apv53-finetuned-gtzan
This model is a fine-tuned version of OthmaneJ/distil-wav2vec2 on the GTZAN dataset. It achieves the following results on the evaluation set:
- Loss: 0.7427
- Accuracy: 0.82
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 adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.8074 | 1.0 | 113 | 1.1764 | 0.63 |
| 0.8226 | 2.0 | 226 | 0.8222 | 0.73 |
| 0.8055 | 3.0 | 339 | 0.9653 | 0.74 |
| 0.5099 | 4.0 | 452 | 1.3430 | 0.59 |
| 0.6568 | 5.0 | 565 | 0.8467 | 0.76 |
| 0.5449 | 6.0 | 678 | 0.9551 | 0.76 |
| 0.3872 | 7.0 | 791 | 0.8185 | 0.81 |
| 0.3452 | 8.0 | 904 | 0.8198 | 0.82 |
| 0.1398 | 9.0 | 1017 | 0.7110 | 0.85 |
| 0.1282 | 10.0 | 1130 | 0.7427 | 0.82 |
Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0