Open-source check_event_wa text classification model - accurately classify texts, with both accuracy and F1 scores reaching 1.0 on the evaluation set

Check Event Wa

Developed by Venkatesh4342

A text classification model fine-tuned based on distilbert-base-uncased, demonstrating outstanding performance on the evaluation set with both accuracy and F1 score reaching 1.0.

Large Language Model

Transformers

Open Source License:Apache-2.0 #High Accuracy Event Detection #Lightweight BERT #Text Classification Optimization

Downloads 15

Release Time : 6/2/2024

Model Overview

This model is a text classification model primarily used for specific task classification. The exact task and purpose require further clarification.

Model Features

Efficient and Lightweight

Based on the DistilBERT architecture, it reduces model size and computational resource requirements while maintaining performance.

High Accuracy

Achieved perfect accuracy and F1 score of 1.0 on the evaluation set, demonstrating excellent performance.

Fast Training

Only requires 3 training epochs to achieve outstanding performance, with high training efficiency.

Model Capabilities

Text Classification

Natural Language Processing

Use Cases

Text Analysis

Event Detection

Potentially used for detecting specific types of events or content (inferred from the model name)

High accuracy (1.0)

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	1.0	62	0.0095	1.0	1.0
No log	2.0	124	0.0039	1.0	1.0
No log	3.0	186	0.0032	1.0	1.0

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Check Event Wa

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 check_event_wa

🚀 Quick Start

📚 Documentation

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

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📄 License