|
--- |
|
license: gpl-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 |
|
language: |
|
- ug |
|
--- |
|
|
|
<!-- 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 |
