How sutarshoeb/nlp-case-study-ca3 works
This repository is a notebook-based study comparing classical machine-learning classifiers with GPT fine-tuning for binary classification of research abstracts. Users supply datasets and run either notebook: the classical workflow vectorizes text and evaluates sklearn models, while the fine-tuning workflow prepares data and uses the OpenAI fine-tuning API. Both approaches are compared using test-set metrics. The README documents these capabilities; notebook internals were not sampled, so the graph shows only documented stages and avoids asserting finer-grained wiring.
Main entry points: NLP_Fine_Tuning.ipynb Fine-tuning workflow · Traditional_ML_Implementation_Abstract.ipynb Classical workflow
Components 13
Classical ML
- Classical workflow
notebooks/Traditional_ML_Implementation_Abstract.ipynb - Count / TF-IDF
notebooks/Traditional_ML_Implementation_Abstract.ipynb - Sklearn classifiers
notebooks/Traditional_ML_Implementation_Abstract.ipynb
GPT Fine-Tuning
- Fine-tuning workflow
notebooks/NLP_Fine_Tuning.ipynb - GPT-4.1-nano
notebooks/NLP_Fine_Tuning.ipynb
Evaluation
- Classical test metrics
notebooks/Traditional_ML_Implementation_Abstract.ipynb - GPT test metrics
notebooks/NLP_Fine_Tuning.ipynb - Model comparison
notebooks/Traditional_ML_Implementation_Abstract.ipynb
Other components
- Notebook user
- Classified abstracts CSV
- Train/val/test CSVs
- Colab API key
- OpenAI fine-tuning API
Connections 16
- Notebook user → Classical workflow: runs
- Notebook user → Fine-tuning workflow: runs
- Notebook user → Classified abstracts CSV: uploads
- Classified abstracts CSV → Classical workflow: provides data
- Classical workflow → Count / TF-IDF: vectorizes text
- Classical workflow → Sklearn classifiers: trains models
- Sklearn classifiers → Classical test metrics: evaluates
- Classical test metrics → Model comparison: contributes scores
- Notebook user → Train/val/test CSVs: uploads
- Train/val/test CSVs → Fine-tuning workflow: provides data
- Notebook user → Colab API key: stores key
- Colab API key → Fine-tuning workflow: provides credential
- Fine-tuning workflow → OpenAI fine-tuning API: uses fine-tuning API
- OpenAI fine-tuning API → GPT-4.1-nano: fine-tunes
- Fine-tuning workflow → GPT test metrics: evaluates test set
- GPT test metrics → Model comparison: contributes scores