---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_8_0
model-index:
- name: SHK_Urdu_Fine_Tuned_2
  results: []
---

<!-- 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. -->

# SHK_Urdu_Fine_Tuned_2

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice_8_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3107
- Wer: 0.7347

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 16.3705       | 1.69  | 100  | 4.1962          | 1.0    |
| 3.415         | 3.39  | 200  | 3.2513          | 1.0    |
| 3.2396        | 5.08  | 300  | 3.2481          | 1.0    |
| 3.2109        | 6.78  | 400  | 3.1929          | 1.0    |
| 3.1661        | 8.47  | 500  | 3.1312          | 1.0    |
| 3.1014        | 10.17 | 600  | 3.1059          | 0.9993 |
| 3.0761        | 11.86 | 700  | 3.0239          | 1.0    |
| 2.9687        | 13.56 | 800  | 2.8371          | 1.0    |
| 2.7406        | 15.25 | 900  | 2.4320          | 0.9978 |
| 2.2203        | 16.95 | 1000 | 2.0063          | 0.9834 |
| 1.7338        | 18.64 | 1100 | 1.6290          | 0.8753 |
| 1.3901        | 20.34 | 1200 | 1.4847          | 0.7904 |
| 1.1757        | 22.03 | 1300 | 1.3944          | 0.7649 |
| 1.0581        | 23.73 | 1400 | 1.3455          | 0.7520 |
| 0.9609        | 25.42 | 1500 | 1.3346          | 0.7417 |
| 0.9147        | 27.12 | 1600 | 1.3014          | 0.7339 |
| 0.8662        | 28.81 | 1700 | 1.3107          | 0.7347 |


### Framework versions

- Transformers 4.21.0
- Pytorch 1.11.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1