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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224-in21k |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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model-index: |
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- name: alz-mri-vit |
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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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# alz-mri-vit |
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2447 |
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- F1: 0.9086 |
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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: 0.0002 |
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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: 30 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 1.1101 | 1.0 | 64 | 0.9590 | 0.5549 | |
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| 0.9356 | 2.0 | 128 | 0.8877 | 0.5940 | |
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| 0.9187 | 3.0 | 192 | 0.9376 | 0.5272 | |
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| 0.8804 | 4.0 | 256 | 0.8667 | 0.5962 | |
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| 0.7854 | 5.0 | 320 | 0.7756 | 0.6720 | |
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| 0.7278 | 6.0 | 384 | 0.7202 | 0.6860 | |
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| 0.6462 | 7.0 | 448 | 0.7124 | 0.6898 | |
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| 0.5731 | 8.0 | 512 | 0.6027 | 0.7553 | |
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| 0.473 | 9.0 | 576 | 0.5520 | 0.7724 | |
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| 0.4378 | 10.0 | 640 | 0.5550 | 0.7758 | |
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| 0.4086 | 11.0 | 704 | 0.4366 | 0.8271 | |
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| 0.36 | 12.0 | 768 | 0.4446 | 0.8225 | |
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| 0.3217 | 13.0 | 832 | 0.3841 | 0.8441 | |
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| 0.2941 | 14.0 | 896 | 0.4719 | 0.8182 | |
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| 0.2679 | 15.0 | 960 | 0.4112 | 0.8410 | |
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| 0.2565 | 16.0 | 1024 | 0.3698 | 0.8527 | |
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| 0.2502 | 17.0 | 1088 | 0.3283 | 0.8810 | |
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| 0.2166 | 18.0 | 1152 | 0.3569 | 0.8627 | |
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| 0.197 | 19.0 | 1216 | 0.3475 | 0.8699 | |
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| 0.2004 | 20.0 | 1280 | 0.3171 | 0.8834 | |
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| 0.1722 | 21.0 | 1344 | 0.2711 | 0.8998 | |
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| 0.1529 | 22.0 | 1408 | 0.2432 | 0.9100 | |
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| 0.1495 | 23.0 | 1472 | 0.2950 | 0.8978 | |
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| 0.1307 | 24.0 | 1536 | 0.2811 | 0.9034 | |
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| 0.1278 | 25.0 | 1600 | 0.2545 | 0.9086 | |
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| 0.1175 | 26.0 | 1664 | 0.2561 | 0.9051 | |
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| 0.1264 | 27.0 | 1728 | 0.2128 | 0.9186 | |
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| 0.1015 | 28.0 | 1792 | 0.3022 | 0.9014 | |
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| 0.1077 | 29.0 | 1856 | 0.2403 | 0.9221 | |
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| 0.0932 | 30.0 | 1920 | 0.2447 | 0.9086 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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