🚀 Qwen2.5-3B Fine-Tuned on BBH (Dyck Languages) - Model Card 📌 Model Overview Model Name: Qwen2.5-3B Fine-Tuned on BBH (Dyck Languages) Base Model: Qwen2.5-3B-Instruct Fine-Tuned Dataset: BBH (BigBench Hard) - Dyck Languages Task: Causal Language Modeling (CLM) Fine-Tuning Objective: Improve performance on Dyck language sequence completion (correctly closing nested parentheses and brackets) 📌 Dataset Information This model was fine-tuned on the Dyck Languages subset of the BigBench Hard (BBH) dataset.
Dataset characteristics:
Task Type: Sequence completion of balanced parentheses Input Format: A sequence of open parentheses, brackets, or braces with missing closing elements Target Labels: The correct sequence of closing parentheses, brackets, or braces Example:
Input: Complete the rest of the sequence, making sure that the parentheses are closed properly. Input: [ [
Target: ] ]
This dataset evaluates a model’s ability to correctly complete structured sequences, which is crucial for programming language syntax, formal language understanding, and symbolic reasoning.