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---
language:
- vi
base_model: vinai/phobert-base
tags:
- generated_from_trainer
model-index:
- name: phobert-base_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_baseline_words
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: 0.0829
- Patient Id: 0.9848
- Name: 0.9421
- Gender: 0.9570
- Age: 0.9766
- Job: 0.8095
- Location: 0.9448
- Organization: 0.9078
- Date: 0.9869
- Symptom And Disease: 0.8923
- Transportation: 0.9943
- F1 Macro: 0.9396
- F1 Micro: 0.9498
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:------:|:------:|:------:|:--------:|:------------:|:------:|:-------------------:|:--------------:|:--------:|:--------:|
| 0.2964 | 1.0 | 629 | 0.1215 | 0.9689 | 0.9534 | 0.9107 | 0.8987 | 0.5357 | 0.9350 | 0.8368 | 0.9856 | 0.8584 | 0.9667 | 0.8850 | 0.9251 |
| 0.068 | 2.0 | 1258 | 0.0890 | 0.9844 | 0.9479 | 0.9487 | 0.9723 | 0.6167 | 0.9377 | 0.8815 | 0.9860 | 0.8835 | 0.9886 | 0.9147 | 0.9409 |
| 0.0441 | 3.0 | 1887 | 0.0847 | 0.9828 | 0.9446 | 0.9554 | 0.9737 | 0.7570 | 0.9445 | 0.9062 | 0.9874 | 0.8909 | 0.9943 | 0.9337 | 0.9482 |
| 0.0327 | 4.0 | 2516 | 0.0859 | 0.9859 | 0.9449 | 0.9570 | 0.9765 | 0.7778 | 0.9451 | 0.9062 | 0.9874 | 0.8914 | 0.9943 | 0.9366 | 0.9495 |
| 0.0259 | 5.0 | 3145 | 0.0829 | 0.9848 | 0.9421 | 0.9570 | 0.9766 | 0.8095 | 0.9448 | 0.9078 | 0.9869 | 0.8923 | 0.9943 | 0.9396 | 0.9498 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
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