roberta-base-finetuned-sms-spam-detection Open-source Model - Accurately Detect Whether an SMS is Spam

Roberta Base Finetuned Sms Spam Detection

Developed by mariagrandury

A text classification model fine-tuned on SMS spam datasets based on the roberta-base model, used to detect whether a message is spam.

Downloads 171

Release Time : 3/2/2022

Model Overview

This model is a fine-tuned version of roberta-base on SMS spam datasets, primarily used for text classification tasks, especially spam SMS detection.

High Accuracy

Achieved an accuracy of 0.998 on the evaluation set, demonstrating excellent performance.

Based on RoBERTa

Fine-tuned on the powerful roberta-base model, inheriting its excellent text comprehension capabilities.

Lightweight Fine-tuning

Only requires 2 training epochs to achieve high performance, with efficient training.

Text Classification

Spam SMS Detection

Communication Security

Spam SMS Filtering

Used in mobile SMS applications or communication systems to automatically filter spam messages.

Accurately identifies 99.8% of spam messages

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.0363	1.0	250	0.0156	0.996
0.0147	2.0	500	0.0133	0.998

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