<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
openai/whisper-medium.en
This model is a fine-tuned version of openai/whisper-medium.en on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1748
- Wer: 2.7097
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 |
|---|---|---|---|---|
| 0.0329 | 5.0 | 500 | 0.1343 | 4.0125 |
| 0.0013 | 10.01 | 1000 | 0.1531 | 2.8810 |
| 0.0002 | 15.01 | 1500 | 0.1609 | 2.7321 |
| 0.0002 | 20.01 | 2000 | 0.1608 | 2.7544 |
| 0.0001 | 25.01 | 2500 | 0.1688 | 2.7321 |
| 0.0002 | 30.02 | 3000 | 0.1722 | 2.7172 |
| 0.0001 | 35.02 | 3500 | 0.1742 | 2.7172 |
| 0.0001 | 40.02 | 4000 | 0.1748 | 2.7097 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.9.1.dev0
- Tokenizers 0.13.2
