Whisper Fine-tuning Event: Winning Models
Collection
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Updated
Whisper Large-V2 Nepali
This model is a fine-tuned version of DrishtiSharma/whisper-large-v2-hindi-3k-steps on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.8851
- Wer: 9.7561
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: 8
- 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: 100
- training_steps: 200
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0 | 200.0 | 200 | 0.8851 | 9.7561 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2
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Dataset used to train DrishtiSharma/whisper-large-v2-hindi-to-nepali-transfer-learning-200-steps
Collection including DrishtiSharma/whisper-large-v2-hindi-to-nepali-transfer-learning-200-steps
Evaluation results
- Wer on mozilla-foundation/common_voice_11_0 ne-NPtest set self-reported9.756