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Whisper Large v2 Hi - Kabin
This model is a fine-tuned version of openai/whisper-large-v2 on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3904
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: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.553 | 0.6944 | 25 | 0.8388 |
| 0.508 | 1.3889 | 50 | 0.4456 |
| 0.3276 | 2.0833 | 75 | 0.3984 |
| 0.16 | 2.7778 | 100 | 0.3904 |
Framework versions
- PEFT 0.9.0
- Transformers 4.46.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1
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Model tree for girikabin/whisper-NEPALI-LARGE-v2-common-17
Base model
openai/whisper-large-v2