---
base_model: Shehryar718/URDU-ASR
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: URDU-ASR-25-EPOCH
  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: 0.47599520290920344
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# URDU-ASR-25-EPOCH

This model is a fine-tuned version of [Shehryar718/URDU-ASR](https://huggingface.co/Shehryar718/URDU-ASR) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6782
- Wer: 0.4760
- Cer: 0.1986

## 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: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.99) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 25
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 5.3707        | 1.0   | 341  | 1.3583          | 0.8266 | 0.3484 |
| 0.4814        | 2.0   | 683  | 0.7213          | 0.5187 | 0.2196 |
| 0.2821        | 3.0   | 1024 | 0.6354          | 0.4917 | 0.2066 |
| 0.2368        | 4.0   | 1366 | 0.6730          | 0.5122 | 0.2181 |
| 0.2105        | 5.0   | 1707 | 0.6430          | 0.4871 | 0.2076 |
| 0.1965        | 6.0   | 2049 | 0.6397          | 0.4902 | 0.2136 |
| 0.1879        | 7.0   | 2390 | 0.6397          | 0.4698 | 0.1951 |
| 0.1743        | 8.0   | 2732 | 0.6636          | 0.4739 | 0.1996 |
| 0.1632        | 9.0   | 3073 | 0.6752          | 0.4782 | 0.1996 |
| 0.1572        | 10.0  | 3415 | 0.6859          | 0.4874 | 0.2072 |
| 0.1586        | 11.0  | 3756 | 0.6761          | 0.4844 | 0.2069 |
| 0.1595        | 12.0  | 4098 | 0.6846          | 0.4746 | 0.1959 |
| 0.1534        | 13.0  | 4439 | 0.6750          | 0.4830 | 0.2034 |
| 0.16          | 14.0  | 4781 | 0.6653          | 0.4826 | 0.2038 |
| 0.1752        | 15.0  | 5122 | 0.6536          | 0.4727 | 0.1946 |
| 0.1739        | 16.0  | 5464 | 0.6753          | 0.4738 | 0.1912 |
| 0.1709        | 17.0  | 5805 | 0.6600          | 0.4730 | 0.1996 |
| 0.1676        | 18.0  | 6147 | 0.6691          | 0.4678 | 0.1919 |
| 0.1636        | 19.0  | 6488 | 0.6638          | 0.4772 | 0.1990 |
| 0.1593        | 20.0  | 6830 | 0.6787          | 0.4764 | 0.1976 |
| 0.1588        | 21.0  | 7171 | 0.6699          | 0.4772 | 0.1974 |
| 0.1525        | 22.0  | 7513 | 0.6827          | 0.4738 | 0.1962 |
| 0.1554        | 23.0  | 7854 | 0.6740          | 0.4736 | 0.1970 |
| 0.1522        | 24.0  | 8196 | 0.6791          | 0.4768 | 0.1989 |
| 0.1502        | 24.96 | 8525 | 0.6782          | 0.4760 | 0.1986 |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.4
- Tokenizers 0.14.1