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Whisper Small Ckb - Razhan Hameed
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3825
- Wer: 33.2193
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: 12000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1693 | 2.49 | 1000 | 0.2060 | 39.1265 |
| 0.0722 | 4.98 | 2000 | 0.2124 | 36.3173 |
| 0.0127 | 7.46 | 3000 | 0.2736 | 36.5568 |
| 0.008 | 9.95 | 4000 | 0.3131 | 35.7015 |
| 0.0032 | 12.44 | 5000 | 0.3434 | 35.3936 |
| 0.0028 | 14.93 | 6000 | 0.3453 | 35.9258 |
| 0.003 | 17.41 | 7000 | 0.3558 | 34.9565 |
| 0.0022 | 19.9 | 8000 | 0.3593 | 34.2722 |
| 0.0016 | 22.39 | 9000 | 0.3639 | 34.3369 |
| 0.0015 | 24.88 | 10000 | 0.3785 | 34.0062 |
| 0.0009 | 27.36 | 11000 | 0.3915 | 34.2951 |
| 0.0001 | 29.85 | 12000 | 0.3825 | 33.2193 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
