Whisper-large-v3-burmese
This model is a fine-tuned version of openai/whisper-large-v3 on the myanmar-speech-dataset-openslr-80 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1044
- Cer: 18.5592
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: 2e-05
- train_batch_size: 1
- eval_batch_size: 1
- 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: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 0.2102 | 0.4392 | 1000 | 0.1902 | 27.2963 |
| 0.1191 | 0.8783 | 2000 | 0.1044 | 18.5592 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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Base model
openai/whisper-large-v3