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square_run_second_vote_full_pic_stratified

Image Classification
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vit
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  1. README.md +100 -0
  2. all_results.json +22 -0
  3. config.json +42 -0
  4. eval_results.json +17 -0
  5. model.safetensors +3 -0
  6. preprocessor_config.json +26 -0
  7. runs/Feb17_18-19-19_modal/events.out.tfevents.1739816360.modal.2.0 +3 -0
  8. runs/Feb17_18-19-19_modal/events.out.tfevents.1739816360.modal.2.1 +3 -0
  9. runs/Feb17_18-19-19_modal/events.out.tfevents.1739816584.modal.2.2 +3 -0
  10. runs/Feb17_18-19-19_modal/events.out.tfevents.1739816584.modal.2.3 +3 -0
  11. train_results.json +8 -0
  12. trainer_state.json +0 -0
  13. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: google/vit-base-patch16-224
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: square_run_second_vote_full_pic_stratified
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+ results: []
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+ ---
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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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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # square_run_second_vote_full_pic_stratified
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+
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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 an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.8527
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+ - F1 Macro: 0.6046
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+ - F1 Micro: 0.7121
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+ - F1 Weighted: 0.6979
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+ - Precision Macro: 0.6148
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+ - Precision Micro: 0.7121
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+ - Precision Weighted: 0.7042
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+ - Recall Macro: 0.6157
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+ - Recall Micro: 0.7121
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+ - Recall Weighted: 0.7121
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+ - Accuracy: 0.7121
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 30
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Micro | F1 Weighted | Precision Macro | Precision Micro | Precision Weighted | Recall Macro | Recall Micro | Recall Weighted | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|:---------------:|:---------------:|:------------------:|:------------:|:------------:|:---------------:|:--------:|
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+ | 1.8233 | 1.0 | 58 | 1.8311 | 0.1942 | 0.2727 | 0.2274 | 0.1804 | 0.2727 | 0.2139 | 0.2367 | 0.2727 | 0.2727 | 0.2727 |
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+ | 1.8698 | 2.0 | 116 | 1.9889 | 0.0840 | 0.1742 | 0.0989 | 0.0796 | 0.1742 | 0.1011 | 0.1719 | 0.1742 | 0.1742 | 0.1742 |
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+ | 1.9152 | 3.0 | 174 | 1.7868 | 0.1549 | 0.2727 | 0.1775 | 0.3078 | 0.2727 | 0.3022 | 0.2068 | 0.2727 | 0.2727 | 0.2727 |
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+ | 1.6147 | 4.0 | 232 | 1.9341 | 0.2055 | 0.2955 | 0.2523 | 0.3212 | 0.2955 | 0.3791 | 0.2645 | 0.2955 | 0.2955 | 0.2955 |
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+ | 1.6414 | 5.0 | 290 | 1.4736 | 0.3384 | 0.4470 | 0.3905 | 0.3487 | 0.4470 | 0.3844 | 0.3667 | 0.4470 | 0.4470 | 0.4470 |
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+ | 1.1299 | 6.0 | 348 | 1.2117 | 0.4394 | 0.5227 | 0.5100 | 0.4779 | 0.5227 | 0.5389 | 0.4409 | 0.5227 | 0.5227 | 0.5227 |
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+ | 1.493 | 7.0 | 406 | 1.3023 | 0.4501 | 0.5227 | 0.5130 | 0.4975 | 0.5227 | 0.5811 | 0.4699 | 0.5227 | 0.5227 | 0.5227 |
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+ | 1.191 | 8.0 | 464 | 1.1375 | 0.5136 | 0.6136 | 0.5937 | 0.5140 | 0.6136 | 0.5852 | 0.5227 | 0.6136 | 0.6136 | 0.6136 |
