whisper-base-tamil
This model is a fine-tuned version of openai/whisper-base on the Common Voice 13 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6483
- Wer Ortho: 72.2910
- Wer: 28.2243
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: 32
- eval_batch_size: 32
- 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: 500
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.003 | 20.0 | 500 | 0.6483 | 72.2910 | 28.2243 |
Framework versions
- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.14.0
- Tokenizers 0.13.3