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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_43243531 |
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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_43243531 |
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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: 0.0063 |
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- Accuracy: 0.9990 |
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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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| 0.13 | 1.0 | 339 | 0.1382 | 0.9616 | |
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| 0.0931 | 2.0 | 678 | 0.0613 | 0.9839 | |
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| 0.0265 | 3.0 | 1017 | 0.0248 | 0.9942 | |
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| 0.026 | 4.0 | 1357 | 0.0612 | 0.9900 | |
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| 0.0252 | 5.0 | 1696 | 0.0460 | 0.9894 | |
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| 0.0369 | 6.0 | 2035 | 0.0148 | 0.9968 | |
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| 0.0018 | 7.0 | 2374 | 0.0049 | 0.9990 | |
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| 0.0007 | 8.0 | 2714 | 0.0114 | 0.9981 | |
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| 0.0056 | 9.0 | 3053 | 0.0107 | 0.9987 | |
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| 0.0003 | 10.0 | 3392 | 0.0067 | 0.9990 | |
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| 0.0101 | 11.0 | 3731 | 0.0039 | 0.9994 | |
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| 0.0073 | 12.0 | 4071 | 0.0049 | 0.9994 | |
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| 0.0113 | 13.0 | 4410 | 0.0061 | 0.9990 | |
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| 0.0002 | 14.0 | 4749 | 0.0067 | 0.9990 | |
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| 0.0002 | 14.99 | 5085 | 0.0063 | 0.9990 | |
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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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