DistilHuBERT-GenreCLS
This model is a fine-tuned version of ntu-spml/distilhubert on the GTZAN dataset. It achieves the following results on the evaluation set:
- Loss: 0.8775
- Accuracy: 0.7791
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: 8
- eval_batch_size: 8
- seed: 42
- 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: 100
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.9882 | 1.0 | 97 | 1.9219 | 0.5465 |
| 1.4381 | 2.0 | 194 | 1.3256 | 0.6395 |
| 1.1721 | 3.0 | 291 | 1.1294 | 0.6977 |
| 0.8336 | 4.0 | 388 | 0.9077 | 0.7791 |
| 0.8231 | 5.0 | 485 | 0.8775 | 0.7791 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2