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---
tags:
- generated_from_trainer
model-index:
- name: fine-tuned-viquad-hgf
results: []
---
<!-- 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. -->
# FINE-TUNED-VIQUAD-HGF
This model is a fine-tuned version of [bhavikardeshna/xlm-roberta-base-vietnamese](https://huggingface.co/bhavikardeshna/xlm-roberta-base-vietnamese) on the [UIT-ViQuAD](https://github.com/windhashira06/Demo-QA-Extraction-system/blob/main/Dataset/UIT-ViQuAD.json) dataset.
## Model description
The model is described in [Cascading Adaptors to Leverage English Data to Improve Performance of
Question Answering for Low-Resource Languages](https://arxiv.org/pdf/2112.09866v1.pdf) paper
## Training and evaluation data
A new dataset for the low-resource language as Vietnamese to evaluate MRC models. This dataset comprises over 23,000 human-generated question-answer pairs based on 5,109 passages of 174 Vietnamese articles from Wikipedia. However in processing, I eliminated more than 3000 questions with no answers.
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
- **EM**: 52.38
- **F1-SCORE**: 77.67
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
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