openai/whisper-base.en
This model is a fine-tuned version of openai/whisper-base.en on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6446
- Wer: 16.4580
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 |
|---|---|---|---|---|
| 0.3205 | 4.02 | 1000 | 0.4080 | 14.5116 |
| 0.1568 | 8.04 | 2000 | 0.4672 | 15.3758 |
| 0.035 | 13.01 | 3000 | 0.5696 | 15.9737 |
| 0.0087 | 17.02 | 4000 | 0.6242 | 15.7283 |
| 0.0065 | 21.04 | 5000 | 0.6446 | 16.4580 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.9.1.dev0
- Tokenizers 0.13.2