openai/whisper-medium
This model is a fine-tuned version of openai/whisper-medium on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2617
- Wer: 9.8915
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: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.201 | 0.12 | 500 | 0.2391 | 10.8388 |
| 0.1726 | 1.06 | 1000 | 0.2055 | 11.1596 |
| 0.0984 | 1.18 | 1500 | 0.2025 | 10.4073 |
| 0.0782 | 2.12 | 2000 | 0.2073 | 10.9048 |
| 0.0301 | 3.05 | 2500 | 0.2261 | 10.1788 |
| 0.0284 | 3.17 | 3000 | 0.2303 | 10.0631 |
| 0.0153 | 4.11 | 3500 | 0.2513 | 10.4804 |
| 0.0386 | 5.04 | 4000 | 0.2617 | 9.8915 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.9.1.dev0
- Tokenizers 0.13.2