Whisper Turbo - Chee Li
This model is a fine-tuned version of openai/whisper-large-v3-turbo on the Google Fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 0.2122
- Wer: 16.5502
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 |
---|---|---|---|---|
0.0128 | 5.0251 | 1000 | 0.2026 | 11.1336 |
0.0021 | 10.0503 | 2000 | 0.2049 | 14.8868 |
0.0003 | 15.0754 | 3000 | 0.2108 | 13.6427 |
0.0001 | 20.1005 | 4000 | 0.2122 | 16.5502 |
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-polish
Base model
openai/whisper-large-v3
Finetuned
openai/whisper-large-v3-turbo