---
language:
- vi
license: apache-2.0
base_model: google-bert/bert-base-multilingual-cased
tags:
- generated_from_trainer
model-index:
- name: bert-base-multilingual-cased_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. -->

# bert-base-multilingual-cased_baseline_words

This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on the covid19_ner dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0998
- Patient Id: 0.9840
- Name: 0.9182
- Gender: 0.9623
- Age: 0.9725
- Job: 0.7799
- Location: 0.9501
- Organization: 0.8965
- Date: 0.9869
- Symptom And Disease: 0.8626
- Transportation: 0.9885
- F1 Macro: 0.9302
- F1 Micro: 0.9466

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:------:|:------:|:------:|:--------:|:------------:|:------:|:-------------------:|:--------------:|:--------:|:--------:|
| 0.1996        | 1.0   | 629  | 0.1207          | 0.9728     | 0.8997 | 0.8414 | 0.9018 | 0.5020 | 0.9030   | 0.7496       | 0.9847 | 0.8064              | 0.9053         | 0.8467   | 0.8959   |
| 0.0584        | 2.0   | 1258 | 0.0978          | 0.9793     | 0.9101 | 0.9476 | 0.9726 | 0.5044 | 0.9380   | 0.8738       | 0.9860 | 0.8433              | 0.9091         | 0.8864   | 0.9319   |
| 0.0344        | 3.0   | 1887 | 0.0925          | 0.9776     | 0.9125 | 0.9455 | 0.9766 | 0.7216 | 0.9417   | 0.8665       | 0.9865 | 0.8634              | 0.9655         | 0.9157   | 0.9383   |
| 0.0222        | 4.0   | 2516 | 0.0971          | 0.9836     | 0.9178 | 0.9556 | 0.9739 | 0.7442 | 0.9493   | 0.8883       | 0.9865 | 0.8579              | 0.9943         | 0.9251   | 0.9443   |
| 0.0147        | 5.0   | 3145 | 0.0998          | 0.9840     | 0.9182 | 0.9623 | 0.9725 | 0.7799 | 0.9501   | 0.8965       | 0.9869 | 0.8626              | 0.9885         | 0.9302   | 0.9466   |


### Framework versions

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