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