---
license: apache-2.0
base_model: openai/whisper-base
tags:
- whisper-event
- generated_from_trainer
datasets:
- yt
metrics:
- wer
model-index:
- name: Whisper Small Indonesian
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: yt id
      type: yt
    metrics:
    - name: Wer
      type: wer
      value: 66.04630049931912
---

<!-- 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 Small Indonesian

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the yt id dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0175
- Wer: 66.0463

## 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: 4
- eval_batch_size: 2
- 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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4446        | 0.09  | 1000 | 1.2313          | 91.5959  |
| 1.0599        | 0.17  | 2000 | 1.1312          | 106.3420 |
| 1.1851        | 0.26  | 3000 | 1.0801          | 77.3166  |
| 1.0325        | 0.34  | 4000 | 1.0380          | 71.8436  |
| 1.008         | 0.43  | 5000 | 1.0175          | 66.0463  |


### Framework versions

- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3