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---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: xlm-roberta-base-Balance_VietNam-aug_replace_tfidf
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-Balance_VietNam-aug_replace_tfidf
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: 0.8255
- Accuracy: 0.71
- F1: 0.7123
## 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: 8
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.0682 | 1.0 | 87 | 0.8850 | 0.63 | 0.5828 |
| 0.8982 | 2.0 | 174 | 0.8205 | 0.68 | 0.6460 |
| 0.7637 | 3.0 | 261 | 0.7253 | 0.7 | 0.7013 |
| 0.6902 | 4.0 | 348 | 0.6887 | 0.71 | 0.7088 |
| 0.5525 | 5.0 | 435 | 0.6648 | 0.75 | 0.7480 |
| 0.4981 | 6.0 | 522 | 0.7215 | 0.75 | 0.7504 |
| 0.403 | 7.0 | 609 | 0.8010 | 0.72 | 0.7251 |
| 0.3255 | 8.0 | 696 | 0.8255 | 0.71 | 0.7123 |
### Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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