---
language:
- vi
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
model-index:
- name: phobert-base-v2_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-v2_baseline_words

This model is a fine-tuned version of [vinai/phobert-base-v2](https://huggingface.co/vinai/phobert-base-v2) on the covid19_ner dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0874
- Patient Id: 0.9824
- Name: 0.9415
- Gender: 0.9647
- Age: 0.9502
- Job: 0.8000
- Location: 0.9509
- Organization: 0.9148
- Date: 0.9860
- Symptom And Disease: 0.8863
- Transportation: 1.0
- F1 Macro: 0.9377
- F1 Micro: 0.9503

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:------:|:------:|:------:|:--------:|:------------:|:------:|:-------------------:|:--------------:|:--------:|:--------:|
| 0.4337        | 1.0   | 629  | 0.1664          | 0.9739     | 0.9446 | 0.7794 | 0.9010 | 0.0    | 0.9341   | 0.8413       | 0.9851 | 0.8585              | 0.9885         | 0.8206   | 0.9172   |
| 0.1019        | 2.0   | 1258 | 0.1071          | 0.9770     | 0.9340 | 0.9640 | 0.9644 | 0.5412 | 0.9460   | 0.8823       | 0.9865 | 0.8771              | 1.0            | 0.9072   | 0.9402   |
| 0.0639        | 3.0   | 1887 | 0.0952          | 0.9797     | 0.928  | 0.9647 | 0.9682 | 0.5799 | 0.9488   | 0.9094       | 0.9847 | 0.8814              | 1.0            | 0.9145   | 0.9445   |
| 0.0454        | 4.0   | 2516 | 0.0873          | 0.9820     | 0.9365 | 0.9663 | 0.9632 | 0.7734 | 0.9537   | 0.9075       | 0.9851 | 0.8832              | 1.0            | 0.9351   | 0.9503   |
| 0.0365        | 5.0   | 3145 | 0.0874          | 0.9824     | 0.9415 | 0.9647 | 0.9502 | 0.8000 | 0.9509   | 0.9148       | 0.9860 | 0.8863              | 1.0            | 0.9377   | 0.9503   |


### Framework versions

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