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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: 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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+
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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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+ # SeizureClassifier_Wav2Vec_43243531
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+
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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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+
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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: 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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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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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