---
datasets:
- mozilla-foundation/common_voice_11_0
language:
- ur
metrics:
- wer
library_name: transformers

license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer

model-index:
- name: Whisper Medium Urdu - Hassaan Butt
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: fleurs
      type: mozilla-foundation/common_voice_11_0
      config: ur
      split: test
      args: 'config: ps, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 32.0

---

<!-- 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 Urdu - Hassaan Butt

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co./openai/whisper-medium) on the common voice dataset.
It achieves the following results on the evaluation set:

- Wer: 32.0

## 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: 8
- eval_batch_size: 8
- 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: 3000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.283800      | 2.92  | 1000 | 0.466280      | 51.433879 |
| 0.090300      | 5.85  | 2000 | 0.448847      | 33.646813 |
| 0.036666      | 8.77  | 3000 | 0.420809        | 32.035004 |



### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.11.0+cu113
- Datasets 11.0
- Tokenizers 0.13.2