Whisper Large V3 tr Fleurs 3 - 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: 0.0941
- Wer: 6.6584
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: 62
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3259 | 0.6983 | 125 | 0.2217 | 9.7386 |
| 0.1565 | 1.3966 | 250 | 0.1212 | 6.7906 |
| 0.0982 | 2.0950 | 375 | 0.0994 | 6.6273 |
| 0.084 | 2.7933 | 500 | 0.0941 | 6.6584 |
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-fleurs3
Base model
openai/whisper-large-v3