---
library_name: transformers
base_model: UBC-NLP/MARBERT
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: phishGuard-AI
  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. -->

# phishGuard-AI

This model is a fine-tuned version of [UBC-NLP/MARBERT](https://huggingface.co/UBC-NLP/MARBERT) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1009
- Accuracy: 0.9821
- F1: 0.9850
- Precision: 0.9911
- Recall: 0.9821

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 4    | 0.3616          | 0.9911   | 0.9896 | 0.9912    | 0.9911 |
| No log        | 2.0   | 8    | 0.2057          | 0.9940   | 0.9940 | 0.9940    | 0.9940 |
| No log        | 3.0   | 12   | 0.1473          | 0.9792   | 0.9829 | 0.9904    | 0.9792 |
| No log        | 4.0   | 16   | 0.1119          | 0.9821   | 0.9850 | 0.9911    | 0.9821 |
| No log        | 5.0   | 20   | 0.1009          | 0.9821   | 0.9850 | 0.9911    | 0.9821 |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2