---
license: apache-2.0
base_model: DunnBC22/distilbert-base-uncased-SpamFilter-LG
tags:
- generated_from_trainer
model-index:
- name: bert_spam_detection
  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. -->

# bert_spam_detection

This model is a fine-tuned version of [DunnBC22/distilbert-base-uncased-SpamFilter-LG](https://huggingface.co/DunnBC22/distilbert-base-uncased-SpamFilter-LG) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1079
- Roc Auc: 0.9951

## 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: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Roc Auc |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0113        | 1.0   | 814  | 0.0974          | 0.9948  |
| 0.0009        | 2.0   | 1628 | 0.1079          | 0.9951  |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1