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update model card README.md
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README.md
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---
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license: bsd-3-clause
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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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---
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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: 0.3882
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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: 20
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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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| 0.4932 | 1.0 | 112 | 0.5325 | 0.86 |
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| 0.3541 | 2.0 | 225 | 0.6068 | 0.77 |
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| 0.5743 | 3.0 | 337 | 0.6356 | 0.83 |
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| 0.6256 | 4.0 | 450 | 0.4878 | 0.86 |
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| 0.0619 | 5.0 | 562 | 0.4262 | 0.88 |
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| 0.0044 | 6.0 | 675 | 0.3266 | 0.91 |
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| 0.0018 | 7.0 | 787 | 0.4827 | 0.87 |
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| 0.001 | 8.0 | 900 | 0.9245 | 0.82 |
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| 0.1854 | 9.0 | 1012 | 0.4256 | 0.89 |
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| 0.0001 | 10.0 | 1125 | 0.3898 | 0.9 |
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| 0.0001 | 11.0 | 1237 | 0.3873 | 0.9 |
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| 0.0001 | 12.0 | 1350 | 0.4064 | 0.91 |
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| 0.0 | 13.0 | 1462 | 0.3910 | 0.9 |
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| 0.0 | 14.0 | 1575 | 0.3924 | 0.9 |
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| 0.0001 | 15.0 | 1687 | 0.3917 | 0.91 |
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| 0.0 | 16.0 | 1800 | 0.3903 | 0.9 |
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| 0.0 | 17.0 | 1912 | 0.3900 | 0.89 |
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| 0.0 | 18.0 | 2025 | 0.3894 | 0.89 |
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| 0.0 | 19.0 | 2137 | 0.3886 | 0.9 |
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| 0.0 | 19.91 | 2240 | 0.3882 | 0.9 |
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### Framework versions
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- Transformers 4.30.2
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- Pytorch 2.0.1+cu118
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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