| | --- |
| | library_name: peft |
| | license: mit |
| | base_model: openai/whisper-large-v3-turbo |
| | tags: |
| | - base_model:adapter:openai/whisper-large-v3-turbo |
| | - lora |
| | - transformers |
| | metrics: |
| | - wer |
| | model-index: |
| | - name: model |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # model |
| |
|
| | This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0984 |
| | - Wer: 12.1817 |
| |
|
| | ## 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: 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: 500 |
| | - training_steps: 4000 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Wer | |
| | |:-------------:|:-------:|:----:|:---------------:|:-------:| |
| | | 0.0432 | 4.2373 | 1000 | 0.0928 | 13.0043 | |
| | | 0.0211 | 8.4746 | 2000 | 0.0946 | 13.2132 | |
| | | 0.0126 | 12.7119 | 3000 | 0.0959 | 12.5996 | |
| | | 0.0136 | 16.9492 | 4000 | 0.0984 | 12.1817 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - PEFT 0.17.1 |
| | - Transformers 4.55.2 |
| | - Pytorch 2.7.0+cu126 |
| | - Datasets 3.6.0 |
| | - Tokenizers 0.21.4 |
