Downloads · 30 days
50
7% of all-time downloads
bert-email-spam-classifier_tuned
SGHOSH1999/bert-email-spam-classifier_tuned
bert-email-spam-classifier_tuned is a machine learning model from SGHOSH1999. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
This repository contains a fine-tuned BERT model for SMS/email spam detection using the SMS Spam Collection Dataset.
All-time downloads
679
Public
Parameters
109M
438 MB on disk
Likes
1
Public
Repo makeup
Click a slice to open those files.
.safetensors438 MB · 100%
At a glance
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- Jun 11, 2025
- Updated
- Jun 11, 2025
- SHA
- 60b6778b
Datasets
Model card
From the Hugging Face model README
BERT Email Spam Classifier
This repository contains a fine-tuned BERT model for SMS/email spam detection using the SMS Spam Collection Dataset.
Accuracy:
Loss: 0.012 Accuracy: 0.98
Model Details
- Architecture: BERT (Bidirectional Encoder Representations from Transformers)
- Task: Binary classification (spam vs. ham)
- Base Model:
bert-base-uncased - Framework: Hugging Face Transformers (PyTorch)
- License: MIT
Usage
Load the model and tokenizer using Hugging Face Transformers:
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("SGHOSH1999/bert-email-spam-classifier_tuned")
model = AutoModelForSequenceClassification.from_pretrained("SGHOSH1999/bert-email-spam-classifier_tuned")
Training Data
- SMS Spam Collection Dataset
- The dataset contains 5,574 SMS messages labeled as 'ham' (legitimate) or 'spam'.
How to Cite
If you use this model, please cite the original dataset and this repository.
License
MIT
- Type
- bert
- License
- mit
- Created
- Jun 11, 2025
- Updated
- Jun 11, 2025