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--- |
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library_name: transformers |
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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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datasets: |
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- marsyas/gtzan |
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metrics: |
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- accuracy |
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model-index: |
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- name: ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan |
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results: |
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- task: |
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type: audio-classification |
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name: Audio Classification |
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dataset: |
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name: GTZAN |
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type: marsyas/gtzan |
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config: all |
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split: train |
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args: all |
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metrics: |
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- type: accuracy |
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value: 0.89 |
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name: Accuracy |
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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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# ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan |
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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 GTZAN dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5321 |
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- Accuracy: 0.89 |
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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: 5e-06 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 5 |
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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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| 5.3547 | 0.9912 | 28 | 1.1577 | 0.73 | |
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| 2.8199 | 1.9823 | 56 | 0.7326 | 0.83 | |
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| 2.0591 | 2.9735 | 84 | 0.6054 | 0.87 | |
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| 1.5609 | 4.0 | 113 | 0.5425 | 0.89 | |
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| 1.5001 | 4.9558 | 140 | 0.5321 | 0.89 | |
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### Framework versions |
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- Transformers 4.46.0 |
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- Pytorch 2.5.0 |
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- Datasets 3.0.2 |
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- Tokenizers 0.20.1 |
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