---
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: 0.4924368447522148
---

<!-- 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: 0.7833
- Wer: 0.4924
- Cer: 0.2059

## 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: 0.00025
- 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 3.5981        | 1.0   | 341  | 0.7487          | 0.5453 | 0.2200 |
| 0.2559        | 2.0   | 683  | 0.7159          | 0.5086 | 0.2077 |
| 0.3018        | 3.0   | 1024 | 0.7059          | 0.5457 | 0.2325 |
| 0.2848        | 4.0   | 1366 | 0.6575          | 0.5464 | 0.2350 |
| 0.2599        | 5.0   | 1707 | 0.6924          | 0.5436 | 0.2346 |
| 0.2479        | 6.0   | 2049 | 0.6785          | 0.5372 | 0.2254 |
| 0.2363        | 7.0   | 2390 | 0.7261          | 0.5356 | 0.2284 |
| 0.2225        | 8.0   | 2732 | 0.7228          | 0.5199 | 0.2268 |
| 0.2038        | 9.0   | 3073 | 0.7688          | 0.5248 | 0.2218 |
| 0.1944        | 10.0  | 3415 | 0.7385          | 0.5384 | 0.2298 |
| 0.1908        | 11.0  | 3756 | 0.7569          | 0.5325 | 0.2283 |
| 0.1899        | 12.0  | 4098 | 0.7458          | 0.5088 | 0.2106 |
| 0.1728        | 13.0  | 4439 | 0.7386          | 0.5326 | 0.2236 |
| 0.1762        | 14.0  | 4781 | 0.7521          | 0.5297 | 0.2265 |
| 0.1762        | 15.0  | 5122 | 0.7338          | 0.5197 | 0.2184 |
| 0.1666        | 16.0  | 5464 | 0.7795          | 0.5294 | 0.2149 |
| 0.1605        | 17.0  | 5805 | 0.7622          | 0.5092 | 0.2211 |
| 0.1539        | 18.0  | 6147 | 0.7756          | 0.5144 | 0.2132 |
| 0.1472        | 19.0  | 6488 | 0.7522          | 0.4989 | 0.2094 |
| 0.1399        | 20.0  | 6830 | 0.7691          | 0.5144 | 0.2171 |
| 0.1341        | 21.0  | 7171 | 0.7673          | 0.4992 | 0.2079 |
| 0.1278        | 22.0  | 7513 | 0.7807          | 0.4889 | 0.2005 |
| 0.1235        | 23.0  | 7854 | 0.7924          | 0.4932 | 0.2060 |
| 0.1189        | 24.0  | 8196 | 0.7876          | 0.4954 | 0.2060 |
| 0.1167        | 24.96 | 8525 | 0.7833          | 0.4924 | 0.2059 |


### Framework versions

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