Configuration Parsing Warning:In adapter_config.json: "peft.task_type" must be a string
whisper-large-v3-turbo-gurmukhi-lora
This model is a fine-tuned version of openai/whisper-large-v3-turbo on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.6186
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_BNB 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: 100
- training_steps: 1000
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.1
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 18.5560 | 1.25 | 50 | 2.2197 |
| 14.4289 | 2.5 | 100 | 1.7854 |
| 13.4670 | 3.75 | 150 | 1.6946 |
| 12.9902 | 5.0 | 200 | 1.6491 |
| 12.6007 | 6.25 | 250 | 1.6347 |
| 12.4687 | 7.5 | 300 | 1.6227 |
| 12.3255 | 8.75 | 350 | 1.6154 |
| 12.2176 | 10.0 | 400 | 1.6133 |
| 12.0832 | 11.25 | 450 | 1.6163 |
| 12.0028 | 12.5 | 500 | 1.6153 |
| 11.9251 | 13.75 | 550 | 1.6186 |
Framework versions
- PEFT 0.18.1
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.5
- Tokenizers 0.22.2
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# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("abhi8799/whisper-large-v3-turbo-gurmukhi-lora", device_map="auto")