JLB-JLB commited on
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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-in21k
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: seizure_vit_jlb_231108_iir_adjusted
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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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+ # seizure_vit_jlb_231108_iir_adjusted
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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: 0.8152
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+ - Roc Auc: 0.7587
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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: 1e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 5
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Roc Auc |
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+ |:-------------:|:-----:|:-----:|:---------------:|:-------:|
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+ | 0.3803 | 0.34 | 1000 | 0.4734 | 0.7746 |
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+ | 0.3456 | 0.68 | 2000 | 0.4863 | 0.7782 |
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+ | 0.2831 | 1.02 | 3000 | 0.4817 | 0.7897 |
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+ | 0.2781 | 1.36 | 4000 | 0.5418 | 0.7656 |
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+ | 0.2355 | 1.7 | 5000 | 0.5398 | 0.7786 |
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+ | 0.1978 | 2.04 | 6000 | 0.6121 | 0.7649 |
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+ | 0.149 | 2.38 | 7000 | 0.6402 | 0.7706 |
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+ | 0.1766 | 2.72 | 8000 | 0.6768 | 0.7610 |
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+ | 0.1496 | 3.06 | 9000 | 0.6239 | 0.7733 |
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+ | 0.155 | 3.4 | 10000 | 0.7333 | 0.7602 |
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+ | 0.1238 | 3.75 | 11000 | 0.6513 | 0.7726 |
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+ | 0.1054 | 4.09 | 12000 | 0.7551 | 0.7667 |
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+ | 0.1076 | 4.43 | 13000 | 0.8132 | 0.7627 |
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+ | 0.1321 | 4.77 | 14000 | 0.8152 | 0.7587 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.0
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+ - Pytorch 2.1.0
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+ - Datasets 2.14.6
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+ - Tokenizers 0.14.1
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