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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: barghavani/Cheese_xray |
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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: Cheese_X_ray |
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results: [] |
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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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# Cheese_X_ray |
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This model is a fine-tuned version of [barghavani/Cheese_xray](https://huggingface.co/barghavani/Cheese_xray) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1890 |
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- Accuracy: 0.9381 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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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: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-------:|:----:|:---------------:|:--------:| |
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| 0.5579 | 0.9882 | 63 | 0.5524 | 0.7062 | |
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| 0.4491 | 1.9922 | 127 | 0.4218 | 0.7062 | |
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| 0.3646 | 2.9961 | 191 | 0.3928 | 0.7440 | |
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| 0.3419 | 4.0 | 255 | 0.3827 | 0.8110 | |
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| 0.3546 | 4.9882 | 318 | 0.3530 | 0.8608 | |
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| 0.3745 | 5.9922 | 382 | 0.3298 | 0.8814 | |
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| 0.3323 | 6.9961 | 446 | 0.3022 | 0.8952 | |
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| 0.3125 | 8.0 | 510 | 0.2750 | 0.9089 | |
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| 0.2663 | 8.9882 | 573 | 0.2648 | 0.8883 | |
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| 0.2672 | 9.9922 | 637 | 0.2476 | 0.9038 | |
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| 0.2492 | 10.9961 | 701 | 0.2354 | 0.9278 | |
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| 0.2297 | 12.0 | 765 | 0.2272 | 0.9175 | |
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| 0.1915 | 12.9882 | 828 | 0.2126 | 0.9107 | |
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| 0.2071 | 13.9922 | 892 | 0.2006 | 0.9227 | |
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| 0.2251 | 14.9961 | 956 | 0.1806 | 0.9244 | |
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| 0.1979 | 16.0 | 1020 | 0.1900 | 0.9347 | |
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| 0.1969 | 16.9882 | 1083 | 0.2081 | 0.9192 | |
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| 0.2 | 17.9922 | 1147 | 0.2037 | 0.9175 | |
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| 0.2082 | 18.9961 | 1211 | 0.2108 | 0.9175 | |
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| 0.1838 | 19.7647 | 1260 | 0.1688 | 0.9330 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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