---
license: apache-2.0
base_model: albert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: albert-base-v2-Malicious_URLs
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# albert-base-v2-Malicious_URLs

This model is a fine-tuned version of [albert-base-v2](https://huggingface.co./albert-base-v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8368
- Accuracy: 0.7267
- Weighted f1: 0.6482
- Micro f1: 0.7267
- Macro f1: 0.4521
- Weighted recall: 0.7267
- Micro recall: 0.7267
- Macro recall: 0.4294
- Weighted precision: 0.6262
- Micro precision: 0.7267
- Macro precision: 0.5508

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Weighted f1 | Micro f1 | Macro f1 | Weighted recall | Micro recall | Macro recall | Weighted precision | Micro precision | Macro precision |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
| 0.7839        | 1.0   | 51087 | 0.8368          | 0.7267   | 0.6482      | 0.7267   | 0.4521   | 0.7267          | 0.7267       | 0.4294       | 0.6262             | 0.7267          | 0.5508          |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3