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---
language:
- ur
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Urdu
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_11_0 ur
type: mozilla-foundation/common_voice_11_0
config: ur
split: test
args: ur
metrics:
- name: Wer
type: wer
value: 32.68135868933731
---
<!-- 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 Urdu
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co./openai/whisper-small) on the mozilla-foundation/common_voice_11_0 ur dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7803
- Wer: 32.6814
## 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: 64
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2634 | 3.85 | 200 | 0.5562 | 43.3518 |
| 0.0592 | 7.69 | 400 | 0.6271 | 40.8807 |
| 0.0121 | 11.54 | 600 | 0.7298 | 35.4506 |
| 0.0048 | 15.38 | 800 | 0.7803 | 32.6814 |
| 0.0039 | 19.23 | 1000 | 0.7940 | 33.3243 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
|