| --- |
| license: apache-2.0 |
| base_model: openai/whisper-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - wer |
| model-index: |
| - name: whisper-base-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-base-basque |
|
|
| This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2498 |
| - Wer: 62.1644 |
|
|
| ## 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: 192 |
| - eval_batch_size: 96 |
| - 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 | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:| |
| | 0.4078 | 0.25 | 500 | 0.5613 | 136.6055 | |
| | 0.2533 | 0.5 | 1000 | 0.3973 | 105.6700 | |
| | 0.1994 | 0.74 | 1500 | 0.3350 | 73.1485 | |
| | 0.1723 | 0.99 | 2000 | 0.3101 | 55.7387 | |
| | 0.1403 | 1.24 | 2500 | 0.2895 | 49.8689 | |
| | 0.1318 | 1.49 | 3000 | 0.2800 | 70.4321 | |
| | 0.1279 | 1.73 | 3500 | 0.2711 | 80.4296 | |
| | 0.1192 | 1.98 | 4000 | 0.2667 | 60.5533 | |
| | 0.104 | 2.23 | 4500 | 0.2605 | 54.0402 | |
| | 0.0986 | 2.48 | 5000 | 0.2601 | 53.4158 | |
| | 0.0929 | 2.73 | 5500 | 0.2539 | 61.0653 | |
| | 0.0971 | 2.97 | 6000 | 0.2521 | 45.2104 | |
| | 0.0806 | 3.22 | 6500 | 0.2526 | 51.5736 | |
| | 0.0812 | 3.47 | 7000 | 0.2509 | 53.9903 | |
| | 0.0817 | 3.72 | 7500 | 0.2498 | 56.8440 | |
| | 0.0799 | 3.96 | 8000 | 0.2511 | 65.1305 | |
| | 0.0723 | 4.21 | 8500 | 0.2500 | 55.6326 | |
| | 0.0724 | 4.46 | 9000 | 0.2498 | 60.2910 | |
| | 0.0707 | 4.71 | 9500 | 0.2501 | 59.5854 | |
| | 0.0685 | 4.96 | 10000 | 0.2498 | 62.1644 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.38.0 |
| - Pytorch 2.1.1+cu121 |
| - Datasets 2.8.0 |
| - Tokenizers 0.15.2 |
| |
