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---
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
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