---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: XMLRoberta_Dataset8kMeta
  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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/phunganhsang123/huggingface/runs/idvfzc2q)
# XMLRoberta_Dataset8kMeta

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: 0.3777
- Accuracy: 0.9464
- F1: 0.9465

## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.6260  | 200  | 0.2882          | 0.9243   | 0.9108 |
| 0.4946        | 3.2520  | 400  | 0.2445          | 0.9166   | 0.9073 |
| 0.1849        | 4.8780  | 600  | 0.2282          | 0.9447   | 0.9453 |
| 0.1256        | 6.5041  | 800  | 0.2781          | 0.9472   | 0.9459 |
| 0.0808        | 8.1301  | 1000 | 0.2434          | 0.9404   | 0.9422 |
| 0.0808        | 9.7561  | 1200 | 0.3441          | 0.9438   | 0.9436 |
| 0.0592        | 11.3821 | 1400 | 0.3017          | 0.9506   | 0.9499 |
| 0.0418        | 13.0081 | 1600 | 0.3410          | 0.9455   | 0.9446 |
| 0.0345        | 14.6341 | 1800 | 0.3515          | 0.9430   | 0.9434 |
| 0.0233        | 16.2602 | 2000 | 0.3690          | 0.9455   | 0.9458 |
| 0.0233        | 17.8862 | 2200 | 0.3746          | 0.9481   | 0.9480 |
| 0.0176        | 19.5122 | 2400 | 0.3777          | 0.9464   | 0.9465 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1