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README.md

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+Student Chat Toxicity Classifier
+This model is a fine-tuned version of the s-nlp/roberta_toxicity_classifier and is designed to classify text-based messages in student conversations as toxic or non-toxic. It is specifically tailored to detect and flag malpractice suggestions, unethical advice, or any toxic communication while encouraging ethical and positive interactions among students.
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+Model Details
+Language: English (en)
+Base Model: s-nlp/roberta_toxicity_classifier
+Task: Text Classification (Binary)
+Class 0: Non-Toxic
+Class 1: Toxic
+Key Features:
+Detects messages promoting cheating or malpractice.
+Flags harmful or unethical advice in student chats.
+Encourages ethical and constructive communication.
+Training Details
+Dataset: The model was fine-tuned on a custom dataset containing examples of student conversations labeled as toxic (malpractice suggestions, harmful advice) or non-toxic (positive and constructive communication).
+Preprocessing:
+Tokenization using RobertaTokenizer.
+Truncation and padding applied for consistent input length (max_length=128).
+Framework: Hugging Face's transformers library.
+Optimizer: AdamW
+Loss Function: CrossEntropyLoss
+Epochs: 3 (adjusted for convergence)