FINE-TUNED-VIQUAD-HGF

This model is a fine-tuned version of bhavikardeshna/xlm-roberta-base-vietnamese on the UIT-ViQuAD dataset.

Model description

The model is described in Cascading Adaptors to Leverage English Data to Improve Performance of Question Answering for Low-Resource Languages 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