---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base-960h
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: Wav2Vec-Urdu-Test4
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_17_0
      type: common_voice_17_0
      config: ur
      split: test
      args: ur
    metrics:
    - name: Wer
      type: wer
      value: 99.17818453492715
---

<!-- 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. -->

# Wav2Vec-Urdu-Test4

This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0093
- Wer: 99.1782

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 300
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 19   | 18.2298         | 105.9395 |
| 19.0476       | 2.0   | 38   | 5.0072          | 100.0374 |
| 6.1409        | 3.0   | 57   | 1.9519          | 98.3190  |
| 1.5743        | 4.0   | 76   | 1.0208          | 98.5805  |
| 1.5743        | 5.0   | 95   | 0.8330          | 99.3650  |
| 1.0023        | 6.0   | 114  | 0.7071          | 98.3937  |
| 0.8148        | 7.0   | 133  | 0.7718          | 95.5174  |
| 0.7533        | 8.0   | 152  | 0.6405          | 93.5002  |
| 0.7533        | 9.0   | 171  | 1.5573          | 95.2559  |
| 0.7768        | 9.48  | 180  | 1.0093          | 99.1782  |


### Framework versions

- Transformers 4.50.0
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1