---
library_name: transformers
language:
- ur
license: apache-2.0
base_model: GogetaBlueMUI/whisper-medium-ur-jalandhary
tags:
- generated_from_trainer
datasets:
- mirfan899/jalandhary_asr
metrics:
- wer
model-index:
- name: Whisper Medium Ur - Jalandhary ASR Fine-Tuned
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Jalandhary ASR
      type: mirfan899/jalandhary_asr
      args: 'split: test'
    metrics:
    - name: Wer
      type: wer
      value: 18.709390064975896
---

<!-- 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. -->

# Whisper Medium Ur - Jalandhary ASR Fine-Tuned

This model is a fine-tuned version of [GogetaBlueMUI/whisper-medium-ur-jalandhary](https://huggingface.co/GogetaBlueMUI/whisper-medium-ur-jalandhary) on the Jalandhary ASR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1395
- Wer: 18.7094

## 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: 5e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use 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: 100
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.1443        | 0.4859 | 500  | 0.1518          | 19.8360 |
| 0.1315        | 0.9718 | 1000 | 0.1395          | 18.7094 |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.2
- Tokenizers 0.21.0