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---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: xlm-roberta-base-Final_VietNam-aug_replace_synonym-1
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-Final_VietNam-aug_replace_synonym-1
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: 1.0663
- Accuracy: 0.69
- F1: 0.6982
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.0809 | 1.0 | 86 | 1.0198 | 0.5 | 0.4206 |
| 0.7967 | 2.0 | 172 | 0.7866 | 0.62 | 0.6178 |
| 0.5958 | 3.0 | 258 | 0.7556 | 0.7 | 0.6975 |
| 0.4574 | 4.0 | 344 | 0.8233 | 0.66 | 0.6653 |
| 0.3242 | 5.0 | 430 | 0.8224 | 0.7 | 0.7039 |
| 0.2399 | 6.0 | 516 | 0.9593 | 0.7 | 0.7099 |
| 0.1898 | 7.0 | 602 | 1.0689 | 0.7 | 0.7097 |
| 0.1665 | 8.0 | 688 | 1.0663 | 0.69 | 0.6982 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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