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--- |
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license: bsd-3-clause |
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base_model: MIT/ast-finetuned-audioset-10-10-0.4593 |
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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_AST_U_43275873 |
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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_AST_U_43275873 |
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This model is a fine-tuned version of [MIT/ast-finetuned-audioset-10-10-0.4593](https://huggingface.co./MIT/ast-finetuned-audioset-10-10-0.4593) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0052 |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.0222 | 1.0 | 339 | 0.0859 | 0.9761 | |
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| 0.0242 | 2.0 | 678 | 0.0091 | 0.9977 | |
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| 0.0033 | 3.0 | 1017 | 0.0198 | 0.9932 | |
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| 0.0171 | 4.0 | 1357 | 0.0242 | 0.9945 | |
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| 0.0212 | 5.0 | 1696 | 0.0079 | 0.9990 | |
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| 0.0 | 6.0 | 2035 | 0.0095 | 0.9984 | |
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| 0.0 | 7.0 | 2374 | 0.0047 | 0.9990 | |
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| 0.0 | 8.0 | 2714 | 0.0048 | 0.9990 | |
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| 0.0 | 9.0 | 3053 | 0.0048 | 0.9990 | |
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| 0.0 | 10.0 | 3392 | 0.0050 | 0.9990 | |
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| 0.0 | 11.0 | 3731 | 0.0050 | 0.9990 | |
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| 0.0 | 12.0 | 4071 | 0.0051 | 0.9990 | |
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| 0.0 | 13.0 | 4410 | 0.0051 | 0.9990 | |
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| 0.0 | 14.0 | 4749 | 0.0052 | 0.9990 | |
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| 0.0 | 14.99 | 5085 | 0.0052 | 0.9990 | |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 2.1.2 |
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- Datasets 2.16.1 |
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- Tokenizers 0.13.3 |
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