distilhubert-finetuned-gtzan-finetuned-gtzan
This model is a fine-tuned version of chaouch/distilhubert-finetuned-gtzan on the GTZAN dataset. It achieves the following results on the evaluation set:
- Loss: 0.1733
- Accuracy: 0.9667
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: 0.0001
- train_batch_size: 6
- eval_batch_size: 6
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 7
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.026 | 1.0 | 135 | 0.2289 | 0.9444 |
| 0.1351 | 2.0 | 270 | 0.1379 | 0.9778 |
| 0.01 | 3.0 | 405 | 0.2310 | 0.9667 |
| 0.0053 | 4.0 | 540 | 0.1727 | 0.9667 |
| 0.0002 | 5.0 | 675 | 0.1703 | 0.9667 |
| 0.0002 | 6.0 | 810 | 0.1722 | 0.9667 |
| 0.0002 | 7.0 | 945 | 0.1733 | 0.9667 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2