---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: outputs
  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. -->

# outputs

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: 0.1489
- F1 Micro: 0.8209
- Precision Micro: 0.8209
- Recall Micro: 0.8209

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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 | F1 Micro | Precision Micro | Recall Micro |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------------:|:------------:|
| 0.4507        | 0.7782 | 200  | 0.3227          | 0.0      | 0.0             | 0.0          |
| 0.263         | 1.5564 | 400  | 0.2081          | 0.5201   | 0.8744          | 0.3701       |
| 0.1789        | 2.3346 | 600  | 0.1686          | 0.7489   | 0.8231          | 0.6870       |
| 0.13          | 3.1128 | 800  | 0.1555          | 0.7691   | 0.8074          | 0.7343       |
| 0.1063        | 3.8911 | 1000 | 0.1416          | 0.7974   | 0.7649          | 0.8327       |
| 0.0844        | 4.6693 | 1200 | 0.1492          | 0.8      | 0.8008          | 0.7992       |
| 0.0617        | 5.4475 | 1400 | 0.1449          | 0.8268   | 0.8268          | 0.8268       |
| 0.0534        | 6.2257 | 1600 | 0.1388          | 0.8283   | 0.8258          | 0.8307       |
| 0.0352        | 7.0039 | 1800 | 0.1471          | 0.8272   | 0.8297          | 0.8248       |
| 0.0296        | 7.7821 | 2000 | 0.1489          | 0.8209   | 0.8209          | 0.8209       |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.1.0.post100
- Datasets 2.19.0
- Tokenizers 0.19.1