---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: xlm-roberta-base-New_VietNam-aug_replace_w2v-1
  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-New_VietNam-aug_replace_w2v-1

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: 1.0760
- Accuracy: 0.73
- F1: 0.7316

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.0605        | 1.0   | 84   | 0.9570          | 0.55     | 0.4830 |
| 0.7614        | 2.0   | 168  | 0.7075          | 0.68     | 0.6682 |
| 0.5718        | 3.0   | 252  | 0.7353          | 0.74     | 0.7413 |
| 0.4409        | 4.0   | 336  | 0.7226          | 0.73     | 0.7346 |
| 0.3768        | 5.0   | 420  | 0.7989          | 0.76     | 0.7612 |
| 0.2887        | 6.0   | 504  | 0.8930          | 0.74     | 0.7424 |
| 0.2218        | 7.0   | 588  | 1.0373          | 0.74     | 0.7429 |
| 0.1798        | 8.0   | 672  | 1.0760          | 0.73     | 0.7316 |


### Framework versions

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