openai/whisper-tiny
This model is a fine-tuned version of openai/whisper-tiny on the MyST(55 hours) dataset. It achieves the following results on the evaluation set (MyST 10 hours):
- Loss: 0.5675
- Wer: 20.2661
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: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3752 | 4.02 | 1000 | 0.4264 | 20.9318 |
| 0.2349 | 8.04 | 2000 | 0.4460 | 19.5872 |
| 0.095 | 13.01 | 3000 | 0.5086 | 20.6995 |
| 0.0416 | 17.02 | 4000 | 0.5504 | 20.7856 |
| 0.0339 | 21.04 | 5000 | 0.5675 | 20.2661 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.9.1.dev0
- Tokenizers 0.13.2