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---
language:
- vi
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
model-index:
- name: phobert-base-v2_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-base-v2_baseline_words
This model is a fine-tuned version of [vinai/phobert-base-v2](https://huggingface.co/vinai/phobert-base-v2) on the covid19_ner dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0874
- Patient Id: 0.9824
- Name: 0.9415
- Gender: 0.9647
- Age: 0.9502
- Job: 0.8000
- Location: 0.9509
- Organization: 0.9148
- Date: 0.9860
- Symptom And Disease: 0.8863
- Transportation: 1.0
- F1 Macro: 0.9377
- F1 Micro: 0.9503
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:------:|:------:|:------:|:--------:|:------------:|:------:|:-------------------:|:--------------:|:--------:|:--------:|
| 0.4337 | 1.0 | 629 | 0.1664 | 0.9739 | 0.9446 | 0.7794 | 0.9010 | 0.0 | 0.9341 | 0.8413 | 0.9851 | 0.8585 | 0.9885 | 0.8206 | 0.9172 |
| 0.1019 | 2.0 | 1258 | 0.1071 | 0.9770 | 0.9340 | 0.9640 | 0.9644 | 0.5412 | 0.9460 | 0.8823 | 0.9865 | 0.8771 | 1.0 | 0.9072 | 0.9402 |
| 0.0639 | 3.0 | 1887 | 0.0952 | 0.9797 | 0.928 | 0.9647 | 0.9682 | 0.5799 | 0.9488 | 0.9094 | 0.9847 | 0.8814 | 1.0 | 0.9145 | 0.9445 |
| 0.0454 | 4.0 | 2516 | 0.0873 | 0.9820 | 0.9365 | 0.9663 | 0.9632 | 0.7734 | 0.9537 | 0.9075 | 0.9851 | 0.8832 | 1.0 | 0.9351 | 0.9503 |
| 0.0365 | 5.0 | 3145 | 0.0874 | 0.9824 | 0.9415 | 0.9647 | 0.9502 | 0.8000 | 0.9509 | 0.9148 | 0.9860 | 0.8863 | 1.0 | 0.9377 | 0.9503 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
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