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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_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. -->
# xlm-roberta-base_baseline_words
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: 0.0873
- Patient Id: 0.9883
- Name: 0.9446
- Gender: 0.9785
- Age: 0.9765
- Job: 0.7063
- Location: 0.9538
- Organization: 0.8807
- Date: 0.9851
- Symptom And Disease: 0.8886
- Transportation: 1.0
- F1 Macro: 0.9302
- F1 Micro: 0.9499
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:------:|:------:|:------:|:--------:|:------------:|:------:|:-------------------:|:--------------:|:--------:|:--------:|
| 0.2425 | 1.0 | 629 | 0.0989 | 0.9661 | 0.8889 | 0.8030 | 0.9068 | 0.3358 | 0.9152 | 0.8045 | 0.9843 | 0.8291 | 0.9222 | 0.8356 | 0.9001 |
| 0.0596 | 2.0 | 1258 | 0.0885 | 0.9807 | 0.9446 | 0.9283 | 0.9620 | 0.4786 | 0.9462 | 0.8665 | 0.9810 | 0.8690 | 0.9885 | 0.8945 | 0.9367 |
| 0.0376 | 3.0 | 1887 | 0.0899 | 0.9828 | 0.9284 | 0.9483 | 0.9765 | 0.6406 | 0.9458 | 0.8720 | 0.9865 | 0.8783 | 1.0 | 0.9159 | 0.9423 |
| 0.0257 | 4.0 | 2516 | 0.0919 | 0.9875 | 0.9362 | 0.9766 | 0.9805 | 0.6818 | 0.9505 | 0.8827 | 0.9869 | 0.8871 | 1.0 | 0.9270 | 0.9484 |
| 0.0172 | 5.0 | 3145 | 0.0873 | 0.9883 | 0.9446 | 0.9785 | 0.9765 | 0.7063 | 0.9538 | 0.8807 | 0.9851 | 0.8886 | 1.0 | 0.9302 | 0.9499 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
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