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---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: cyber_xlm_roberta
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. -->
# cyber_xlm_roberta
This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4037
- Accuracy: 0.8200
- F1: 0.8080
- Precision: 0.8010
- Recall: 0.8236
## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.5504 | 1.0 | 144 | 0.4762 | 0.7637 | 0.7467 | 0.7416 | 0.7580 |
| 0.4198 | 2.0 | 288 | 0.4175 | 0.7945 | 0.7819 | 0.7759 | 0.7987 |
| 0.4121 | 3.0 | 432 | 0.4079 | 0.8148 | 0.8035 | 0.7969 | 0.8215 |
| 0.3715 | 4.0 | 576 | 0.3859 | 0.8221 | 0.8064 | 0.8012 | 0.8138 |
| 0.3464 | 5.0 | 720 | 0.4037 | 0.8200 | 0.8080 | 0.8010 | 0.8236 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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