openai/whisper-small
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: 0.1815
- Wer: 206.4766
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: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0065 | 10.0 | 500 | 0.1476 | 109.2459 |
| 0.0006 | 20.0 | 1000 | 0.1683 | 144.5619 |
| 0.0012 | 30.01 | 1500 | 0.1623 | 205.1738 |
| 0.0002 | 40.01 | 2000 | 0.1710 | 152.7209 |
| 0.0001 | 51.0 | 2500 | 0.1760 | 171.9869 |
| 0.0001 | 61.0 | 3000 | 0.1789 | 193.3447 |
| 0.0001 | 71.01 | 3500 | 0.1808 | 201.9206 |
| 0.0001 | 81.01 | 4000 | 0.1815 | 206.4766 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.9.1.dev0
- Tokenizers 0.13.2
- Downloads last month
- 3
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.