whisper-small-urdu / README.md
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---
language:
- ur
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small UR
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
args: 'config: ur, split: test'
metrics:
- name: Wer
type: wer
value: 41.698656429942424
---
<!-- 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 Small UR - Muhammad Abdullah
This model is a fine-tuned version of [openai/whisper-Small](https://huggingface.co/openai/whisper-large) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9758
- Wer: 41.6987
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 10
- 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: 3500
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0074 | 9.62 | 1000 | 0.8238 | 42.0345 |
| 0.0003 | 19.23 | 2000 | 0.9381 | 42.6583 |
| 0.0002 | 28.85 | 3000 | 0.9758 | 41.6987 |
### Framework versions
- Transformers 4.25.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.7.0
- Tokenizers 0.13.2