hubert-base-ls960-finetuned-gtzan
This model is a fine-tuned version of facebook/hubert-base-ls960 on the GTZAN dataset. It achieves the following results on the evaluation set:
- Loss: 0.6629
- Accuracy: 0.86
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
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- 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_steps: 150
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 4.0166 | 1.0 | 113 | 1.9303 | 0.37 |
| 2.9802 | 2.0 | 226 | 1.5313 | 0.5 |
| 2.7809 | 3.0 | 339 | 1.2783 | 0.58 |
| 1.6393 | 4.0 | 452 | 1.0212 | 0.71 |
| 1.7196 | 5.0 | 565 | 0.9676 | 0.7 |
| 1.7533 | 6.0 | 678 | 0.8288 | 0.72 |
| 1.2629 | 7.0 | 791 | 0.5269 | 0.85 |
| 0.9351 | 8.0 | 904 | 0.6159 | 0.82 |
| 0.5778 | 9.0 | 1017 | 0.5569 | 0.83 |
| 0.4505 | 10.0 | 1130 | 0.5305 | 0.86 |
| 0.5766 | 11.0 | 1243 | 0.7149 | 0.83 |
| 0.3385 | 12.0 | 1356 | 0.7123 | 0.86 |
| 0.1503 | 13.0 | 1469 | 0.7124 | 0.84 |
| 0.4639 | 14.0 | 1582 | 0.6589 | 0.84 |
| 0.0482 | 15.0 | 1695 | 0.6629 | 0.86 |
Framework versions
- Transformers 5.20.2
- Pytorch 2.11.0+cu130
- Datasets 4.8.5
- Tokenizers 0.23.3