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whisper-small-et-ERR2020
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: 0.5321
- Wer: 22.8462
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: 1000
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3387 | 0.1 | 1000 | 0.5383 | 33.8216 |
| 0.1393 | 0.2 | 2000 | 0.4897 | 27.7546 |
| 0.0982 | 0.3 | 3000 | 0.5477 | 26.7815 |
| 0.0912 | 1.02 | 4000 | 0.5195 | 24.8816 |
| 0.0811 | 1.12 | 5000 | 0.5373 | 25.9282 |
| 0.0649 | 1.22 | 6000 | 0.5422 | 23.7285 |
| 0.0618 | 1.32 | 7000 | 0.5504 | 23.5179 |
| 0.0558 | 2.03 | 8000 | 0.5321 | 22.8462 |
| 0.0452 | 2.13 | 9000 | 0.5543 | 23.5813 |
| 0.0462 | 2.23 | 10000 | 0.5424 | 22.8830 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.12.1+rocm5.1.1
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
