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---
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
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