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---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-small-ug
results: []
datasets:
- mozilla-foundation/common_voice_15_0
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-small-ug
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset. The model is trained on
transcripts written in Uyghur Latin Script via utilising Uzbek Tokeniser , as Uyghur Tokeniser is not included in Whisper. Therefore, the output of the model is
in Uyghur Latin Script. To convert the output to the Uyghur Arabic Script, you can use the Uyghur script converter: https://github.com/neouyghur/ScriptConverter4Uyghur
or you can use online script converter: https://www.yulghun.com/imla/convert.html
It achieves the following results on the evaluation set:
- Loss: 0.3563
- Wer: 26.8793
## 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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2677 | 1.43 | 1000 | 0.4063 | 34.1157 |
| 0.1035 | 2.85 | 2000 | 0.3375 | 29.2183 |
| 0.0226 | 4.28 | 3000 | 0.3472 | 27.5155 |
| 0.0073 | 5.71 | 4000 | 0.3563 | 26.8793 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0 |