pytorch tensorboard xlm-roberta question-answering dataset:squad_v2 transformers generated_from_trainer license:mit model-index autotrain_compatible
---
license: mit
tags:
- generated_from_trainer
datasets:
- squad_v2
model-index:
- name: xlmRoberta-for-VietnameseQA
  results: []
---

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# xlmRoberta-for-VietnameseQA

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the UIT-Viquad_v2 dataset. 
It achieves the following results on the evaluation set:
- Loss: 0.8315

## Model description

Fine-tuned by Honganh Nguyen (FPTU AI Club).

## Intended uses & limitations

More information needed

## Training and evaluation data

Credits to Viet Nguyen (FPTU AI Club) for the training and evaluation data.

Training data: https://github.com/vietnguyen012/QA_viuit/blob/main/train.json

Evaluation data: https://github.com/vietnguyen012/QA_viuit/blob/main/trial/trial.json

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 12
- eval_batch_size: 12
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.5701        | 1.0   | 2534 | 1.2220          |
| 1.2942        | 2.0   | 5068 | 0.9698          |
| 1.0693        | 3.0   | 7602 | 0.8315          |


### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.0+cu111
- Datasets 1.17.0
- Tokenizers 0.10.3
