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

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: 0.0807
- Patient Id: 0.9855
- Name: 0.9337
- Gender: 0.9714
- Age: 0.9834
- Job: 0.8092
- Location: 0.9596
- Organization: 0.8897
- Date: 0.9860
- Symptom And Disease: 0.8885
- Transportation: 1.0
- F1 Macro: 0.9407
- F1 Micro: 0.9541

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:------:|:------:|:------:|:--------:|:------------:|:------:|:-------------------:|:--------------:|:--------:|:--------:|
| 0.216         | 1.0   | 629  | 0.0912          | 0.9477     | 0.9143 | 0.8367 | 0.9237 | 0.6228 | 0.9426   | 0.8234       | 0.9811 | 0.8603              | 0.9827         | 0.8835   | 0.9202   |
| 0.0478        | 2.0   | 1258 | 0.0832          | 0.9860     | 0.8942 | 0.9414 | 0.9741 | 0.5368 | 0.9434   | 0.8584       | 0.9811 | 0.8722              | 0.9829         | 0.8970   | 0.9369   |
| 0.0306        | 3.0   | 1887 | 0.0744          | 0.9867     | 0.9206 | 0.9494 | 0.9780 | 0.7664 | 0.9550   | 0.8913       | 0.9860 | 0.8791              | 0.9829         | 0.9295   | 0.9492   |
| 0.0211        | 4.0   | 2516 | 0.0789          | 0.9863     | 0.9309 | 0.9661 | 0.9793 | 0.7795 | 0.9549   | 0.8859       | 0.9860 | 0.8844              | 1.0            | 0.9353   | 0.9508   |
| 0.0153        | 5.0   | 3145 | 0.0807          | 0.9855     | 0.9337 | 0.9714 | 0.9834 | 0.8092 | 0.9596   | 0.8897       | 0.9860 | 0.8885              | 1.0            | 0.9407   | 0.9541   |


### Framework versions

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