Whisper Large V3 fa fleurs- 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: 0.1409
- Wer: 33.0741
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: 125
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1605 | 1.1521 | 250 | 0.1698 | 16.5640 |
| 0.1076 | 2.3041 | 500 | 0.1445 | 26.3351 |
| 0.0938 | 3.4562 | 750 | 0.1406 | 34.2381 |
| 0.088 | 4.6083 | 1000 | 0.1409 | 33.0741 |
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-fa-fleurs
Base model
openai/whisper-large-v3Dataset used to train liqi03/whisper-large-v3-fa-fleurs
Evaluation results
- Wer on Google Fleursself-reported33.074