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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: 0.9 |
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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: 0.4793 |
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- Accuracy: 0.9 |
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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-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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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: 25 |
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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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| 0.6559 | 1.0 | 112 | 0.5081 | 0.86 | |
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| 0.5141 | 2.0 | 225 | 0.5618 | 0.77 | |
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| 0.5517 | 3.0 | 337 | 0.5009 | 0.84 | |
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| 0.6651 | 4.0 | 450 | 0.7811 | 0.82 | |
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| 0.0057 | 5.0 | 562 | 0.3074 | 0.93 | |
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| 0.0018 | 6.0 | 675 | 0.4843 | 0.87 | |
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| 0.0007 | 7.0 | 787 | 0.6949 | 0.85 | |
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| 0.0007 | 8.0 | 900 | 0.6981 | 0.88 | |
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| 0.0007 | 9.0 | 1012 | 0.8356 | 0.87 | |
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| 0.0001 | 10.0 | 1125 | 0.6164 | 0.89 | |
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| 0.1709 | 11.0 | 1237 | 0.5464 | 0.89 | |
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| 0.0001 | 12.0 | 1350 | 0.4885 | 0.88 | |
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| 0.0003 | 13.0 | 1462 | 0.4970 | 0.91 | |
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| 0.0 | 14.0 | 1575 | 0.5346 | 0.88 | |
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| 0.0001 | 15.0 | 1687 | 0.5526 | 0.89 | |
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| 0.0 | 16.0 | 1800 | 0.4808 | 0.91 | |
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| 0.0 | 17.0 | 1912 | 0.4999 | 0.9 | |
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| 0.0 | 18.0 | 2025 | 0.4909 | 0.89 | |
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| 0.0 | 19.0 | 2137 | 0.4953 | 0.89 | |
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| 0.0 | 20.0 | 2250 | 0.4883 | 0.9 | |
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| 0.0543 | 21.0 | 2362 | 0.4830 | 0.91 | |
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| 0.0 | 22.0 | 2475 | 0.4811 | 0.9 | |
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| 0.0 | 23.0 | 2587 | 0.4805 | 0.9 | |
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| 0.0 | 24.0 | 2700 | 0.4785 | 0.91 | |
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| 0.0 | 24.89 | 2800 | 0.4793 | 0.9 | |
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### Framework versions |
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- Transformers 4.36.0.dev0 |
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- Pytorch 2.0.1 |
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- Datasets 2.14.5 |
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- Tokenizers 0.15.0 |
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