Whisper Medium English - Chee Li
This model is a fine-tuned version of openai/whisper-medium on the Google Fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 0.3285
- Wer: 7.1528
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 |
---|---|---|---|---|
0.005 | 5.3191 | 1000 | 0.2599 | 6.9576 |
0.0002 | 10.6383 | 2000 | 0.3051 | 7.1946 |
0.0001 | 15.9574 | 3000 | 0.3228 | 7.2295 |
0.0001 | 21.2766 | 4000 | 0.3285 | 7.1528 |
Framework versions
- Transformers 4.43.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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openai/whisper-medium