| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: openai/whisper-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - wer |
| model-index: |
| - name: whisper-base-v4 |
| 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. --> |
|
|
| # whisper-base-v4 |
|
|
| This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.1814 |
| - Wer: 43.8709 |
|
|
| ## 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: 0.0002 |
| - train_batch_size: 16 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 500 |
| - training_steps: 2000 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:| |
| | 0.4275 | 10.0 | 500 | 0.8866 | 50.2836 | |
| | 0.069 | 20.0 | 1000 | 1.0774 | 47.0699 | |
| | 0.0134 | 30.0 | 1500 | 1.1680 | 44.5689 | |
| | 0.002 | 40.0 | 2000 | 1.1814 | 43.8709 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.45.2 |
| - Pytorch 2.5.0+cu121 |
| - Datasets 3.0.2 |
| - Tokenizers 0.20.1 |
| |
