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updated train.py for ceb mode

feat: add counter-facts to fake verdict, fix train.py skiprows, enable oversampling for language models, suppress tqdm output

Integrated pattern deviation, fixed Cebuano modeling, and added ISO Survey

feat: Implement inverted pyramid structure analysis for articles, including language detection and journalistic signal checks, and add new training and core checker modules.

feat: Add fake news detection model training script utilizing hybrid features (TF-IDF, MiniLM, stylometric) and a core checker module, along with updated dependencies.

feat: enhanced bias analysis + obfuscation detection

feat: bias analyzer improvements, VADER integration, LIME samples reduction

feat: Implement a unified fact-checking engine integrating internal ML models, external source verification, and date validation with associated data and training scripts.

added date checker because context changes over time

added feature

added feature extractions for more precise internal checking.