---
language:
- vi
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-large_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-large_baseline_syllables

This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the covid19_ner dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0838
- Patient Id: 0.9883
- Name: 0.9409
- Gender: 0.9712
- Age: 0.9767
- Job: 0.8506
- Location: 0.9670
- Organization: 0.9134
- Date: 0.9860
- Symptom And Disease: 0.8820
- Transportation: 0.9773
- F1 Macro: 0.9453
- F1 Micro: 0.9587

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:------:|:------:|:------:|:--------:|:------------:|:------:|:-------------------:|:--------------:|:--------:|:--------:|
| 0.1707        | 1.0   | 629  | 0.1042          | 0.9528     | 0.9227 | 0.8406 | 0.9523 | 0.5899 | 0.9308   | 0.8045       | 0.9874 | 0.8248              | 0.96           | 0.8766   | 0.9140   |
| 0.0475        | 2.0   | 1258 | 0.0811          | 0.9841     | 0.9372 | 0.9591 | 0.9876 | 0.6849 | 0.9350   | 0.8817       | 0.9847 | 0.8584              | 0.9831         | 0.9196   | 0.9390   |
| 0.0312        | 3.0   | 1887 | 0.0744          | 0.9856     | 0.9297 | 0.9691 | 0.9875 | 0.7554 | 0.9578   | 0.8826       | 0.9869 | 0.8648              | 0.9659         | 0.9285   | 0.9498   |
| 0.0196        | 4.0   | 2516 | 0.0808          | 0.9883     | 0.9465 | 0.9644 | 0.9835 | 0.8346 | 0.9635   | 0.9136       | 0.9856 | 0.8730              | 0.9886         | 0.9442   | 0.9565   |
| 0.0119        | 5.0   | 3145 | 0.0838          | 0.9883     | 0.9409 | 0.9712 | 0.9767 | 0.8506 | 0.9670   | 0.9134       | 0.9860 | 0.8820              | 0.9773         | 0.9453   | 0.9587   |


### Framework versions

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