whisper-large-v3-sr
This model is a fine-tuned version of openai/whisper-large-v3 on the Common Voice 16.1 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3961
- Wer: 17.2694
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 |
|---|---|---|---|---|
| 0.0498 | 4.81 | 1000 | 0.2004 | 20.1799 |
| 0.0042 | 9.62 | 2000 | 0.3225 | 18.2395 |
| 0.0001 | 14.42 | 3000 | 0.3799 | 17.2694 |
| 0.0001 | 19.23 | 4000 | 0.3961 | 17.2694 |
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.1+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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Base model
openai/whisper-large-v3