Whisper Small Sr - Sagicc
This model is a fine-tuned version of openai/whisper-small on the Common Voice 13 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3675
- Wer Ortho: 28.9565
- Wer: 18.0930
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 1000
Training results
| Training Loss |
Epoch |
Step |
Validation Loss |
Wer Ortho |
Wer |
| 0.0728 |
2.87 |
500 |
0.2978 |
29.5435 |
18.8749 |
| 0.0318 |
5.75 |
1000 |
0.3675 |
28.9565 |
18.0930 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
