---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: xlm-roberta-base-POS-arabic
  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-POS-arabic

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0822
- F1: 0.9689
- Accuracy: 0.9785

## 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
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|
| 0.5584        | 1.0   | 95   | 0.1231          | 0.9537 | 0.9679   |
| 0.1191        | 2.0   | 190  | 0.0933          | 0.9645 | 0.9755   |
| 0.0901        | 3.0   | 285  | 0.0868          | 0.9667 | 0.9768   |
| 0.0757        | 4.0   | 380  | 0.0851          | 0.9675 | 0.9774   |
| 0.066         | 5.0   | 475  | 0.0822          | 0.9689 | 0.9785   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2