README.md

---
language:
- id
base_model:
- openai/whisper-tiny
pipeline_tag: automatic-speech-recognition
datasets:
- mozilla-foundation/common_voice_23_0
---

# Whisper Tiny Model – Indonesian ASR

## Model Description
This model is a fine-tuned version of **openai/whisper-tiny** for **Automatic Speech Recognition (ASR)** in **Indonesian (id)**.  
It supports transcription of Indonesian speech into text across various audio conditions, with performance and resource usage depending on the selected model size.

## Intended Use
- Indonesian speech-to-text transcription
- Research and experimentation
- Educational and academic purposes
- Application development and benchmarking

Model variants (tiny, base, small, medium, large) differ in accuracy, speed, and hardware requirements. Users should select the size that best matches their constraints and objectives.

## Limitations
- Transcription quality depends on audio clarity, speaker accent, and background noise
- Smaller variants may produce higher error rates on long or complex audio
- Larger variants require significantly more compute and memory
- Outputs should be reviewed before use in critical or high-risk applications

## Training Data
This model was fine-tuned using **Mozilla Common Voice v23.0 (Indonesian)**.  
Common Voice is a publicly available, community-driven speech dataset released by Mozilla under a permissive license.  
Dataset characteristics such as speaker diversity, recording quality, and utterance length may influence model behavior.

## Evaluation
The model is typically evaluated using **Word Error Rate (WER)**.  
Evaluation results may vary depending on dataset, domain, audio conditions, and model size.

## Training results
| Step | Training Loss |
|------|---------------|
| 100|	1.282900|
|200|	0.682300|
|300|	0.568900|
|400|	0.487500|
|500|	0.372700|
|600|	0.375500|
|700|	0.276200|
|800|	0.226000|
|900|	0.223800|
|1000|	0.188600|
|1100|	0.164300|
|1200|	0.151400|
|1300|	0.130000|
|1400|	0.133900|
|1500|	0.119700|
|1550|	0.117300|