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🚀 Qwen2.5-3B Fine-Tuned on BBH (Formal Fallacies) - Model Card |
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📌 Model Overview |
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Model Name: Qwen2.5-3B Fine-Tuned on BBH (Formal Fallacies) |
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Base Model: Qwen2.5-3B-Instruct |
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Fine-Tuned Dataset: BBH (BigBench Hard) - Formal Fallacies |
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Task: Logical Reasoning & Deductive Validity Classification |
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Fine-Tuning Objective: Improve the model’s ability to classify logical arguments as valid or invalid based on deductive reasoning principles. |
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📌 Dataset Information |
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This model was fine-tuned on the Formal Fallacies subset of the BigBench Hard (BBH) dataset. |
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Dataset characteristics: |
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Task Type: Deductive reasoning & formal logic classification |
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Input Format: Logical argument statements presented in natural language |
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Target Labels: "valid" or "invalid" |
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Example: |
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Input: |
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"Here comes a perfectly valid argument: First, being a cousin of Chris is sufficient for not being a son of Kermit. We may conclude that whoever is not a son of Kermit is a cousin of Chris." |
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Target: "invalid" |
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This dataset evaluates a model’s ability to identify logically valid vs. invalid arguments, which is crucial for AI-assisted legal analysis, debate systems, and automated theorem proving. |