---
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 Medium 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: 3.993359771281011
---

<!-- 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 Medium Indonesian

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_11_0, magic_data, titml id dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0698
- Wer: 3.9934

## 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: 16
- 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.0252        | 0.35  | 1000  | 0.0733          | 4.4822 |
| 0.0222        | 0.7   | 2000  | 0.0698          | 4.3392 |
| 0.0166        | 1.06  | 3000  | 0.0696          | 4.2378 |
| 0.0117        | 1.41  | 4000  | 0.0679          | 4.0810 |
| 0.0295        | 1.76  | 5000  | 0.0671          | 4.0856 |
| 0.0147        | 2.11  | 6000  | 0.0690          | 4.0302 |
| 0.0157        | 2.47  | 7000  | 0.0698          | 3.9934 |
| 0.0113        | 2.82  | 8000  | 0.0698          | 4.0302 |
| 0.0101        | 3.17  | 9000  | 0.0707          | 4.0579 |
| 0.0076        | 3.52  | 10000 | 0.0708          | 4.0625 |


### Framework versions

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