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---
language:
- vi
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-base_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. -->
# xlm-roberta-base_baseline_syllables
This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the covid19_ner dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0807
- Patient Id: 0.9855
- Name: 0.9337
- Gender: 0.9714
- Age: 0.9834
- Job: 0.8092
- Location: 0.9596
- Organization: 0.8897
- Date: 0.9860
- Symptom And Disease: 0.8885
- Transportation: 1.0
- F1 Macro: 0.9407
- F1 Micro: 0.9541
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:------:|:------:|:------:|:--------:|:------------:|:------:|:-------------------:|:--------------:|:--------:|:--------:|
| 0.216 | 1.0 | 629 | 0.0912 | 0.9477 | 0.9143 | 0.8367 | 0.9237 | 0.6228 | 0.9426 | 0.8234 | 0.9811 | 0.8603 | 0.9827 | 0.8835 | 0.9202 |
| 0.0478 | 2.0 | 1258 | 0.0832 | 0.9860 | 0.8942 | 0.9414 | 0.9741 | 0.5368 | 0.9434 | 0.8584 | 0.9811 | 0.8722 | 0.9829 | 0.8970 | 0.9369 |
| 0.0306 | 3.0 | 1887 | 0.0744 | 0.9867 | 0.9206 | 0.9494 | 0.9780 | 0.7664 | 0.9550 | 0.8913 | 0.9860 | 0.8791 | 0.9829 | 0.9295 | 0.9492 |
| 0.0211 | 4.0 | 2516 | 0.0789 | 0.9863 | 0.9309 | 0.9661 | 0.9793 | 0.7795 | 0.9549 | 0.8859 | 0.9860 | 0.8844 | 1.0 | 0.9353 | 0.9508 |
| 0.0153 | 5.0 | 3145 | 0.0807 | 0.9855 | 0.9337 | 0.9714 | 0.9834 | 0.8092 | 0.9596 | 0.8897 | 0.9860 | 0.8885 | 1.0 | 0.9407 | 0.9541 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
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