m-a-p/MERT-v1-330M-finetuned-gtzan
This model is a fine-tuned version of m-a-p/MERT-v1-330M on the GTZAN dataset. It achieves the following results on the evaluation set:
- Loss: 0.4795
- Accuracy: 0.93
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: 16
- eval_batch_size: 16
- 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: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.125 | 1.0 | 57 | 2.0967 | 0.46 |
| 1.1862 | 2.0 | 114 | 1.0739 | 0.73 |
| 0.7055 | 3.0 | 171 | 0.7744 | 0.81 |
| 0.445 | 4.0 | 228 | 0.5283 | 0.86 |
| 0.2788 | 5.0 | 285 | 0.4848 | 0.89 |
| 0.0948 | 6.0 | 342 | 0.5192 | 0.89 |
| 0.0709 | 7.0 | 399 | 0.4638 | 0.9 |
| 0.0818 | 8.0 | 456 | 0.4345 | 0.91 |
| 0.0835 | 9.0 | 513 | 0.4638 | 0.92 |
| 0.0063 | 10.0 | 570 | 0.4175 | 0.94 |
| 0.0052 | 11.0 | 627 | 0.4807 | 0.93 |
| 0.0055 | 12.0 | 684 | 0.4814 | 0.93 |
| 0.0235 | 13.0 | 741 | 0.4796 | 0.93 |
| 0.0043 | 14.0 | 798 | 0.4793 | 0.93 |
| 0.0044 | 15.0 | 855 | 0.4795 | 0.93 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1