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alz-mri-vit

Image Classification
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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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+
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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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+ # alz-mri-vit
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+
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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: 0.1875
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+ - F1: 0.9309
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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: 0.0002
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 1.1218 | 1.0 | 64 | 0.9419 | 0.5742 |
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+ | 0.94 | 2.0 | 128 | 0.9054 | 0.6029 |
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+ | 0.9123 | 3.0 | 192 | 0.9019 | 0.5262 |
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+ | 0.8625 | 4.0 | 256 | 0.8465 | 0.6029 |
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+ | 0.8104 | 5.0 | 320 | 0.7810 | 0.6319 |
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+ | 0.7244 | 6.0 | 384 | 0.7278 | 0.7037 |
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+ | 0.697 | 7.0 | 448 | 0.6300 | 0.7480 |
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+ | 0.5865 | 8.0 | 512 | 0.5659 | 0.7662 |
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+ | 0.5199 | 9.0 | 576 | 0.5445 | 0.7721 |
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+ | 0.4734 | 10.0 | 640 | 0.6750 | 0.7185 |
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+ | 0.4399 | 11.0 | 704 | 0.4893 | 0.8274 |
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+ | 0.3817 | 12.0 | 768 | 0.5578 | 0.7844 |
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+ | 0.3318 | 13.0 | 832 | 0.4699 | 0.8228 |
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+ | 0.3096 | 14.0 | 896 | 0.4460 | 0.8399 |
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+ | 0.2787 | 15.0 | 960 | 0.4105 | 0.8399 |
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+ | 0.2517 | 16.0 | 1024 | 0.3488 | 0.8578 |
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+ | 0.2346 | 17.0 | 1088 | 0.3877 | 0.8773 |
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+ | 0.2286 | 18.0 | 1152 | 0.3420 | 0.8575 |
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+ | 0.1914 | 19.0 | 1216 | 0.4123 | 0.8682 |
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+ | 0.1844 | 20.0 | 1280 | 0.2894 | 0.8913 |
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+ | 0.173 | 21.0 | 1344 | 0.3197 | 0.8887 |
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+ | 0.1687 | 22.0 | 1408 | 0.2626 | 0.9075 |
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+ | 0.1601 | 23.0 | 1472 | 0.2951 | 0.9068 |
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+ | 0.1466 | 24.0 | 1536 | 0.2666 | 0.9049 |
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+ | 0.1468 | 25.0 | 1600 | 0.2136 | 0.9103 |
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+ | 0.1226 | 26.0 | 1664 | 0.2387 | 0.9127 |
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+ | 0.1186 | 27.0 | 1728 | 0.2131 | 0.9271 |
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+ | 0.0951 | 28.0 | 1792 | 0.2520 | 0.9130 |
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+ | 0.1049 | 29.0 | 1856 | 0.2096 | 0.9259 |
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+ | 0.0936 | 30.0 | 1920 | 0.1875 | 0.9309 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.0