---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: xlm-roberta-base-Final_VietNam-aug_delete
  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-Final_VietNam-aug_delete

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: 1.9977
- Accuracy: 0.71
- F1: 0.7211

## 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: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.4259        | 1.0   | 87   | 1.2266          | 0.72     | 0.7286 |
| 0.2928        | 2.0   | 174  | 1.2963          | 0.7      | 0.7078 |
| 0.2487        | 3.0   | 261  | 1.7082          | 0.7      | 0.7102 |
| 0.1831        | 4.0   | 348  | 1.9729          | 0.68     | 0.6943 |
| 0.1636        | 5.0   | 435  | 1.9036          | 0.69     | 0.7030 |
| 0.1244        | 6.0   | 522  | 1.9171          | 0.7      | 0.7119 |
| 0.0924        | 7.0   | 609  | 1.9842          | 0.7      | 0.7119 |
| 0.0791        | 8.0   | 696  | 1.9977          | 0.71     | 0.7211 |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.0
- Datasets 2.14.4
- Tokenizers 0.13.3