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README.md ADDED
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+ ---
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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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+ - precision
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+ - recall
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+ - f1
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+ model-index:
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+ - name: vit-epsilon-1e-7
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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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+ # vit-epsilon-1e-7
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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: 0.6523
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+ - Accuracy: 0.8714
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+ - Precision: 0.8675
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+ - Recall: 0.8714
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+ - F1: 0.8677
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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: 16
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.99) and epsilon=1e-07
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_steps: 1733
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+ - num_epochs: 100
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | 1.765 | 1.0 | 321 | 0.9570 | 0.6917 | 0.6487 | 0.6917 | 0.6531 |
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+ | 1.1815 | 2.0 | 642 | 0.6949 | 0.7559 | 0.7315 | 0.7559 | 0.7314 |
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+ | 1.0605 | 3.0 | 963 | 0.6213 | 0.7715 | 0.7649 | 0.7715 | 0.7530 |
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+ | 1.0147 | 4.0 | 1284 | 0.5768 | 0.7732 | 0.7807 | 0.7732 | 0.7734 |
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+ | 0.93 | 5.0 | 1605 | 0.6572 | 0.7587 | 0.7940 | 0.7587 | 0.7662 |
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+ | 0.9793 | 6.0 | 1926 | 0.6165 | 0.7701 | 0.7940 | 0.7701 | 0.7742 |
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+ | 0.8662 | 7.0 | 2247 | 0.6535 | 0.7240 | 0.8098 | 0.7240 | 0.7456 |
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+ | 0.7767 | 8.0 | 2568 | 0.5813 | 0.7566 | 0.8124 | 0.7566 | 0.7733 |
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+ | 0.7572 | 9.0 | 2889 | 0.5385 | 0.8145 | 0.8131 | 0.8145 | 0.8114 |
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+ | 0.7003 | 10.0 | 3210 | 0.5355 | 0.8027 | 0.8276 | 0.8027 | 0.8093 |
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+ | 0.6316 | 11.0 | 3531 | 0.6285 | 0.7653 | 0.8322 | 0.7653 | 0.7816 |
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+ | 0.5723 | 12.0 | 3852 | 0.5775 | 0.8017 | 0.8279 | 0.8017 | 0.8105 |
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+ | 0.4717 | 13.0 | 4173 | 0.5348 | 0.8350 | 0.8391 | 0.8350 | 0.8350 |
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+ | 0.4472 | 14.0 | 4494 | 0.5469 | 0.8239 | 0.8442 | 0.8239 | 0.8299 |
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+ | 0.3764 | 15.0 | 4815 | 0.5738 | 0.8291 | 0.8501 | 0.8291 | 0.8355 |
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+ | 0.3346 | 16.0 | 5136 | 0.5368 | 0.8436 | 0.8512 | 0.8436 | 0.8461 |
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+ | 0.2826 | 17.0 | 5457 | 0.5510 | 0.8474 | 0.8489 | 0.8474 | 0.8468 |
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+ | 0.2659 | 18.0 | 5778 | 0.5467 | 0.8547 | 0.8560 | 0.8547 | 0.8549 |
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+ | 0.2545 | 19.0 | 6099 | 0.6156 | 0.8433 | 0.8617 | 0.8433 | 0.8487 |
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+ | 0.2123 | 20.0 | 6420 | 0.6871 | 0.8429 | 0.8499 | 0.8429 | 0.8427 |
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+ | 0.1655 | 21.0 | 6741 | 0.6139 | 0.8610 | 0.8552 | 0.8610 | 0.8567 |
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+ | 0.1246 | 22.0 | 7062 | 0.6129 | 0.8675 | 0.8681 | 0.8675 | 0.8677 |
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+ | 0.1394 | 23.0 | 7383 | 0.6523 | 0.8714 | 0.8675 | 0.8714 | 0.8677 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.40.0.dev0
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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