---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: xlm-roberta-base-finetuned-pos
  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-pos

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: 0.0683
- Precision: 0.9800
- Recall: 0.9819
- F1: 0.9809
- Accuracy: 0.9822

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1542        | 1.0   | 1583 | 0.1251          | 0.9526    | 0.9613 | 0.9569 | 0.9622   |
| 0.0953        | 2.0   | 3166 | 0.0813          | 0.9725    | 0.9750 | 0.9737 | 0.9763   |
| 0.0694        | 3.0   | 4749 | 0.0707          | 0.9765    | 0.9792 | 0.9778 | 0.9797   |
| 0.0497        | 4.0   | 6332 | 0.0684          | 0.9784    | 0.9809 | 0.9796 | 0.9814   |
| 0.0435        | 5.0   | 7915 | 0.0683          | 0.9800    | 0.9819 | 0.9809 | 0.9822   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3