jpwhisperfinetune
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: 0.4688
- Wer: 32.2907
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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0924 | 2.4450 | 1000 | 0.2989 | 35.0800 |
| 0.0227 | 4.8900 | 2000 | 0.3584 | 33.6578 |
| 0.0018 | 7.3350 | 3000 | 0.4135 | 32.3161 |
| 0.0003 | 9.7800 | 4000 | 0.4539 | 32.3034 |
| 0.0002 | 12.2249 | 5000 | 0.4688 | 32.2907 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1
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Model tree for jaype/whisper-small-hi
Base model
openai/whisper-smallEvaluation results
- Wer on Common Voice 11.0self-reported32.291