|
--- |
|
language: |
|
- vi |
|
base_model: vinai/phobert-base-v2 |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: phobert-base-v2_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-base-v2_baseline_syllables |
|
|
|
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: 0.0934 |
|
- Patient Id: 0.9852 |
|
- Name: 0.9337 |
|
- Gender: 0.9489 |
|
- Age: 0.9644 |
|
- Job: 0.7601 |
|
- Location: 0.9449 |
|
- Organization: 0.8970 |
|
- Date: 0.9892 |
|
- Symptom And Disease: 0.8754 |
|
- Transportation: 1.0 |
|
- F1 Macro: 0.9299 |
|
- F1 Micro: 0.9455 |
|
|
|
## 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:------:|:------:|:------:|:--------:|:------------:|:------:|:-------------------:|:--------------:|:--------:|:--------:| |
|
| 0.4655 | 1.0 | 629 | 0.2020 | 0.9690 | 0.9276 | 0.8866 | 0.8962 | 0.0 | 0.9159 | 0.8135 | 0.9860 | 0.8368 | 0.9486 | 0.8180 | 0.9093 | |
|
| 0.1235 | 2.0 | 1258 | 0.1219 | 0.9761 | 0.9125 | 0.9529 | 0.9642 | 0.0 | 0.9419 | 0.8810 | 0.9883 | 0.8545 | 0.9943 | 0.8466 | 0.9336 | |
|
| 0.0713 | 3.0 | 1887 | 0.1015 | 0.9789 | 0.9355 | 0.9541 | 0.9699 | 0.7077 | 0.9428 | 0.8891 | 0.9878 | 0.8667 | 1.0 | 0.9232 | 0.9418 | |
|
| 0.0502 | 4.0 | 2516 | 0.0950 | 0.9824 | 0.9291 | 0.9485 | 0.9657 | 0.7442 | 0.9455 | 0.8899 | 0.9865 | 0.8698 | 1.0 | 0.9262 | 0.9435 | |
|
| 0.0405 | 5.0 | 3145 | 0.0934 | 0.9852 | 0.9337 | 0.9489 | 0.9644 | 0.7601 | 0.9449 | 0.8970 | 0.9892 | 0.8754 | 1.0 | 0.9299 | 0.9455 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.2 |
|
- Pytorch 2.1.2 |
|
- Datasets 2.19.2 |
|
- Tokenizers 0.19.1 |
|
|
