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

# phobert-base_baseline_syllables

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: 0.0881
- Patient Id: 0.9817
- Name: 0.9476
- Gender: 0.9385
- Age: 0.9684
- Job: 0.7463
- Location: 0.9427
- Organization: 0.8958
- Date: 0.9883
- Symptom And Disease: 0.8849
- Transportation: 0.9943
- F1 Macro: 0.9288
- F1 Micro: 0.9448

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:------:|:------:|:------:|:--------:|:------------:|:------:|:-------------------:|:--------------:|:--------:|:--------:|
| 0.3091        | 1.0   | 629  | 0.1389          | 0.9660     | 0.9316 | 0.8391 | 0.9008 | 0.0    | 0.9237   | 0.8249       | 0.9865 | 0.8435              | 0.9444         | 0.8160   | 0.9115   |
| 0.0807        | 2.0   | 1258 | 0.0955          | 0.9809     | 0.9178 | 0.9481 | 0.9707 | 0.4646 | 0.9390   | 0.8704       | 0.9883 | 0.8628              | 0.9831         | 0.8926   | 0.9358   |
| 0.0491        | 3.0   | 1887 | 0.0898          | 0.9828     | 0.9418 | 0.9401 | 0.9671 | 0.6824 | 0.9457   | 0.9007       | 0.9856 | 0.8715              | 0.9886         | 0.9206   | 0.9436   |
| 0.0375        | 4.0   | 2516 | 0.0886          | 0.9817     | 0.9452 | 0.9354 | 0.9644 | 0.7509 | 0.9406   | 0.8887       | 0.9869 | 0.8805              | 0.9943         | 0.9269   | 0.9425   |
| 0.0282        | 5.0   | 3145 | 0.0881          | 0.9817     | 0.9476 | 0.9385 | 0.9684 | 0.7463 | 0.9427   | 0.8958       | 0.9883 | 0.8849              | 0.9943         | 0.9288   | 0.9448   |


### Framework versions

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