---
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