---
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_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. -->

# bert-base-multilingual-cased_baseline_syllables

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: 0.1003
- Patient Id: 0.9860
- Name: 0.9239
- Gender: 0.9642
- Age: 0.9834
- Job: 0.7734
- Location: 0.9494
- Organization: 0.8827
- Date: 0.9883
- Symptom And Disease: 0.8631
- Transportation: 0.9773
- F1 Macro: 0.9292
- F1 Micro: 0.9463

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:------:|:------:|:------:|:--------:|:------------:|:------:|:-------------------:|:--------------:|:--------:|:--------:|
| 0.1923        | 1.0   | 629  | 0.1099          | 0.9735     | 0.9049 | 0.9288 | 0.9247 | 0.5296 | 0.9225   | 0.7969       | 0.9861 | 0.7873              | 0.9189         | 0.8673   | 0.9102   |
| 0.0555        | 2.0   | 1258 | 0.0937          | 0.9804     | 0.9144 | 0.9586 | 0.9847 | 0.4700 | 0.9390   | 0.8694       | 0.9856 | 0.8604              | 0.9180         | 0.8881   | 0.9353   |
| 0.0334        | 3.0   | 1887 | 0.0875          | 0.9772     | 0.9153 | 0.9590 | 0.9806 | 0.7568 | 0.9450   | 0.8676       | 0.9883 | 0.8571              | 0.96           | 0.9207   | 0.9402   |
| 0.0207        | 4.0   | 2516 | 0.0972          | 0.9859     | 0.9284 | 0.9590 | 0.9808 | 0.7742 | 0.9507   | 0.8919       | 0.9869 | 0.8616              | 0.9718         | 0.9291   | 0.9468   |
| 0.014         | 5.0   | 3145 | 0.1003          | 0.9860     | 0.9239 | 0.9642 | 0.9834 | 0.7734 | 0.9494   | 0.8827       | 0.9883 | 0.8631              | 0.9773         | 0.9292   | 0.9463   |


### Framework versions

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