| --- |
| license: apache-2.0 |
| base_model: openai/whisper-large |
| tags: |
| - generated_from_trainer |
| metrics: |
| - wer |
| model-index: |
| - name: whisper-large-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-large-basque |
|
|
| This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2281 |
| - Wer: 11.8969 |
|
|
| ## 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: 256 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - distributed_type: multi-GPU |
| - num_devices: 2 |
| - total_train_batch_size: 512 |
| - total_eval_batch_size: 64 |
| - 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:| |
| | 0.1763 | 0.42 | 500 | 0.2915 | 17.9244 | |
| | 0.1415 | 0.84 | 1000 | 0.2468 | 15.0738 | |
| | 0.1182 | 1.26 | 1500 | 0.2483 | 14.3144 | |
| | 0.1234 | 1.68 | 2000 | 0.2520 | 14.1380 | |
| | 0.0961 | 2.1 | 2500 | 0.2397 | 13.6557 | |
| | 0.0952 | 2.52 | 3000 | 0.2360 | 12.7999 | |
| | 0.0912 | 2.94 | 3500 | 0.2264 | 12.4284 | |
| | 0.0717 | 3.36 | 4000 | 0.2295 | 12.0590 | |
| | 0.0698 | 3.78 | 4500 | 0.2260 | 12.2581 | |
| | 0.0582 | 4.2 | 5000 | 0.2281 | 11.8969 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.38.0 |
| - Pytorch 2.1.1+cu121 |
| - Datasets 2.8.0 |
| - Tokenizers 0.15.2 |
| |
