| --- |
| license: apache-2.0 |
| base_model: openai/whisper-medium |
| tags: |
| - generated_from_trainer |
| metrics: |
| - wer |
| model-index: |
| - name: whisper-medium-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-medium-basque |
|
|
| This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1445 |
| - Wer: 8.2615 |
|
|
| ## 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: 96 |
| - eval_batch_size: 48 |
| - 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: 10000 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:-----:|:-----:|:---------------:|:-------:| |
| | 0.1909 | 0.12 | 500 | 0.2820 | 22.5178 | |
| | 0.1253 | 0.25 | 1000 | 0.2133 | 16.1484 | |
| | 0.1046 | 0.37 | 1500 | 0.1899 | 12.7139 | |
| | 0.0874 | 0.5 | 2000 | 0.1793 | 11.4088 | |
| | 0.0836 | 0.62 | 2500 | 0.1621 | 10.5470 | |
| | 0.0726 | 0.74 | 3000 | 0.1597 | 10.1161 | |
| | 0.0707 | 0.87 | 3500 | 0.1498 | 9.4355 | |
| | 0.0652 | 0.99 | 4000 | 0.1470 | 8.5737 | |
| | 0.0416 | 1.11 | 4500 | 0.1482 | 8.5925 | |
| | 0.0415 | 1.24 | 5000 | 0.1490 | 8.6299 | |
| | 0.0394 | 1.36 | 5500 | 0.1474 | 8.0929 | |
| | 0.0381 | 1.49 | 6000 | 0.1425 | 8.3489 | |
| | 0.038 | 1.61 | 6500 | 0.1414 | 8.2990 | |
| | 0.0333 | 1.73 | 7000 | 0.1391 | 8.2553 | |
| | 0.0342 | 1.86 | 7500 | 0.1382 | 8.3864 | |
| | 0.0341 | 1.98 | 8000 | 0.1386 | 8.4301 | |
| | 0.0196 | 2.11 | 8500 | 0.1447 | 8.1429 | |
| | 0.0208 | 2.23 | 9000 | 0.1448 | 8.3115 | |
| | 0.018 | 2.35 | 9500 | 0.1449 | 8.3177 | |
| | 0.0172 | 2.48 | 10000 | 0.1445 | 8.2615 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.38.0 |
| - Pytorch 2.1.1+cu121 |
| - Datasets 2.8.0 |
| - Tokenizers 0.15.2 |
| |
