A fine-tuned ModernBERT model for enterprise chatbot intent classification. This model classifies user queries into predefined intent categories and is designed to be used as the first stage of a chatbot pipeline before Retrieval-Augmented Generation (RAG) or other downstream workflows.

Supported Intents

The model predicts one of the following intents:

Business
Greeting
SmallTalk
Complaint
Feedback
Thanks
Goodbye
OutOfDomain

Intended Use

This model is designed for:

Enterprise AI Chatbots
Customer Support Bots
HR Assistants
Knowledge Base Assistants
Intent Detection
Query Routing
RAG Pipeline Routing

Example flow:

User Query
      │
      ▼
Intent Classifier
      │
      ├── Business
      │      └── RAG Pipeline
      │
      ├── Greeting
      │      └── Greeting Response
      │
      ├── SmallTalk
      │      └── Small Talk Response
      │
      ├── Complaint
      │      └── Complaint Workflow
      │
      ├── Feedback
      │      └── Feedback Workflow
      │
      ├── Thanks
      │      └── Thank You Response
      │
      ├── Goodbye
      │      └── Goodbye Response
      │
      └── OutOfDomain
             └── Reject Politely

Base Model

Model: answerdotai/ModernBERT-base
Task: Sequence Classification
Framework: Hugging Face Transformers
Language: English

Example Usage

python

from transformers import pipeline

classifier = pipeline(
    "text-classification",
    model="yogeshpandey586/chatbot-intent-classifier"
)

print(classifier("Hello"))
print(classifier("What services do you provide?"))
print(classifier("Tell me a joke"))

Example Output

python

[
    {
        "label": "Greeting",
        "score": 0.998
    }
]

Training Dataset

The model was fine-tuned using a custom intent classification dataset containing manually labeled chatbot queries.

Each sample contains:

User Query
Intent Label

Example:

Query	Intent
Hello	Greeting
Hi	Greeting
Good Morning	Greeting
What services do you provide?	Business
How can I reset my password?	Business
Tell me a joke	SmallTalk
Thanks	Thanks
Bye	Goodbye
I have feedback	Feedback
Your service is bad	Complaint
Who won yesterday's IPL match?	OutOfDomain

Training Details

Base Model: ModernBERT-base
Fine-tuning Task: Sequence Classification
Framework: Hugging Face Transformers
Optimizer: AdamW
Loss Function: Cross Entropy Loss

Evaluation

The model was evaluated using a validation dataset.

Evaluation Metric:

Accuracy

This model is intended for production chatbot routing where low latency and high intent classification accuracy are required.

Limitations

This model is intended only for intent classification.

It is not designed for:

Toxicity Detection
Sentiment Analysis
Emotion Detection
Translation
Summarization
Question Answering
Text Generation

Performance may decrease on:

Languages other than English
Ambiguous user queries
Multi-intent queries
Queries outside the training domain

Production Architecture

User Query
      │
      ▼
ModernBERT Intent Classifier
      │
      ▼
Intent Router
      │
      ├── Business → RAG
      ├── Greeting → Greeting Service
      ├── SmallTalk → Small Talk Service
      ├── Complaint → Complaint Service
      ├── Feedback → Feedback Service
      ├── Thanks → Thank You Service
      ├── Goodbye → Goodbye Service
      └── OutOfDomain → Reject Response

Technical Specifications

Property	Value
Architecture	ModernBERT
Base Model	answerdotai/ModernBERT-base
Framework	Transformers
Task	Sequence Classification
Language	English
Deployment	CPU / GPU

Developer

Yogesh Pandey

AI Developer

License

Apache-2.0

Citation

bibtex

@misc{yogeshpandey2026intentclassifier,
  title={ModernBERT Chatbot Intent Classifier},
  author={Yogesh Pandey},
  year={2026},
  publisher={Hugging Face}
}