---
license: apache-2.0
base_model: Talha/URDU-ASR
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: 1.0023598591821734
---

<!-- 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 is a fine-tuned version of [Talha/URDU-ASR](https://huggingface.co./Talha/URDU-ASR) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1901
- Wer: 1.0024
- Cer: 0.9455

## 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: 7.5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.85,0.99) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 19.3758       | 0.59  | 25   | 8.7836          | 1.0    | 0.9999 |
| 6.0744        | 1.17  | 50   | 4.7540          | 1.0    | 0.9999 |
| 4.446         | 1.76  | 75   | 4.0785          | 1.0    | 0.9999 |
| 3.7656        | 2.34  | 100  | 3.5164          | 1.0024 | 0.9457 |
| 3.4626        | 2.93  | 125  | 3.3191          | 1.0024 | 0.9454 |
| 3.2974        | 3.51  | 150  | 3.2566          | 1.0024 | 0.9449 |
| 3.2203        | 4.1   | 175  | 3.2009          | 1.0024 | 0.9456 |
| 3.1955        | 4.69  | 200  | 3.1901          | 1.0024 | 0.9455 |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1