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whisper-base-gcf-lora
This model is a fine-tuned version of openai/whisper-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.3078
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: 0.0005
- train_batch_size: 16
- 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: 50
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.2505 | 1.4085 | 200 | 3.8849 |
| 0.9034 | 2.8169 | 400 | 3.6258 |
| 0.6471 | 4.2254 | 600 | 3.4696 |
| 0.5793 | 5.6338 | 800 | 3.3785 |
| 0.5021 | 7.0423 | 1000 | 3.3078 |
Framework versions
- PEFT 0.18.1
- Transformers 5.5.0
- Pytorch 2.4.1+cu124
- Datasets 3.6.0
- Tokenizers 0.22.2
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Model tree for GwadaDLT/whisper-base-gcf-lora
Base model
openai/whisper-base