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---
datasets:
- mozilla-foundation/common_voice_11_0
language:
- ur
metrics:
- wer
library_name: transformers
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
model-index:
- name: Whisper Medium Urdu - Hassaan Butt
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: fleurs
type: mozilla-foundation/common_voice_11_0
config: ur
split: test
args: 'config: ps, split: test'
metrics:
- name: Wer
type: wer
value: 32.0
---
<!-- 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 Urdu - Hassaan Butt
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the common voice dataset.
It achieves the following results on the evaluation set:
- Wer: 32.0
## 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: 1e-05
- 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: 500
- training_steps: 3000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.283800 | 2.92 | 1000 | 0.466280 | 51.433879 |
| 0.090300 | 5.85 | 2000 | 0.448847 | 33.646813 |
| 0.036666 | 8.77 | 3000 | 0.420809 | 32.035004 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.11.0+cu113
- Datasets 11.0
- Tokenizers 0.13.2
|