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whisper-small-bn-3ds
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: 0.0574
- Wer: 8.5038
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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 8950
- training_steps: 28000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2337 | 0.22 | 2000 | 0.2298 | 31.7734 |
| 0.1444 | 0.45 | 4000 | 0.1516 | 22.2382 |
| 0.1106 | 0.67 | 6000 | 0.1181 | 17.2230 |
| 0.0933 | 0.89 | 8000 | 0.1005 | 14.8008 |
| 0.0747 | 1.12 | 10000 | 0.0865 | 12.7184 |
| 0.0642 | 1.34 | 12000 | 0.0788 | 11.6441 |
| 0.0613 | 1.56 | 14000 | 0.0715 | 10.6524 |
| 0.0565 | 1.79 | 16000 | 0.0666 | 9.8807 |
| 0.0494 | 2.01 | 18000 | 0.0640 | 9.5265 |
| 0.037 | 2.24 | 20000 | 0.0619 | 9.0317 |
| 0.0348 | 2.46 | 22000 | 0.0600 | 9.0329 |
| 0.0329 | 2.68 | 24000 | 0.0582 | 8.8407 |
| 0.0321 | 2.91 | 26000 | 0.0564 | 8.4931 |
| 0.0227 | 3.13 | 28000 | 0.0574 | 8.5038 |
Framework versions
- Transformers 4.28.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.10.2.dev0
- Tokenizers 0.13.2
