openai/whisper-large-v3
This model is a fine-tuned version of openai/whisper-large-v3 on the common_voice_16_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5425
- Wer: 41.0489
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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1378 | 4.35 | 500 | 0.5576 | 51.2554 |
| 0.0024 | 8.7 | 1000 | 0.5425 | 41.0489 |
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0
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Model tree for sanchit-gandhi/whisper-large-v3-ft-cv16-mn-freeze-encoder
Base model
openai/whisper-large-v3