Whisper Large V3 tr ft - Chee Li
This model is a fine-tuned version of openai/whisper-large-v3 on the Google Fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 0.1394
- Wer: 8.9608
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-06
- 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 |
|---|---|---|---|---|
| 0.0368 | 5.5866 | 1000 | 0.1079 | 7.7474 |
| 0.003 | 11.1732 | 2000 | 0.1302 | 8.6030 |
| 0.0016 | 16.7598 | 3000 | 0.1373 | 8.7974 |
| 0.0013 | 22.3464 | 4000 | 0.1394 | 8.9608 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for liqi03/whisper-large-v3-tr-ft
Base model
openai/whisper-large-v3Dataset used to train liqi03/whisper-large-v3-tr-ft
Evaluation results
- Wer on Google Fleursself-reported8.961