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openai/whisper-large-v3
This model is a fine-tuned version of openai/whisper-large-v3 on the OpenSLR54 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0448
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 OptimizerNames.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: 10
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.3183 | 1.0 | 93 | 0.1889 |
| 0.1722 | 2.0 | 186 | 0.0798 |
| 0.0646 | 3.0 | 279 | 0.0448 |
Framework versions
- PEFT 0.14.0
- Transformers 4.47.1
- Pytorch 2.5.1+cxx11.abi
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for kiranpantha/whisper-large-v3-nepali-lora-ex-1
Base model
openai/whisper-large-v3