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convnext-tiny-224-finetuned-biopsy

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convnext
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  1. README.md +113 -0
  2. model.safetensors +1 -1
  3. runs/Oct25_19-18-26_ba9aa54aa265/events.out.tfevents.1729883933.ba9aa54aa265.466.0 +2 -2
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: facebook/convnext-tiny-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: convnext-tiny-224-finetuned-biopsy
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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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+ # convnext-tiny-224-finetuned-biopsy
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+
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+ This model is a fine-tuned version of [facebook/convnext-tiny-224](https://huggingface.co/facebook/convnext-tiny-224) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0655
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+ - Accuracy: 0.9765
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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: 5e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 128
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 50
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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 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 1.2488 | 1.0 | 42 | 1.1914 | 0.5360 |
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+ | 0.9265 | 2.0 | 84 | 0.8634 | 0.5544 |
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+ | 0.5701 | 3.0 | 126 | 0.4834 | 0.8543 |
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+ | 0.4041 | 4.0 | 168 | 0.2996 | 0.9213 |
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+ | 0.2747 | 5.0 | 210 | 0.2743 | 0.9146 |
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+ | 0.2518 | 6.0 | 252 | 0.1826 | 0.9497 |
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+ | 0.2363 | 7.0 | 294 | 0.1731 | 0.9497 |
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+ | 0.1782 | 8.0 | 336 | 0.1870 | 0.9363 |
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+ | 0.2122 | 9.0 | 378 | 0.1327 | 0.9615 |
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+ | 0.1856 | 10.0 | 420 | 0.2082 | 0.9313 |
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+ | 0.1736 | 11.0 | 462 | 0.1306 | 0.9564 |
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+ | 0.1423 | 12.0 | 504 | 0.0989 | 0.9732 |
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+ | 0.1296 | 13.0 | 546 | 0.0949 | 0.9732 |
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+ | 0.1158 | 14.0 | 588 | 0.1084 | 0.9631 |
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+ | 0.1383 | 15.0 | 630 | 0.0865 | 0.9715 |
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+ | 0.1384 | 16.0 | 672 | 0.0879 | 0.9715 |
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+ | 0.0924 | 17.0 | 714 | 0.0758 | 0.9782 |
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+ | 0.0966 | 18.0 | 756 | 0.0866 | 0.9682 |
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+ | 0.1324 | 19.0 | 798 | 0.0876 | 0.9715 |
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+ | 0.0995 | 20.0 | 840 | 0.0990 | 0.9648 |
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+ | 0.083 | 21.0 | 882 | 0.0911 | 0.9698 |
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+ | 0.082 | 22.0 | 924 | 0.0816 | 0.9799 |
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+ | 0.1038 | 23.0 | 966 | 0.1453 | 0.9430 |
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+ | 0.0751 | 24.0 | 1008 | 0.0877 | 0.9732 |
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+ | 0.0733 | 25.0 | 1050 | 0.0878 | 0.9682 |
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+ | 0.0813 | 26.0 | 1092 | 0.0688 | 0.9816 |
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+ | 0.0788 | 27.0 | 1134 | 0.0732 | 0.9782 |
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+ | 0.0617 | 28.0 | 1176 | 0.0722 | 0.9749 |
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+ | 0.0568 | 29.0 | 1218 | 0.0883 | 0.9648 |
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+ | 0.0701 | 30.0 | 1260 | 0.0703 | 0.9765 |
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+ | 0.0535 | 31.0 | 1302 | 0.0792 | 0.9782 |
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+ | 0.0716 | 32.0 | 1344 | 0.0684 | 0.9799 |
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+ | 0.0419 | 33.0 | 1386 | 0.0666 | 0.9816 |
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+ | 0.054 | 34.0 | 1428 | 0.0768 | 0.9749 |
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+ | 0.0332 | 35.0 | 1470 | 0.0717 | 0.9799 |
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+ | 0.0524 | 36.0 | 1512 | 0.1067 | 0.9715 |
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+ | 0.0372 | 37.0 | 1554 | 0.0604 | 0.9816 |
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+ | 0.0692 | 38.0 | 1596 | 0.0579 | 0.9799 |
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+ | 0.038 | 39.0 | 1638 | 0.0824 | 0.9732 |
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+ | 0.0524 | 40.0 | 1680 | 0.0635 | 0.9765 |
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+ | 0.0429 | 41.0 | 1722 | 0.0644 | 0.9816 |
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+ | 0.0705 | 42.0 | 1764 | 0.0747 | 0.9765 |
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+ | 0.0325 | 43.0 | 1806 | 0.0685 | 0.9816 |
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+ | 0.0446 | 44.0 | 1848 | 0.0683 | 0.9782 |
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+ | 0.0439 | 45.0 | 1890 | 0.0707 | 0.9749 |
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+ | 0.0346 | 46.0 | 1932 | 0.0642 | 0.9782 |
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+ | 0.0504 | 47.0 | 1974 | 0.0654 | 0.9799 |
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+ | 0.0379 | 48.0 | 2016 | 0.0651 | 0.9765 |
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+ | 0.0433 | 49.0 | 2058 | 0.0654 | 0.9765 |
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+ | 0.0337 | 50.0 | 2100 | 0.0655 | 0.9765 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.2
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+ - Pytorch 2.5.0+cu121
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+ - Datasets 3.0.2
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+ - Tokenizers 0.19.1
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