---
language:
- vi
base_model: vinai/phobert-base
tags:
- generated_from_trainer
model-index:
- name: phobert-base_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. -->

# phobert-base_baseline_words

This model is a fine-tuned version of [vinai/phobert-base](https://huggingface.co/vinai/phobert-base) on the covid19_ner dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0829
- Patient Id: 0.9848
- Name: 0.9421
- Gender: 0.9570
- Age: 0.9766
- Job: 0.8095
- Location: 0.9448
- Organization: 0.9078
- Date: 0.9869
- Symptom And Disease: 0.8923
- Transportation: 0.9943
- F1 Macro: 0.9396
- F1 Micro: 0.9498

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:------:|:------:|:------:|:--------:|:------------:|:------:|:-------------------:|:--------------:|:--------:|:--------:|
| 0.2964        | 1.0   | 629  | 0.1215          | 0.9689     | 0.9534 | 0.9107 | 0.8987 | 0.5357 | 0.9350   | 0.8368       | 0.9856 | 0.8584              | 0.9667         | 0.8850   | 0.9251   |
| 0.068         | 2.0   | 1258 | 0.0890          | 0.9844     | 0.9479 | 0.9487 | 0.9723 | 0.6167 | 0.9377   | 0.8815       | 0.9860 | 0.8835              | 0.9886         | 0.9147   | 0.9409   |
| 0.0441        | 3.0   | 1887 | 0.0847          | 0.9828     | 0.9446 | 0.9554 | 0.9737 | 0.7570 | 0.9445   | 0.9062       | 0.9874 | 0.8909              | 0.9943         | 0.9337   | 0.9482   |
| 0.0327        | 4.0   | 2516 | 0.0859          | 0.9859     | 0.9449 | 0.9570 | 0.9765 | 0.7778 | 0.9451   | 0.9062       | 0.9874 | 0.8914              | 0.9943         | 0.9366   | 0.9495   |
| 0.0259        | 5.0   | 3145 | 0.0829          | 0.9848     | 0.9421 | 0.9570 | 0.9766 | 0.8095 | 0.9448   | 0.9078       | 0.9869 | 0.8923              | 0.9943         | 0.9396   | 0.9498   |


### Framework versions

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