---
language:
- id
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
- magic_data
- TITML
metrics:
- wer
model-index:
- name: Whisper Large 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: 6.248270773771097
---

<!-- 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 Large Indonesian

This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the mozilla-foundation/common_voice_11_0, magic_data, titml id dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2034
- Wer: 6.2483

## 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-06
- train_batch_size: 12
- eval_batch_size: 12
- 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.1516        | 0.5   | 1000  | 0.1730          | 6.5664 |
| 0.1081        | 1.0   | 2000  | 0.1638          | 6.3682 |
| 0.0715        | 1.49  | 3000  | 0.1803          | 6.2713 |
| 0.1009        | 1.99  | 4000  | 0.1796          | 6.2667 |
| 0.0387        | 2.49  | 5000  | 0.2054          | 6.4927 |
| 0.0494        | 2.99  | 6000  | 0.2034          | 6.2483 |
| 0.0259        | 3.48  | 7000  | 0.2226          | 6.3497 |
| 0.0265        | 3.98  | 8000  | 0.2274          | 6.4004 |
| 0.0232        | 4.48  | 9000  | 0.2443          | 6.5618 |
| 0.015         | 4.98  | 10000 | 0.2413          | 6.4927 |

### Framework versions

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