---
library_name: transformers
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-peyma-fa
  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-finetuned-peyma-fa

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: 0.0848
- F1: 0.9170

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.1488        | 1.0   | 998  | 0.0672          | 0.8665 |
| 0.061         | 2.0   | 1996 | 0.0650          | 0.8881 |
| 0.041         | 3.0   | 2994 | 0.0640          | 0.8954 |
| 0.0274        | 4.0   | 3992 | 0.0728          | 0.8898 |
| 0.0207        | 5.0   | 4990 | 0.0723          | 0.8935 |
| 0.0148        | 6.0   | 5988 | 0.0745          | 0.9006 |
| 0.0084        | 7.0   | 6986 | 0.0825          | 0.9088 |
| 0.0056        | 8.0   | 7984 | 0.0824          | 0.9151 |
| 0.0033        | 9.0   | 8982 | 0.0836          | 0.9143 |
| 0.0021        | 10.0  | 9980 | 0.0848          | 0.9170 |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0