---
library_name: transformers
language:
- ur
license: apache-2.0
base_model: GogetaBlueMUI/whisper-small-ur
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Small Urdu V2 - Muhammad Abdullah
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 13.0
      type: mozilla-foundation/common_voice_13_0
      config: ur
      split: test
      args: 'config: ur, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 35.42311262376238
---

<!-- 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 Small Urdu V2 - Muhammad Abdullah

This model is a fine-tuned version of [GogetaBlueMUI/whisper-small-ur](https://huggingface.co/GogetaBlueMUI/whisper-small-ur) on the Common Voice 13.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7436
- Wer: 35.4231

## 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: 16
- eval_batch_size: 8
- seed: 42
- 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: 500
- training_steps: 1500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.068         | 1.9305 | 500  | 0.6670          | 37.1751 |
| 0.0182        | 3.8610 | 1000 | 0.7094          | 35.9684 |
| 0.0032        | 5.7915 | 1500 | 0.7436          | 35.4231 |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.21.0