---
language:
- vi
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-base_covid_ner_full
  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_covid_ner_full

This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the covid19_ner dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0873
- Patient Id: 0.9883
- Name: 0.9446
- Gender: 0.9785
- Age: 0.9765
- Job: 0.7063
- Location: 0.9538
- Organization: 0.8807
- Date: 0.9851
- Symptom And Disease: 0.8886
- Transportation: 1.0
- F1 Macro: 0.9302
- F1 Micro: 0.9499

## 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: 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Patient Id | Name   | Gender | Age    | Job    | Location | Organization | Date   | Symptom And Disease | Transportation | F1 Macro | F1 Micro |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:------:|:------:|:------:|:--------:|:------------:|:------:|:-------------------:|:--------------:|:--------:|:--------:|
| 0.2425        | 1.0   | 629  | 0.0989          | 0.9661     | 0.8889 | 0.8030 | 0.9068 | 0.3358 | 0.9152   | 0.8045       | 0.9843 | 0.8291              | 0.9222         | 0.8356   | 0.9001   |
| 0.0596        | 2.0   | 1258 | 0.0885          | 0.9807     | 0.9446 | 0.9283 | 0.9620 | 0.4786 | 0.9462   | 0.8665       | 0.9810 | 0.8690              | 0.9885         | 0.8945   | 0.9367   |
| 0.0376        | 3.0   | 1887 | 0.0899          | 0.9828     | 0.9284 | 0.9483 | 0.9765 | 0.6406 | 0.9458   | 0.8720       | 0.9865 | 0.8783              | 1.0            | 0.9159   | 0.9423   |
| 0.0257        | 4.0   | 2516 | 0.0919          | 0.9875     | 0.9362 | 0.9766 | 0.9805 | 0.6818 | 0.9505   | 0.8827       | 0.9869 | 0.8871              | 1.0            | 0.9270   | 0.9484   |
| 0.0172        | 5.0   | 3145 | 0.0873          | 0.9883     | 0.9446 | 0.9785 | 0.9765 | 0.7063 | 0.9538   | 0.8807       | 0.9851 | 0.8886              | 1.0            | 0.9302   | 0.9499   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1