| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: facebook/hubert-base-ls960 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - gtzan |
| metrics: |
| - accuracy |
| model-index: |
| - name: hubert-test-model |
| results: |
| - task: |
| name: Audio Classification |
| type: audio-classification |
| dataset: |
| name: gtzan |
| type: gtzan |
| config: default |
| split: train |
| args: default |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.785 |
| --- |
| |
| <!-- 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. --> |
|
|
| # hubert-test-model |
|
|
| This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on the gtzan dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.5276 |
| - Accuracy: 0.785 |
|
|
| ## 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: 5e-05 |
| - train_batch_size: 4 |
| - eval_batch_size: 4 |
| - seed: 42 |
| - optimizer: Use adamw_torch 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: 20 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | No log | 1.0 | 150 | 2.0494 | 0.29 | |
| | No log | 2.0 | 300 | 2.1993 | 0.19 | |
| | No log | 3.0 | 450 | 1.8439 | 0.44 | |
| | 1.9218 | 4.0 | 600 | 1.5277 | 0.48 | |
| | 1.9218 | 5.0 | 750 | 1.4164 | 0.475 | |
| | 1.9218 | 6.0 | 900 | 1.3641 | 0.63 | |
| | 1.2685 | 7.0 | 1050 | 1.1557 | 0.675 | |
| | 1.2685 | 8.0 | 1200 | 1.0935 | 0.72 | |
| | 1.2685 | 9.0 | 1350 | 1.0594 | 0.71 | |
| | 0.7151 | 10.0 | 1500 | 1.0119 | 0.735 | |
| | 0.7151 | 11.0 | 1650 | 1.0868 | 0.77 | |
| | 0.7151 | 12.0 | 1800 | 1.3736 | 0.75 | |
| | 0.7151 | 13.0 | 1950 | 1.2705 | 0.77 | |
| | 0.4135 | 14.0 | 2100 | 1.4052 | 0.76 | |
| | 0.4135 | 15.0 | 2250 | 1.3864 | 0.77 | |
| | 0.4135 | 16.0 | 2400 | 1.4296 | 0.785 | |
| | 0.2311 | 17.0 | 2550 | 1.5663 | 0.77 | |
| | 0.2311 | 18.0 | 2700 | 1.5310 | 0.78 | |
| | 0.2311 | 19.0 | 2850 | 1.4884 | 0.795 | |
| | 0.1408 | 20.0 | 3000 | 1.5276 | 0.785 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.46.2 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 3.1.0 |
| - Tokenizers 0.20.3 |
| |
