| --- |
| license: apache-2.0 |
| tags: |
| - whisper-event |
| - generated_from_trainer |
| metrics: |
| - wer |
| model-index: |
| - name: whisper-small-basque |
| 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-small-basque |
|
|
| This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1906 |
| - Wer: 9.5417 |
|
|
| ## 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: 128 |
| - eval_batch_size: 32 |
| - 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: 5000 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:| |
| | 0.17 | 0.33 | 1000 | 0.2697 | 15.6613 | |
| | 0.1163 | 0.66 | 2000 | 0.2198 | 11.7272 | |
| | 0.0966 | 0.99 | 3000 | 0.2009 | 10.2785 | |
| | 0.073 | 1.32 | 4000 | 0.1945 | 9.8476 | |
| | 0.0666 | 1.65 | 5000 | 0.1906 | 9.5417 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.25.1 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 2.8.0 |
| - Tokenizers 0.13.3 |
| |
