---
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: URDU-ASR
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_13_0
      type: common_voice_13_0
      config: ur
      split: test
      args: ur
    metrics:
    - name: Wer
      type: wer
      value: 0.49680838717165077
---

<!-- 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. -->

# URDU-ASR

This model was trained from scratch on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6632
- Wer: 0.4968
- Cer: 0.2099

## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.85,0.9) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 1.9625        | 1.0   | 341  | 0.7371          | 0.5348 | 0.2190 |
| 0.2156        | 2.0   | 683  | 0.7057          | 0.5103 | 0.2169 |
| 0.2451        | 3.0   | 1024 | 0.6654          | 0.5161 | 0.2214 |
| 0.199         | 4.0   | 1366 | 0.6707          | 0.5089 | 0.2153 |
| 0.1657        | 4.99  | 1705 | 0.6632          | 0.4968 | 0.2099 |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1