---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: xlm_70k_co_vn
  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_70k_co_vn

This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1934
- Accuracy: 0.9679
- F1: 0.9680

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 0.2054        | 1.0   | 1719  | 0.1449          | 0.9595   | 0.9599 |
| 0.1226        | 2.0   | 3438  | 0.1261          | 0.9638   | 0.9641 |
| 0.1038        | 3.0   | 5157  | 0.1055          | 0.9682   | 0.9684 |
| 0.0856        | 4.0   | 6876  | 0.1107          | 0.9676   | 0.9678 |
| 0.0732        | 5.0   | 8595  | 0.1240          | 0.9680   | 0.9680 |
| 0.0595        | 6.0   | 10314 | 0.1457          | 0.9679   | 0.9679 |
| 0.0494        | 7.0   | 12033 | 0.1931          | 0.9667   | 0.9668 |
| 0.0425        | 8.0   | 13752 | 0.1772          | 0.9672   | 0.9674 |
| 0.0375        | 9.0   | 15471 | 0.1867          | 0.9683   | 0.9684 |
| 0.034         | 10.0  | 17190 | 0.1934          | 0.9679   | 0.9680 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1