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mjpsm/
check_in_or_not_v2

Name: check_in_or_not_v2
Availability: InStock

text-embeddings-inference

endpoints_compatible

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Check-in or Not Classifier (v2)

🔍 Overview

The Check-in or Not Classifier is a binary text classification model designed to determine whether a given message is a valid daily check-in.

This model is part of a larger AI pipeline built for Coding in Color (CIC) to analyze and improve student check-ins.

🎯 Purpose

Students are required to submit daily check-ins describing their work. However, messages can vary widely and may include:

Announcements
Questions
Off-topic messages

This model filters those inputs and ensures only valid check-ins are processed further.

🧠 Model Details

Task: Binary Text Classification
Labels:
- CHECKIN → Valid check-in
- NOT_CHECKIN → Not a check-in
Architecture: Transformer-based (fine-tuned)

📦 Use Cases

Pre-processing filter for check-in pipelines
Slack/Discord message classification
Productivity tracking systems
Educational workflow automation

🧪 Example

Input

Today I worked on fixing my API deployment issue and tested endpoints

Output

json

{
  "label": "CHECKIN",
  "confidence": 0.98
}

Pipeline Integration

This model is the first step in a multi-model pipeline:

Check-in Detection (this model)
Check-in Quality Classification
Roadblock Detection
Check-in Generation (if needed)

Usage (Python)

python

from transformers import pipeline

classifier = pipeline("text-classification", model="mjpsm/check_in_or_not_v2")

result = classifier("Today I worked on building an API")
print(result)

Future Improvements

Improve edge case detection (short messages)
Add multi-label classification (e.g., check-in + question)
Expand dataset diversity

👤 Author

Mazamesso Meba
Information Systems Student | AI Developer