---
language:
- ur
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Large-v2 Urdu
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0 ur
      type: mozilla-foundation/common_voice_11_0
      config: ur
      split: test
      args: ur
    metrics:
    - name: Wer
      type: wer
      value: 23.5020721174329
---

<!-- 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-v2 Urdu

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co./openai/whisper-large-v2) on the mozilla-foundation/common_voice_11_0 ur dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5947
- Wer: 23.5021

## 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: 32
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 1000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.1935        | 1.1   | 200  | 0.4241          | 29.6526 |
| 0.0649        | 3.09  | 400  | 0.4683          | 26.0622 |
| 0.0156        | 5.08  | 600  | 0.5444          | 25.8104 |
| 0.0039        | 7.08  | 800  | 0.5947          | 23.5021 |
| 0.0019        | 9.07  | 1000 | 0.6123          | 23.8933 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2