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Remove Reddit scraper, add IBM Claim Stance loaderβ
Reddit's Responsible Builder Policy prohibits using scraped data to train ML/AI models and requires RFR Program approval for all research use. - Remove data/loaders/reddit.py and .env.example - Drop praw from requirements.txt - Add data/loaders/claim_stance.py (ibm/claim_stance via HuggingFace): ~2,400 claim/counter-claim pairs with PRO/CON stance labels, auto-downloads - Update data/__init__.py and loaders/__init__.py exports accordingly - Update data/README.md to document the new source Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>e82a201
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Updating the Data Model : IBM Debater vs CMV, testing out CVM and check if it's good or notβ
stefhooyhttps://www.cs.cornell.edu/~cristian/pdfs/winning_arguments.pdf https://convokit.cornell.edu/documentation/winning.html94abcb8
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Created src/dataset.py β converts Debate objects into PyTorch tensors for RoBERTaβ
stefhooyCreated src/model.py β loads roberta-base configured for 4-class classification Created src/train.py β full training loop with class weights, AdamW optimizer, validation, checkpoint saving Created src/__init__.py β predict() and predict_debate() functions for other team members to use Fixed Person 1's IBM loader bug (was ignoring stance_WA, labeling everything as premise) Trained a first model (wrong labels, now discarded) What still needs to be done right now: Retrain with the fixed labels β run python -m src.train --epochs 3 --batch-size 8 Sanity check the model once training finishes β run a quick predict test to confirm it returns different labels for different inputs Commit and push the fixed code to the repo so the rest of the team can use predict() and predict_debate()deefbae -
Setting up the training model first draft and also updating the requirements.txt for the second part of this project.
stefhooy28e0f73
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Add data loading pipeline (Person 1)β
Unified schema (Argument, Debate dataclasses), loaders for CMV offline dataset, IBM Debater via HuggingFace, and a live Reddit scraper via PRAW. Preprocessing module strips Reddit noise and filters short/deleted text. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>54cd75a