| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: openai/whisper-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - wer |
| model-index: |
| - name: Shunya_Augmentation_enabled_attempt2 |
| 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. --> |
|
|
| # Shunya_Augmentation_enabled_attempt2 |
| |
| 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: 0.6338 |
| - Wer: 26.8203 |
| |
| ## 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: 0.0001 |
| - train_batch_size: 2 |
| - eval_batch_size: 4 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 500 |
| - training_steps: 100000 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:-------:|:------:|:---------------:|:-------:| |
| | 0.3379 | 3.9062 | 5000 | 0.7792 | 47.4376 | |
| | 0.1422 | 7.8125 | 10000 | 0.7314 | 38.2661 | |
| | 0.1088 | 11.7188 | 15000 | 0.7569 | 38.1037 | |
| | 0.0704 | 15.625 | 20000 | 0.7331 | 37.7788 | |
| | 0.0265 | 19.5312 | 25000 | 0.7670 | 39.1670 | |
| | 0.0179 | 23.4375 | 30000 | 0.7927 | 36.2428 | |
| | 0.0225 | 27.3438 | 35000 | 0.7842 | 35.8883 | |
| | 0.0227 | 31.25 | 40000 | 0.7847 | 34.4705 | |
| | 0.0167 | 35.1562 | 45000 | 0.7585 | 32.4472 | |
| | 0.0149 | 39.0625 | 50000 | 0.7667 | 31.9894 | |
| | 0.0288 | 42.9688 | 55000 | 0.7391 | 32.6983 | |
| | 0.0067 | 46.875 | 60000 | 0.7365 | 31.1475 | |
| | 0.0048 | 50.7812 | 65000 | 0.7247 | 29.8626 | |
| | 0.0184 | 54.6875 | 70000 | 0.7135 | 30.5272 | |
| | 0.0051 | 58.5938 | 75000 | 0.7035 | 29.5525 | |
| | 0.0185 | 62.5 | 80000 | 0.6938 | 29.1833 | |
| | 0.0008 | 66.4062 | 85000 | 0.6732 | 30.0399 | |
| | 0.0068 | 70.3125 | 90000 | 0.6482 | 28.3710 | |
| | 0.0065 | 74.2188 | 95000 | 0.6310 | 27.7212 | |
| | 0.0001 | 78.125 | 100000 | 0.6338 | 26.8203 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 5.3.0.dev0 |
| - Pytorch 2.9.0+cu126 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.2 |
|
|
