Whisper Large Mongolian
This model is a fine-tuned version of openai/whisper-large-v2 on the Common Voice 16.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4028
- Wer: 37.2336
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: 4
- 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: 50
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3446 | 0.99 | 1000 | 0.4391 | 51.4572 |
| 0.1481 | 1.98 | 2000 | 0.3765 | 42.2412 |
| 0.076 | 2.97 | 3000 | 0.3830 | 39.0822 |
| 0.0149 | 3.96 | 4000 | 0.4028 | 37.2336 |
Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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openai/whisper-large-v2