distilhubert-finetuned-gtzan
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: 0.9734
- Model Preparation Time: 0.0068
- Accuracy: 0.8602
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: 0.1
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Accuracy |
|---|---|---|---|---|---|
| 1.2068 | 1.0 | 733 | 1.1166 | 0.0068 | 0.6774 |
| 0.8130 | 2.0 | 1466 | 0.6470 | 0.0068 | 0.7957 |
| 0.3782 | 3.0 | 2199 | 0.5003 | 0.0068 | 0.8280 |
| 0.2297 | 4.0 | 2932 | 0.5445 | 0.0068 | 0.8495 |
| 0.1655 | 5.0 | 3665 | 0.6829 | 0.0068 | 0.8602 |
| 0.0025 | 6.0 | 4398 | 0.7646 | 0.0068 | 0.8280 |
| 0.1201 | 7.0 | 5131 | 0.8735 | 0.0068 | 0.8495 |
| 0.0508 | 8.0 | 5864 | 0.8754 | 0.0068 | 0.8817 |
| 0.0434 | 9.0 | 6597 | 0.9917 | 0.0068 | 0.8710 |
| 0.0015 | 10.0 | 7330 | 1.2593 | 0.0068 | 0.8602 |
| 0.0000 | 11.0 | 8063 | 0.8777 | 0.0068 | 0.8817 |
| 0.0001 | 12.0 | 8796 | 1.2714 | 0.0068 | 0.8387 |
| 0.0000 | 13.0 | 9529 | 0.9322 | 0.0068 | 0.8495 |
| 0.0000 | 14.0 | 10262 | 0.9663 | 0.0068 | 0.8495 |
| 0.0000 | 15.0 | 10995 | 0.9734 | 0.0068 | 0.8602 |
Framework versions
- Transformers 5.12.1
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2