| --- |
| library_name: transformers |
| 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-gtzan |
| results: |
| - task: |
| name: Audio Classification |
| type: audio-classification |
| dataset: |
| name: GTZAN |
| type: marsyas/gtzan |
| config: all |
| split: None |
| 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-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: 0.3410 |
| - 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: 3e-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 16 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 25 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 1.627 | 1.0 | 50 | 0.8714 | 0.795 | |
| | 0.4145 | 2.0 | 100 | 0.5660 | 0.825 | |
| | 0.2344 | 3.0 | 150 | 0.4988 | 0.85 | |
| | 0.1334 | 4.0 | 200 | 0.3726 | 0.87 | |
| | 0.0341 | 5.0 | 250 | 0.3637 | 0.895 | |
| | 0.0172 | 6.0 | 300 | 0.4197 | 0.87 | |
| | 0.0338 | 7.0 | 350 | 0.5035 | 0.87 | |
| | 0.002 | 8.0 | 400 | 0.5825 | 0.86 | |
| | 0.001 | 9.0 | 450 | 0.4126 | 0.895 | |
| | 0.0093 | 10.0 | 500 | 0.4564 | 0.89 | |
| | 0.0056 | 11.0 | 550 | 0.4783 | 0.84 | |
| | 0.0162 | 12.0 | 600 | 0.3161 | 0.89 | |
| | 0.0019 | 13.0 | 650 | 0.4062 | 0.875 | |
| | 0.0005 | 14.0 | 700 | 0.3630 | 0.895 | |
| | 0.0098 | 15.0 | 750 | 0.3410 | 0.9 | |
| | 0.008 | 16.0 | 800 | 0.3385 | 0.89 | |
| | 0.0001 | 17.0 | 850 | 0.3434 | 0.895 | |
| | 0.0067 | 18.0 | 900 | 0.3414 | 0.885 | |
| | 0.0064 | 19.0 | 950 | 0.3453 | 0.895 | |
| | 0.0001 | 20.0 | 1000 | 0.3422 | 0.885 | |
| | 0.0001 | 21.0 | 1050 | 0.3520 | 0.89 | |
| | 0.0036 | 22.0 | 1100 | 0.3403 | 0.89 | |
| | 0.0001 | 23.0 | 1150 | 0.3394 | 0.89 | |
| | 0.0001 | 24.0 | 1200 | 0.3407 | 0.89 | |
| | 0.0026 | 25.0 | 1250 | 0.3417 | 0.89 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.57.3 |
| - Pytorch 2.9.0+cu128 |
| - Datasets 2.18.0 |
| - Tokenizers 0.22.1 |
| |
