---
language:
- vi
base_model: vinai/phobert-large
tags:
- generated_from_trainer
model-index:
- name: phobert-large_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-large_baseline_syllables

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: 0.0933
- Patient Id: 0.9859
- Name: 0.9437
- Gender: 0.9624
- Age: 0.9656
- Job: 0.7954
- Location: 0.9517
- Organization: 0.9037
- Date: 0.9874
- Symptom And Disease: 0.8808
- Transportation: 0.9886
- F1 Macro: 0.9365
- F1 Micro: 0.9505

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:------:|:------:|:------:|:--------:|:------------:|:------:|:-------------------:|:--------------:|:--------:|:--------:|
| 0.2696        | 1.0   | 629  | 0.1036          | 0.9758     | 0.9365 | 0.8730 | 0.8965 | 0.6113 | 0.9386   | 0.8447       | 0.9870 | 0.8494              | 0.9721         | 0.8885   | 0.9247   |
| 0.0518        | 2.0   | 1258 | 0.0801          | 0.9851     | 0.9491 | 0.9540 | 0.9709 | 0.6063 | 0.9393   | 0.8843       | 0.9887 | 0.8856              | 0.9503         | 0.9114   | 0.9416   |
| 0.0301        | 3.0   | 1887 | 0.0856          | 0.9867     | 0.9437 | 0.9524 | 0.9669 | 0.7812 | 0.9496   | 0.8909       | 0.9878 | 0.8740              | 0.9831         | 0.9316   | 0.9475   |
| 0.0213        | 4.0   | 2516 | 0.0923          | 0.9855     | 0.9465 | 0.9626 | 0.9605 | 0.7907 | 0.9495   | 0.8948       | 0.9874 | 0.8815              | 0.9775         | 0.9337   | 0.9486   |
| 0.0146        | 5.0   | 3145 | 0.0933          | 0.9859     | 0.9437 | 0.9624 | 0.9656 | 0.7954 | 0.9517   | 0.9037       | 0.9874 | 0.8808              | 0.9886         | 0.9365   | 0.9505   |


### Framework versions

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