---
language:
- id
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Base Indonesian
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0 id
      type: mozilla-foundation/common_voice_11_0
      config: id
      split: test
      args: id
    metrics:
    - name: Wer
      type: wer
      value: 23.757262750161395
---

<!-- 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 Base Indonesian

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the mozilla-foundation/common_voice_11_0 id dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5101
- Wer: 23.7573

## 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: 2e-05
- train_batch_size: 64
- eval_batch_size: 32
- 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: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2041        | 4.95  | 500  | 0.3906          | 23.9140 |
| 0.015         | 9.9   | 1000 | 0.4619          | 24.3752 |
| 0.0032        | 14.85 | 1500 | 0.4901          | 23.7803 |
| 0.0015        | 19.8  | 2000 | 0.5101          | 23.7573 |
| 0.001         | 24.75 | 2500 | 0.5265          | 23.9786 |
| 0.0008        | 29.7  | 3000 | 0.5399          | 24.1216 |
| 0.0006        | 34.65 | 3500 | 0.5501          | 23.8956 |
| 0.0005        | 39.6  | 4000 | 0.5583          | 24.0570 |
| 0.0004        | 44.55 | 4500 | 0.5638          | 24.1815 |
| 0.0004        | 49.5  | 5000 | 0.5659          | 24.1492 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2