This is a text-classification model to classify text on Bloom's Taxonomy Levels.

The Blooms Taxonomy Dataset is a structured collection of educational materials categorized according to Bloom's Taxonomy, a hierarchical model that classifies cognitive skills into six levels: Remembering, Understanding, Applying, Analyzing, Evaluating, and Creating. Key Levels:

  • BT1: Remembering: Recall or recognize basic facts and concepts.
  • BT2: Understanding: Comprehend and explain ideas or concepts.
  • BT3: Applying: Use knowledge in new situations or solve problems.
  • BT4: Analyzing: Break down information to explore relationships and patterns.
  • BT5: Evaluating:Make judgments based on criteria or standards.
  • BT6: Creating:Generate new ideas, products, or approaches by combining information.

Each level reflects a progressively higher order of cognitive skills. This dataset is designed to support research and development in educational tools, assessment systems, and machine learning models by providing examples of tasks, questions, or content aligned with each cognitive level. It aids in the analysis of learning objectives and helps educators design curriculum and assessments that target various levels of student cognition.

Fine tuned on Bloom's Taxonomy Dataset from Kaggle

Usage

from transformers import pipeline

sentence1 = "List three predominant economic systems that exist!"

classifier = pipeline("sentiment-analysis", model=model,tokenizer=tokenizer)

classifier(sentence1)

Uploaded model

  • Developed by: manzarimalik
  • License: apache-2.0
  • Finetuned from model : answerdotai/ModernBERT-large

This modernbert model was trained 2x faster with Unsloth and Huggingface's TRL library.

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