---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: xlm-roberta-base-VietNam-aug_insert_vi
  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. -->

# xlm-roberta-base-VietNam-aug_insert_vi

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5745
- Accuracy: 0.82
- F1: 0.8230

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.8686        | 1.0   | 78   | 0.5869          | 0.78     | 0.7395 |
| 0.596         | 2.0   | 156  | 0.5811          | 0.78     | 0.7521 |
| 0.4227        | 3.0   | 234  | 0.5060          | 0.83     | 0.8332 |
| 0.3102        | 4.0   | 312  | 0.6035          | 0.83     | 0.8293 |
| 0.2586        | 5.0   | 390  | 0.5745          | 0.82     | 0.8230 |


### Framework versions

- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3