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---
language:
- vi
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-large_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-large_baseline_syllables
This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the covid19_ner dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0838
- Patient Id: 0.9883
- Name: 0.9409
- Gender: 0.9712
- Age: 0.9767
- Job: 0.8506
- Location: 0.9670
- Organization: 0.9134
- Date: 0.9860
- Symptom And Disease: 0.8820
- Transportation: 0.9773
- F1 Macro: 0.9453
- F1 Micro: 0.9587
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:------:|:------:|:------:|:--------:|:------------:|:------:|:-------------------:|:--------------:|:--------:|:--------:|
| 0.1707 | 1.0 | 629 | 0.1042 | 0.9528 | 0.9227 | 0.8406 | 0.9523 | 0.5899 | 0.9308 | 0.8045 | 0.9874 | 0.8248 | 0.96 | 0.8766 | 0.9140 |
| 0.0475 | 2.0 | 1258 | 0.0811 | 0.9841 | 0.9372 | 0.9591 | 0.9876 | 0.6849 | 0.9350 | 0.8817 | 0.9847 | 0.8584 | 0.9831 | 0.9196 | 0.9390 |
| 0.0312 | 3.0 | 1887 | 0.0744 | 0.9856 | 0.9297 | 0.9691 | 0.9875 | 0.7554 | 0.9578 | 0.8826 | 0.9869 | 0.8648 | 0.9659 | 0.9285 | 0.9498 |
| 0.0196 | 4.0 | 2516 | 0.0808 | 0.9883 | 0.9465 | 0.9644 | 0.9835 | 0.8346 | 0.9635 | 0.9136 | 0.9856 | 0.8730 | 0.9886 | 0.9442 | 0.9565 |
| 0.0119 | 5.0 | 3145 | 0.0838 | 0.9883 | 0.9409 | 0.9712 | 0.9767 | 0.8506 | 0.9670 | 0.9134 | 0.9860 | 0.8820 | 0.9773 | 0.9453 | 0.9587 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
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