---
language:
- id
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
- magic_data
- titml
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Tiny 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: 18.28368532693904
---

# Whisper Tiny Indonesian

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the mozilla-foundation/common_voice_11_0, magic_data, titml and google/fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2409
- Wer: 18.2837

## 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     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.4103        | 0.66  | 1000  | 0.3802          | 27.0497 |
| 0.2682        | 1.32  | 2000  | 0.3223          | 22.9365 |
| 0.2381        | 1.99  | 3000  | 0.2884          | 20.8245 |
| 0.1606        | 2.65  | 4000  | 0.2727          | 20.1928 |
| 0.1246        | 3.31  | 5000  | 0.2596          | 18.9984 |
| 0.1344        | 3.97  | 6000  | 0.2482          | 18.7540 |
| 0.0975        | 4.63  | 7000  | 0.2471          | 18.6388 |
| 0.0916        | 5.29  | 8000  | 0.2436          | 18.9615 |
| 0.0854        | 5.96  | 9000  | 0.2413          | 18.3114 |
| 0.0812        | 6.62  | 10000 | 0.2409          | 18.2837 |


### Framework versions

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