Classification
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PyTorch
vit
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  1. README.md +34 -32
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.6126
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- - Accuracy: 0.4266
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  ## Model description
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@@ -52,39 +52,41 @@ 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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- | 1.6266 | 0.93 | 10 | 1.5308 | 0.3007 |
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- | 1.4973 | 1.95 | 21 | 1.5000 | 0.3124 |
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- | 1.4636 | 2.98 | 32 | 1.4730 | 0.3450 |
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- | 1.4185 | 4.0 | 43 | 1.5052 | 0.3054 |
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- | 1.4147 | 4.93 | 53 | 1.4456 | 0.3497 |
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- | 1.337 | 5.95 | 64 | 1.4736 | 0.3427 |
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- | 1.2869 | 6.98 | 75 | 1.4170 | 0.3800 |
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- | 1.241 | 8.0 | 86 | 1.5078 | 0.3730 |
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- | 1.2261 | 8.93 | 96 | 1.4629 | 0.3893 |
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- | 1.1967 | 9.95 | 107 | 1.4139 | 0.4103 |
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- | 1.1153 | 10.98 | 118 | 1.4338 | 0.4196 |
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- | 1.063 | 12.0 | 129 | 1.4643 | 0.3939 |
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- | 1.0434 | 12.93 | 139 | 1.4726 | 0.4079 |
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- | 0.9849 | 13.95 | 150 | 1.5287 | 0.4149 |
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- | 0.9285 | 14.98 | 161 | 1.5530 | 0.3986 |
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- | 0.8724 | 16.0 | 172 | 1.5016 | 0.3939 |
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- | 0.8063 | 16.93 | 182 | 1.5185 | 0.4056 |
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- | 0.8206 | 17.95 | 193 | 1.5448 | 0.4172 |
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- | 0.7396 | 18.98 | 204 | 1.5540 | 0.4033 |
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- | 0.7437 | 20.0 | 215 | 1.5796 | 0.4009 |
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- | 0.7103 | 20.93 | 225 | 1.6218 | 0.4033 |
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- | 0.6861 | 21.95 | 236 | 1.6126 | 0.4266 |
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- | 0.6798 | 22.98 | 247 | 1.6051 | 0.4266 |
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- | 0.6358 | 24.0 | 258 | 1.6141 | 0.4103 |
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- | 0.6189 | 24.93 | 268 | 1.6706 | 0.4056 |
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- | 0.6176 | 25.95 | 279 | 1.6404 | 0.4219 |
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- | 0.5756 | 26.98 | 290 | 1.6603 | 0.4172 |
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- | 0.5887 | 27.91 | 300 | 1.6627 | 0.4242 |
 
 
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  ### Framework versions
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- - Transformers 4.32.1
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  - Pytorch 2.0.1+cu118
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- - Datasets 2.14.4
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  - Tokenizers 0.13.3
 
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  This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.7374
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+ - Accuracy: 0.3736
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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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+ | 1.5774 | 0.98 | 16 | 1.5109 | 0.3022 |
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+ | 1.4794 | 1.97 | 32 | 1.4942 | 0.3242 |
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+ | 1.4536 | 2.95 | 48 | 1.4943 | 0.3187 |
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+ | 1.421 | 4.0 | 65 | 1.4247 | 0.3407 |
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+ | 1.3882 | 4.98 | 81 | 1.4944 | 0.3462 |
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+ | 1.3579 | 5.97 | 97 | 1.4180 | 0.3571 |
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+ | 1.2838 | 6.95 | 113 | 1.4693 | 0.3681 |
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+ | 1.2695 | 8.0 | 130 | 1.4359 | 0.3434 |
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+ | 1.2016 | 8.98 | 146 | 1.4656 | 0.3599 |
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+ | 1.2087 | 9.97 | 162 | 1.4550 | 0.3379 |
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+ | 1.206 | 10.95 | 178 | 1.5056 | 0.3516 |
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+ | 1.1236 | 12.0 | 195 | 1.5003 | 0.3434 |
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+ | 1.0534 | 12.98 | 211 | 1.5193 | 0.3269 |
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+ | 1.0024 | 13.97 | 227 | 1.4890 | 0.3681 |
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+ | 0.9767 | 14.95 | 243 | 1.5628 | 0.3434 |
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+ | 0.9201 | 16.0 | 260 | 1.6306 | 0.3516 |
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+ | 0.9136 | 16.98 | 276 | 1.5715 | 0.3626 |
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+ | 0.8566 | 17.97 | 292 | 1.5966 | 0.3654 |
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+ | 0.8273 | 18.95 | 308 | 1.6048 | 0.3929 |
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+ | 0.7825 | 20.0 | 325 | 1.6175 | 0.3846 |
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+ | 0.736 | 20.98 | 341 | 1.6526 | 0.3929 |
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+ | 0.7008 | 21.97 | 357 | 1.6563 | 0.3736 |
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+ | 0.6714 | 22.95 | 373 | 1.7319 | 0.3901 |
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+ | 0.7039 | 24.0 | 390 | 1.6866 | 0.3929 |
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+ | 0.628 | 24.98 | 406 | 1.7023 | 0.3791 |
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+ | 0.6182 | 25.97 | 422 | 1.7301 | 0.3901 |
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+ | 0.5957 | 26.95 | 438 | 1.7157 | 0.3846 |
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+ | 0.5973 | 28.0 | 455 | 1.7478 | 0.3709 |
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+ | 0.5655 | 28.98 | 471 | 1.7377 | 0.3736 |
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+ | 0.5631 | 29.54 | 480 | 1.7374 | 0.3736 |
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  ### Framework versions
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+ - Transformers 4.33.1
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  - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.5
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  - Tokenizers 0.13.3
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