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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-base |
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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: SeizureClassifier_Wav2Vec_B_43828665 |
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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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# SeizureClassifier_Wav2Vec_B_43828665 |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0355 |
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- Accuracy: 0.9950 |
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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: 3e-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: 15 |
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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 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 1.1208 | 0.99 | 44 | 0.9389 | 0.8441 | |
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| 0.6807 | 1.99 | 88 | 0.5630 | 0.8911 | |
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| 0.3684 | 2.98 | 132 | 0.3547 | 0.9332 | |
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| 0.2786 | 4.0 | 177 | 0.2168 | 0.9678 | |
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| 0.1849 | 4.99 | 221 | 0.2235 | 0.9530 | |
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| 0.1888 | 5.99 | 265 | 0.1294 | 0.9802 | |
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| 0.1201 | 6.98 | 309 | 0.1461 | 0.9703 | |
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| 0.1017 | 8.0 | 354 | 0.1188 | 0.9777 | |
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| 0.0972 | 8.99 | 398 | 0.1194 | 0.9752 | |
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| 0.0819 | 9.99 | 442 | 0.0872 | 0.9851 | |
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| 0.0518 | 10.98 | 486 | 0.0550 | 0.9851 | |
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| 0.0604 | 12.0 | 531 | 0.0327 | 0.9975 | |
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| 0.0267 | 12.99 | 575 | 0.0542 | 0.9926 | |
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| 0.019 | 13.99 | 619 | 0.0354 | 0.9926 | |
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| 0.0167 | 14.92 | 660 | 0.0355 | 0.9950 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.2+cu118 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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