| --- |
| library_name: transformers |
| language: |
| - ur |
| license: apache-2.0 |
| base_model: GogetaBlueMUI/whisper-medium-ur-v3 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - fsicoli/common_voice_19_0 |
| metrics: |
| - wer |
| model-index: |
| - name: Whisper Medium Ur - Your Name |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: Common Voice 19.0 |
| type: fsicoli/common_voice_19_0 |
| config: ur |
| split: test |
| args: 'config: ur, split: test' |
| metrics: |
| - name: Wer |
| type: wer |
| value: 25.0787058744725 |
| --- |
| |
| <!-- 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 Ur - Your Name |
|
|
| This model is a fine-tuned version of [GogetaBlueMUI/whisper-medium-ur-v3](https://huggingface.co/GogetaBlueMUI/whisper-medium-ur-v3) on the Common Voice 19.0 dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3692 |
| - Wer: 25.0787 |
|
|
| ## 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: 3e-06 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 16 |
| - optimizer: Use 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: 100 |
| - training_steps: 1000 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:------:|:----:|:---------------:|:-------:| |
| | 0.1648 | 0.3279 | 250 | 0.3832 | 28.1711 | |
| | 0.1748 | 0.6557 | 500 | 0.3737 | 30.1650 | |
| | 0.1887 | 0.9836 | 750 | 0.3587 | 24.8532 | |
| | 0.132 | 1.3108 | 1000 | 0.3692 | 25.0787 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.49.0 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 3.4.1 |
| - Tokenizers 0.21.0 |
|
|
