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

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: 1.2667
- Accuracy: 0.69
- F1: 0.6959

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.9608        | 1.0   | 86   | 0.7778          | 0.63     | 0.5729 |
| 0.6733        | 2.0   | 172  | 0.7087          | 0.68     | 0.6835 |
| 0.4889        | 3.0   | 258  | 0.7707          | 0.7      | 0.7028 |
| 0.3672        | 4.0   | 344  | 0.7906          | 0.69     | 0.7021 |
| 0.2388        | 5.0   | 430  | 1.0683          | 0.7      | 0.6979 |
| 0.1691        | 6.0   | 516  | 1.1391          | 0.69     | 0.7010 |
| 0.1323        | 7.0   | 602  | 1.2486          | 0.71     | 0.7176 |
| 0.1033        | 8.0   | 688  | 1.2667          | 0.69     | 0.6959 |


### Framework versions

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