---
language:
- id
license: cc
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
- magic_data,
- titml
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Small 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
    metrics:
    - name: Wer
      type: wer
      value: 6.059208706077654
---


# Whisper Small Indonesian

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0, magic_data, titml, google/fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1022
- Wer: 6.0592

## 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: 32
- eval_batch_size: 16
- 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: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.173         | 0.66  | 1000  | 0.1654          | 9.8773 |
| 0.0771        | 1.32  | 2000  | 0.1290          | 7.7515 |
| 0.0569        | 1.99  | 3000  | 0.1056          | 7.1475 |
| 0.0274        | 2.65  | 4000  | 0.1044          | 6.6264 |
| 0.0072        | 3.31  | 5000  | 0.1023          | 6.3543 |
| 0.009         | 3.97  | 6000  | 0.1000          | 6.3359 |
| 0.0033        | 4.63  | 7000  | 0.1022          | 6.0592 |
| 0.002         | 5.29  | 8000  | 0.1051          | 6.1560 |
| 0.0028        | 5.96  | 9000  | 0.1052          | 6.1007 |
| 0.0013        | 6.62  | 10000 | 0.1063          | 6.1376 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 2.7.0
- Tokenizers 0.13.1