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# IndoQA

This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on [jakartaresearch/indoqa](https://huggingface.co/datasets/jakartaresearch/indoqa).
It achieves the following results on the evaluation set:
- Loss: 1.4807

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- 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
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 207  | 1.9698          |
| No log        | 2.0   | 414  | 1.8862          |
| 0.9416        | 3.0   | 621  | 1.4807          |

### How to use this model in Transformers Library

```python
from transformers import pipeline

question = "Berapa jumlah pulau yang ada di indonesia?"
context = "Indonesia adalah negara kepulauan, Dengan jumlah pulau sekitar 17 ribu"

from transformers import pipeline

question_answerer = pipeline("question-answering", model="digo-prayudha/IndoQA")
question_answerer(question=question, context=context)
```

### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
{"language": ["id"], "license": "mit", "tags": ["generated_from_trainer"], "datasets": ["jakartaresearch/indoqa"], "base_model": "indolem/indobert-base-uncased", "pipeline_tag": "question-answering", "widget": [{"text": "Berapa jumlah pulau yang ada di indonesia?", "context": "Indonesia adalah negara kepulauan, Dengan jumlah pulau sekitar 17 ribu", "example_title": "Examples"}], "model-index": [{"name": "IndoQA", "results": []}]}
transformers tensorboard safetensors bert question-answering generated_from_trainer id dataset:jakartaresearch/indoqa base_model:indolem/indobert-base-uncased license:mit endpoints_compatible region:us