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Verified signature# framing-bert-model `framing-bert-model` is a fine-tuned BERT-based model that performs **multi-label classification** to identify framing elements in news articles, based on Robert Entman's typology of framing. This model helps detect how news frames are constructed through: 1. **Define Problem** – Identifying the core issue or topic. 2. **Diagnose Cause** – Assigning causality or source. 3. **Make Moral Judgment** – Expressing value-based judgments. 4. **Suggest Remedy** – Proposing solutions or actions. --- ## 🧠 Model Details - **Base model**: `bert-base-uncased` - **Architecture**: `BertForSequenceClassification` (multi-label) - **Tokenizer**: `BertTokenizer` (uncased) - **Training objective**: Binary cross-entropy loss across 4 framing categories - **Number of labels**: 4 ### ✅ Best Hyperparameters (via Optuna) ```json { "learning_rate": 4.235958496352736e-05, "weight_decay": 0.221987649206252, "num_train_epochs": 3 } ``` --- ## 📊 Performance (on Validation Set) …c8038aa -
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Verified signature# Framing Detection with BERT This repository contains a fine-tuned BERT-based model for detecting **framing elements** in news articles. The model is built on top of `bert-base-uncased` using the Hugging Face Transformers library and trained on a custom-labeled dataset consisting of 3,000 news articles. ## 📚 Framing Theory Framing is a concept from communication and media studies that refers to the way information is presented to influence audience interpretation. According to **Robert M. Entman (1993)**, framing involves four key elements: 1. **Define problems** – identifying what a causal agent is doing with what costs and benefits. 2. **Diagnose causes** – identifying the forces creating the problem. 3. **Make moral judgments** – evaluating causal agents and their effects. 4. **Suggest remedies** – proposing solutions to the problem and predicting their likely outcomes. These four elements serve as the foundation for the classification labels used in this model. ## 📰 Datase…f048f37 -
README.md
Verified signature# 🧠 Framing BERT Model (Multi-Label Classification) A fine-tuned `bert-base-uncased` model for **multi-label classification** of *news framing elements*, based on a custom annotated dataset of news texts. The model detects four common elements of framing in political and social discourse. ## 📚 Labels # Framing Elements Classification with BERT ## Overview This project focuses on classifying **framing elements** in news text based on the framing theory of **Robert Entman (1993)**. We fine-tuned a BERT-based sequence classification model to predict the presence of the following four core framing elements: - **`define_problem`** – Whether the text defines a social or political problem. - **`diagnose_cause`** – Whether the text attributes causes or sources for the issue. - **`moral_judgment`** – Whether the text expresses a normative or value-laden evaluation. - **`suggest_remedy`** – Whether the text suggests solutions, actions, or remedies. --- ## Model - **Base Model:** `bert…f03db73 -
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