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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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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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name: Audio Classification |
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type: 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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- name: Accuracy |
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type: accuracy |
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value: 0.89 |
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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: 0.3030 |
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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: 1e-05 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 8 |
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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: 10 |
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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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| 0.9203 | 1.0 | 112 | 0.6901 | 0.82 | |
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| 0.2906 | 1.99 | 224 | 0.4069 | 0.86 | |
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| 0.3416 | 3.0 | 337 | 0.3651 | 0.84 | |
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| 0.2143 | 4.0 | 449 | 0.3208 | 0.89 | |
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| 0.0052 | 4.99 | 561 | 0.3180 | 0.88 | |
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| 0.0037 | 6.0 | 674 | 0.3233 | 0.88 | |
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| 0.0011 | 6.99 | 786 | 0.2975 | 0.9 | |
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| 0.0011 | 8.0 | 899 | 0.3200 | 0.88 | |
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| 0.0325 | 9.0 | 1011 | 0.3028 | 0.89 | |
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| 0.0008 | 9.97 | 1120 | 0.3030 | 0.89 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.2 |
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