whisper-small-ml
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: 0.5452
- Wer: 84.0883
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: 800
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0869 | 6.25 | 200 | 0.3877 | 89.5470 |
| 0.0138 | 12.5 | 400 | 0.4962 | 87.4564 |
| 0.0088 | 18.75 | 600 | 0.5118 | 100.3484 |
| 0.0058 | 25.0 | 800 | 0.5452 | 84.0883 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.14.0