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

# phobert-large_baseline_words

This model is a fine-tuned version of [vinai/phobert-large](https://huggingface.co/vinai/phobert-large) on the covid19_ner dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0943
- Patient Id: 0.9863
- Name: 0.9542
- Gender: 0.9664
- Age: 0.9633
- Job: 0.8300
- Location: 0.9521
- Organization: 0.9188
- Date: 0.9842
- Symptom And Disease: 0.8773
- Transportation: 1.0
- F1 Macro: 0.9433
- F1 Micro: 0.9521

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:------:|:------:|:------:|:--------:|:------------:|:------:|:-------------------:|:--------------:|:--------:|:--------:|
| 0.2801        | 1.0   | 629  | 0.0981          | 0.9840     | 0.9455 | 0.9045 | 0.9010 | 0.5837 | 0.9265   | 0.8726       | 0.9812 | 0.8611              | 0.9831         | 0.8943   | 0.9266   |
| 0.0446        | 2.0   | 1258 | 0.0897          | 0.9863     | 0.9549 | 0.9501 | 0.9722 | 0.7833 | 0.9355   | 0.8907       | 0.9852 | 0.8814              | 0.9721         | 0.9312   | 0.9434   |
| 0.0283        | 3.0   | 1887 | 0.0809          | 0.9867     | 0.9516 | 0.9551 | 0.9695 | 0.7857 | 0.9487   | 0.9086       | 0.9860 | 0.8845              | 1.0            | 0.9376   | 0.9502   |
| 0.0198        | 4.0   | 2516 | 0.0905          | 0.9863     | 0.9542 | 0.9647 | 0.9633 | 0.8287 | 0.9483   | 0.9159       | 0.9842 | 0.8897              | 1.0            | 0.9435   | 0.9516   |
| 0.0134        | 5.0   | 3145 | 0.0943          | 0.9863     | 0.9542 | 0.9664 | 0.9633 | 0.8300 | 0.9521   | 0.9188       | 0.9842 | 0.8773              | 1.0            | 0.9433   | 0.9521   |


### Framework versions

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