Whisper Small - 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: 0.4791
- Wer: 35.4625
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 |
|---|---|---|---|---|
| 0.0147 | 6.6667 | 1000 | 0.3868 | 34.5125 |
| 0.0009 | 13.3333 | 2000 | 0.4417 | 36.6375 |
| 0.0004 | 20.0 | 3000 | 0.4693 | 35.5625 |
| 0.0003 | 26.6667 | 4000 | 0.4791 | 35.4625 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Model tree for CheeLi03/whisper-ar
Base model
openai/whisper-small