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---
language:
- ur
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_7_0
metrics:
- wer
model-index:
- name: Whisper Small Ur - Bakht Ullah
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 7.0
type: mozilla-foundation/common_voice_7_0
args: 'config: ur, split: test'
metrics:
- name: Wer
type: wer
value: 47.34088927637315
---
<!-- 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 - Bakht Ullah
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 7.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8930
- Wer: 47.3409
## 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: 16
- 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: 100
- training_steps: 300
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6104 | 4.17 | 100 | 1.1037 | 163.3827 |
| 0.0242 | 8.33 | 200 | 0.8656 | 47.6024 |
| 0.0042 | 12.5 | 300 | 0.8930 | 47.3409 |
### Framework versions
- Transformers 4.25.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.2
|