Whisper Small ru - Chee Li
This model is a fine-tuned version of openai/whisper-small on the Google Fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 0.2500
- Wer: 50.3541
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: 16
- eval_batch_size: 8
- 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 |
|---|---|---|---|---|
| 0.0049 | 5.4645 | 1000 | 0.2170 | 29.2090 |
| 0.0013 | 10.9290 | 2000 | 0.2340 | 43.3993 |
| 0.0006 | 16.3934 | 3000 | 0.2457 | 49.9800 |
| 0.0004 | 21.8579 | 4000 | 0.2500 | 50.3541 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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