wav2vec2-base
This model is a fine-tuned version of facebook/wav2vec2-base on the galsenai/waxal_dataset dataset. It achieves the following results on the evaluation set:
- Loss: 0.7504
- Accuracy: 0.8632
- Precision: 0.9380
- F1: 0.8954
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: 3e-05
- train_batch_size: 30
- eval_batch_size: 30
- seed: 0
- gradient_accumulation_steps: 4
- total_train_batch_size: 120
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 32.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | F1 |
|---|---|---|---|---|---|---|
| 4.3647 | 2.53 | 500 | 4.8202 | 0.0117 | 0.0134 | 0.0032 |
| 2.6202 | 5.05 | 1000 | 4.2238 | 0.0625 | 0.0781 | 0.0355 |
| 1.38 | 7.58 | 1500 | 3.6392 | 0.2941 | 0.5211 | 0.3174 |
| 0.8601 | 10.1 | 2000 | 2.7953 | 0.4907 | 0.7446 | 0.5657 |
| 0.5645 | 12.63 | 2500 | 1.9829 | 0.6862 | 0.8363 | 0.7421 |
| 0.4009 | 15.15 | 3000 | 1.4535 | 0.7635 | 0.9000 | 0.8174 |
| 0.3054 | 17.68 | 3500 | 1.1426 | 0.7882 | 0.9058 | 0.8298 |
| 0.2448 | 20.2 | 4000 | 0.9860 | 0.8189 | 0.9206 | 0.8593 |
| 0.2116 | 22.73 | 4500 | 0.8820 | 0.8325 | 0.9261 | 0.8711 |
| 0.1863 | 25.25 | 5000 | 0.8191 | 0.8465 | 0.9366 | 0.8848 |
| 0.1701 | 27.78 | 5500 | 0.7504 | 0.8632 | 0.9380 | 0.8954 |
| 0.1558 | 30.3 | 6000 | 0.7665 | 0.8609 | 0.9398 | 0.8956 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.11.0+cu113
- Datasets 2.9.1.dev0
- Tokenizers 0.13.2