---
library_name: transformers
language:
- sun
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- SLR44_Augmented
metrics:
- wer
model-index:
- name: Whisper Small Sundanese
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: SLR44 Augmented Sundanese
      type: SLR44_Augmented
      args: 'split: train/test'
    metrics:
    - type: wer
      value: 13.09883470004316
      name: Wer
---

<!-- 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 Sundanese

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the SLR44 Augmented Sundanese dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1282
- Wer: 13.0988

## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.6373        | 0.4292 | 100  | 0.3069          | 25.1403 |
| 0.4107        | 0.8584 | 200  | 0.1883          | 17.6953 |
| 0.1919        | 1.2876 | 300  | 0.1628          | 15.6884 |
| 0.1769        | 1.7167 | 400  | 0.1486          | 14.1562 |
| 0.0698        | 2.1459 | 500  | 0.1371          | 14.2641 |
| 0.0599        | 2.5751 | 600  | 0.1334          | 13.6167 |
| 0.0604        | 3.0043 | 700  | 0.1288          | 13.5304 |
| 0.0259        | 3.4335 | 800  | 0.1300          | 13.1636 |
| 0.025         | 3.8627 | 900  | 0.1280          | 13.1420 |
| 0.0169        | 4.2918 | 1000 | 0.1282          | 13.0988 |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1