---
language:
- en
pipeline_tag: question-answering
metrics:
- bleu
base_model:
- google/flan-t5-small
library_name: transformers
tags:
- text-generation-inference
- transformer
- question-answering
- fine-tuned
- text-generation
---
# **Generative QA Chatbot for Climate Education**

This chatbot help users (especially students, young activists, or the general public) learn about climate change, its causes, impacts, solutions, and key concepts through conversational Q&A.

- Model: T5-small (Text-To-Text Transfer Transformer)
- Framework: TensorFlow
- Evaluation Metrics: BLEU Score

#### **Domain Justification:**
Climate education chatbots address the critical need for accessible, accurate climate science information. Think of it like having a climate science teacher available 24/7 who can explain complex concepts like carbon cycles, greenhouse effects, or climate policies in simple terms.

#### **Architecture Breakdown:**
- Architecture Type: Encoder-Decoder Transformer
- Layers: 6 Encoder + 6 Decoder
- Parameters: 60,506,624 (60M)
- Size: ~240 MB
- Performance: 0.0549 BLEU, ~17s generation
- Attention Mechanism: Multi-Head Self-Attention
- Position Encoding: Relative Position Bias
- Activation Function: ReLU

**Checkout the deployed QA chatbot on Streamlit Cloud:** https://ayika-app-v1.streamlit.app/

**Author:** Eunice Adewusi Climiradi

**My Links:** https://linktr.ee/climiradi

**Date:** June 2025