---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
base_model: xlm-roberta-base
model-index:
- name: fedcsis-intent_baseline-xlm_r-pl
  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. -->

# fedcsis-intent_baseline-xlm_r-pl

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the
[leyzer-fedcsis](https://huggingface.co/cartesinus/leyzer-fedcsis) dataset.
Results on test set:
- Accuracy: **0.959451**

It achieves the following results on the evaluation set:
- Loss: **0.1602**
- Accuracy: **0.9671**

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 3.4745        | 1.0   | 798  | 1.5821          | 0.6795   | 0.6795 |
| 1.1438        | 2.0   | 1596 | 0.8333          | 0.8259   | 0.8259 |
| 0.7546        | 3.0   | 2394 | 0.4991          | 0.9039   | 0.9039 |
| 0.3955        | 4.0   | 3192 | 0.3466          | 0.9302   | 0.9302 |
| 0.3016        | 5.0   | 3990 | 0.2571          | 0.9440   | 0.9440 |
| 0.183         | 6.0   | 4788 | 0.2147          | 0.9588   | 0.9588 |
| 0.1309        | 7.0   | 5586 | 0.1900          | 0.9605   | 0.9605 |
| 0.1128        | 8.0   | 6384 | 0.1750          | 0.9640   | 0.9640 |
| 0.0873        | 9.0   | 7182 | 0.1638          | 0.9663   | 0.9663 |
| 0.082         | 10.0  | 7980 | 0.1602          | 0.9671   | 0.9671 |


### Framework versions

- Transformers 4.27.0
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2

## Citation

If you use this model, please cite the following:
```
@inproceedings{kubis2023caiccaic,
	author={Marek Kubis and Paweł Skórzewski and Marcin Sowański and Tomasz Ziętkiewicz},
	pages={1319–1324},
	title={Center for Artificial Intelligence Challenge on Conversational AI Correctness},
	booktitle={Proceedings of the 18th Conference on Computer Science and Intelligence Systems},
	year={2023},
	doi={10.15439/2023B6058},
	url={http://dx.doi.org/10.15439/2023B6058},
	volume={35},
	series={Annals of Computer Science and Information Systems}
}

```