metadata

license: mit
base_model: indolem/indobert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - jakartaresearch/indoqa
model-index:
  - name: IndoQA
    results: []
language:
  - id
pipeline_tag: question-answering

IndoQA

This model is a fine-tuned version of indolem/indobert-base-uncased on jakartaresearch/indoqa. It achieves the following results on the evaluation set:

Loss: 1.4807

How to use this model in Transformers Library

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)

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

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.15.0
Tokenizers 0.15.0