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

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: 0.0850
- Patient Id: 0.9840
- Name: 0.7711
- Gender: 0.9767
- Age: 0.9821
- Job: 0.8062
- Location: 0.9570
- Organization: 0.8784
- Date: 0.9869
- Symptom And Disease: 0.8688
- Transportation: 1.0
- F1 Macro: 0.9211
- F1 Micro: 0.9459

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:------:|:------:|:------:|:--------:|:------------:|:------:|:-------------------:|:--------------:|:--------:|:--------:|
| 0.2002        | 1.0   | 629  | 0.1212          | 0.9160     | 0.8349 | 0.8346 | 0.8122 | 0.5385 | 0.8769   | 0.7201       | 0.9553 | 0.7769              | 0.8587         | 0.8124   | 0.8586   |
| 0.0557        | 2.0   | 1258 | 0.1025          | 0.9594     | 0.8836 | 0.9533 | 0.9731 | 0.2841 | 0.9228   | 0.8301       | 0.9842 | 0.8545              | 0.9444         | 0.8590   | 0.9191   |
| 0.038         | 3.0   | 1887 | 0.0804          | 0.9741     | 0.7154 | 0.9732 | 0.9821 | 0.7615 | 0.9372   | 0.8576       | 0.9869 | 0.8461              | 0.9943         | 0.9028   | 0.9309   |
| 0.0222        | 4.0   | 2516 | 0.0862          | 0.9871     | 0.5567 | 0.9691 | 0.9862 | 0.8207 | 0.9553   | 0.8707       | 0.9847 | 0.8740              | 1.0            | 0.9005   | 0.9398   |
| 0.0148        | 5.0   | 3145 | 0.0850          | 0.9840     | 0.7711 | 0.9767 | 0.9821 | 0.8062 | 0.9570   | 0.8784       | 0.9869 | 0.8688              | 1.0            | 0.9211   | 0.9459   |


### Framework versions

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