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+ | 1.6657 | 9.0 | 522 | 0.9972 | 0.5421 | 0.6439 | 0.6344 | 0.5400 | 0.6439 | 0.6329 | 0.5526 | 0.6439 | 0.6439 | 0.6439 |
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+ | 0.6272 | 10.0 | 580 | 1.1733 | 0.4743 | 0.5833 | 0.5586 | 0.4990 | 0.5833 | 0.5887 | 0.4983 | 0.5833 | 0.5833 | 0.5833 |
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+ | 0.3887 | 11.0 | 638 | 1.2098 | 0.4849 | 0.5833 | 0.5713 | 0.4956 | 0.5833 | 0.5931 | 0.5094 | 0.5833 | 0.5833 | 0.5833 |
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+ | 0.5232 | 12.0 | 696 | 1.1906 | 0.5205 | 0.6212 | 0.6061 | 0.5470 | 0.6212 | 0.6370 | 0.5378 | 0.6212 | 0.6212 | 0.6212 |
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+ | 1.1531 | 13.0 | 754 | 1.1958 | 0.5960 | 0.6439 | 0.6364 | 0.6959 | 0.6439 | 0.6619 | 0.5765 | 0.6439 | 0.6439 | 0.6439 |
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+ | 0.4566 | 14.0 | 812 | 1.2707 | 0.5381 | 0.6061 | 0.5919 | 0.5768 | 0.6061 | 0.6055 | 0.5356 | 0.6061 | 0.6061 | 0.6061 |
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+ | 0.6865 | 15.0 | 870 | 1.3936 | 0.5478 | 0.6364 | 0.6304 | 0.5668 | 0.6364 | 0.6634 | 0.5658 | 0.6364 | 0.6364 | 0.6364 |
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+ | 0.4421 | 16.0 | 928 | 1.3080 | 0.5732 | 0.6591 | 0.6616 | 0.5855 | 0.6591 | 0.6781 | 0.5718 | 0.6591 | 0.6591 | 0.6591 |
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+ | 0.3093 | 17.0 | 986 | 1.7662 | 0.4753 | 0.5682 | 0.5524 | 0.5212 | 0.5682 | 0.6010 | 0.4840 | 0.5682 | 0.5682 | 0.5682 |
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+ | 0.134 | 18.0 | 1044 | 1.4813 | 0.5427 | 0.6364 | 0.6250 | 0.5700 | 0.6364 | 0.6476 | 0.5510 | 0.6364 | 0.6364 | 0.6364 |
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+ | 0.0406 | 19.0 | 1102 | 1.5180 | 0.5583 | 0.6515 | 0.6354 | 0.5572 | 0.6515 | 0.6338 | 0.5736 | 0.6515 | 0.6515 | 0.6515 |
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+ | 0.0198 | 20.0 | 1160 | 1.8253 | 0.5403 | 0.6212 | 0.6226 | 0.5579 | 0.6212 | 0.6497 | 0.5487 | 0.6212 | 0.6212 | 0.6212 |
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+ | 0.0054 | 21.0 | 1218 | 1.6285 | 0.5574 | 0.6515 | 0.6478 | 0.5722 | 0.6515 | 0.6595 | 0.5596 | 0.6515 | 0.6515 | 0.6515 |
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+ | 0.2816 | 22.0 | 1276 | 1.7743 | 0.5174 | 0.6212 | 0.6028 | 0.5400 | 0.6212 | 0.6203 | 0.5257 | 0.6212 | 0.6212 | 0.6212 |
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+ | 0.0076 | 23.0 | 1334 | 1.7558 | 0.5353 | 0.6212 | 0.6174 | 0.5506 | 0.6212 | 0.6324 | 0.5389 | 0.6212 | 0.6212 | 0.6212 |
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+ | 0.0046 | 24.0 | 1392 | 1.7770 | 0.5518 | 0.6364 | 0.6346 | 0.5720 | 0.6364 | 0.6581 | 0.5580 | 0.6364 | 0.6364 | 0.6364 |
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+ | 0.0018 | 25.0 | 1450 | 1.5917 | 0.5926 | 0.6818 | 0.6812 | 0.6030 | 0.6818 | 0.6864 | 0.5869 | 0.6818 | 0.6818 | 0.6818 |
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+ | 0.0041 | 26.0 | 1508 | 1.7247 | 0.5866 | 0.6667 | 0.6725 | 0.6022 | 0.6667 | 0.6874 | 0.5788 | 0.6667 | 0.6667 | 0.6667 |
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+ | 0.0013 | 27.0 | 1566 | 1.6674 | 0.5977 | 0.6894 | 0.6852 | 0.6010 | 0.6894 | 0.6861 | 0.5997 | 0.6894 | 0.6894 | 0.6894 |
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+ | 0.0022 | 28.0 | 1624 | 1.7056 | 0.5938 | 0.6818 | 0.6794 | 0.5964 | 0.6818 | 0.6828 | 0.5975 | 0.6818 | 0.6818 | 0.6818 |
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+ | 0.001 | 29.0 | 1682 | 1.6834 | 0.5978 | 0.6894 | 0.6849 | 0.5975 | 0.6894 | 0.6828 | 0.6006 | 0.6894 | 0.6894 | 0.6894 |
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+ | 0.0006 | 30.0 | 1740 | 1.6730 | 0.6075 | 0.6970 | 0.6932 | 0.6149 | 0.6970 | 0.6968 | 0.6081 | 0.6970 | 0.6970 | 0.6970 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.49.0
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+ - Pytorch 2.6.0+cu124
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+ - Datasets 3.3.1
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+ - Tokenizers 0.21.0
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