| --- |
| license: bsd-3-clause |
| base_model: MIT/ast-finetuned-audioset-10-10-0.4593 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - marsyas/gtzan |
| metrics: |
| - accuracy |
| model-index: |
| - name: ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan |
| results: |
| - task: |
| name: Audio Classification |
| type: audio-classification |
| dataset: |
| name: GTZAN |
| type: marsyas/gtzan |
| config: all |
| split: train |
| args: all |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.9 |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan |
|
|
| 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. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4248 |
| - Accuracy: 0.9 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 4e-05 |
| - train_batch_size: 4 |
| - eval_batch_size: 4 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 8 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 15 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 0.9212 | 1.0 | 112 | 0.6617 | 0.79 | |
| | 0.4306 | 2.0 | 225 | 0.5650 | 0.81 | |
| | 0.3493 | 3.0 | 337 | 0.3763 | 0.88 | |
| | 0.0369 | 4.0 | 450 | 0.5402 | 0.83 | |
| | 0.0018 | 5.0 | 562 | 0.4543 | 0.9 | |
| | 0.0025 | 6.0 | 675 | 0.5821 | 0.85 | |
| | 0.0009 | 7.0 | 787 | 0.4905 | 0.89 | |
| | 0.0001 | 8.0 | 900 | 0.5396 | 0.86 | |
| | 0.0871 | 9.0 | 1012 | 0.7212 | 0.86 | |
| | 0.0001 | 10.0 | 1125 | 0.4179 | 0.9 | |
| | 0.0001 | 11.0 | 1237 | 0.5138 | 0.9 | |
| | 0.0001 | 12.0 | 1350 | 0.4133 | 0.9 | |
| | 0.0001 | 13.0 | 1462 | 0.4273 | 0.9 | |
| | 0.0001 | 14.0 | 1575 | 0.4278 | 0.9 | |
| | 0.0001 | 14.93 | 1680 | 0.4248 | 0.9 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.37.2 |
| - Pytorch 2.1.0+cu121 |
| - Datasets 2.17.0 |
| - Tokenizers 0.15.1 |
|
|
