Edit model card

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

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

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
Downloads last month
17
Safetensors
Model size
110M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for digo-prayudha/IndoQA

Finetuned
(366)
this model

Dataset used to train digo-prayudha/IndoQA