transformers pytorch xlm-roberta text-classification generated_from_trainer base_model:FacebookAI/xlm-roberta-base base_model:finetune:FacebookAI/xlm-roberta-base license:mit autotrain_compatible endpoints_compatible region:us
---
base_model: xlm-roberta-base
license: mit
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-base-Final_VietNam-aug_backtranslation-2
  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_backtranslation-2

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: 1.3357
- Accuracy: 0.66
- F1: 0.6673

## 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: 40
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.0185        | 1.0   | 86   | 0.8134          | 0.65     | 0.5550 |
| 0.6948        | 2.0   | 172  | 0.9228          | 0.65     | 0.6376 |
| 0.5272        | 3.0   | 258  | 0.9715          | 0.69     | 0.6920 |
| 0.3985        | 4.0   | 344  | 1.0097          | 0.7      | 0.7042 |
| 0.3273        | 5.0   | 430  | 1.0340          | 0.7      | 0.7067 |
| 0.2035        | 6.0   | 516  | 1.1582          | 0.68     | 0.6870 |
| 0.1705        | 7.0   | 602  | 1.2932          | 0.66     | 0.6673 |
| 0.1303        | 8.0   | 688  | 1.3357          | 0.66     | 0.6673 |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
