whisper-large-v3-ivn-v1
This model is a fine-tuned version of openai/whisper-large-v3 on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.8302
- Wer: 70.5679
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 |
|---|---|---|---|---|
| 0.0274 | 14.29 | 1000 | 1.4520 | 78.4974 |
| 0.0033 | 28.57 | 2000 | 1.6206 | 73.4296 |
| 0.0004 | 42.86 | 3000 | 1.7704 | 70.3553 |
| 0.0002 | 57.14 | 4000 | 1.8302 | 70.5679 |
Framework versions
- Transformers 4.37.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.1
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Model tree for ninninz/whisper-large-v3-ivn-v1
Base model
openai/whisper-large-v3