torgo-sentences
This model is a fine-tuned version of yongjian/wav2vec2-large-a on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4597
- Wer: 0.2763
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: 0.0001
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 7.9559 | 3.68 | 500 | 7.9711 | 1.0 |
| 3.7513 | 7.35 | 1000 | 2.9848 | 1.0 |
| 2.3575 | 11.03 | 1500 | 0.7358 | 0.4943 |
| 0.565 | 14.71 | 2000 | 0.4717 | 0.3160 |
| 0.3093 | 18.38 | 2500 | 0.4621 | 0.3076 |
| 0.2096 | 22.06 | 3000 | 0.4586 | 0.2857 |
| 0.1716 | 25.74 | 3500 | 0.5179 | 0.2805 |
| 0.2116 | 29.41 | 4000 | 0.4597 | 0.2763 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 1.18.3
- Tokenizers 0.13.2