distilhubert-finetuned-gtzan
This model is a fine-tuned version of ntu-spml/distilhubert on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.0786
- Accuracy: 0.76
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use 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: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 7.925 | 1.0 | 113 | 1.7725 | 0.52 |
| 5.6679 | 2.0 | 226 | 1.2555 | 0.67 |
| 4.6664 | 3.0 | 339 | 1.0786 | 0.76 |
Framework versions
- Transformers 5.16.0.dev0
- Pytorch 2.13.0+cu126
- Datasets 5.0.1
- Tokenizers 0.23.1