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---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: xlm-roberta-base-VietNam-aug_insert_vi
results: []
---
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# xlm-roberta-base-VietNam-aug_insert_vi
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5745
- Accuracy: 0.82
- F1: 0.8230
## 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: 16
- eval_batch_size: 16
- 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 | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.8686 | 1.0 | 78 | 0.5869 | 0.78 | 0.7395 |
| 0.596 | 2.0 | 156 | 0.5811 | 0.78 | 0.7521 |
| 0.4227 | 3.0 | 234 | 0.5060 | 0.83 | 0.8332 |
| 0.3102 | 4.0 | 312 | 0.6035 | 0.83 | 0.8293 |
| 0.2586 | 5.0 | 390 | 0.5745 | 0.82 | 0.8230 |
### Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3