---
base_model: openai/whisper-large-v3
datasets:
- google/fleurs
library_name: transformers
license: apache-2.0
metrics:
- wer
model-index:
- name: whisper-large-v3-Urdu-Version1
  results: []
language:
- ur
pipeline_tag: automatic-speech-recognition
---

<!-- 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-large-v3-Urdu-Version1

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) on the fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3244
- Wer: 20.6725

## 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: 3e-06
- 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: 1000
- training_steps: 20000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Wer     |
|:-------------:|:-------:|:-----:|:---------------:|:-------:|
| 0.3271        | 6.7340  | 2000  | 0.3375          | 21.5842 |
| 0.3107        | 13.4680 | 4000  | 0.3244          | 20.9093 |
| 0.2797        | 20.2020 | 6000  | 0.3205          | 20.8383 |
| 0.2639        | 26.9360 | 8000  | 0.3202          | 20.5778 |
| 0.2529        | 33.6700 | 10000 | 0.3216          | 20.7909 |
| 0.26          | 40.4040 | 12000 | 0.3230          | 20.6843 |
| 0.2485        | 47.1380 | 14000 | 0.3244          | 20.6725 |


### Framework versions

- PEFT 0.12.1.dev0
- Transformers 4.45.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1