distilhubert-finetuned-music-genres
This model is a fine-tuned version of ntu-spml/distilhubert on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.6982
- Accuracy: 0.458
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
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 187 | 2.1291 | 0.312 |
| 2.2402 | 2.0 | 374 | 1.9922 | 0.388 |
| 2.2402 | 3.0 | 561 | 1.7594 | 0.444 |
| 1.6793 | 4.0 | 748 | 1.7164 | 0.447 |
| 1.6793 | 5.0 | 935 | 1.6982 | 0.458 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.11.0
- Datasets 2.6.1
- Tokenizers 0.11.6