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whisper-small-cntt2
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6061
- Wer: 64.3143
- Cer: 51.0104
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: 8
- 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: 4000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.0207 | 7.19 | 1000 | 0.4723 | 76.4951 | 61.2694 |
| 0.0017 | 14.39 | 2000 | 0.5593 | 69.3438 | 55.3014 |
| 0.0008 | 21.58 | 3000 | 0.5938 | 67.1198 | 53.9426 |
| 0.0006 | 28.78 | 4000 | 0.6061 | 64.3143 | 51.0104 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.0
- Datasets 2.14.4
- Tokenizers 0.13.3
