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Model: kaushik-harsh-99/Math-Instruct-v1
Source: Original Platform

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README.md

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+---
+license: apache-2.0
+language:
+- en
+tags:
+- mathematics
+- math
+- sft
+- instruction-tuning
+- transformers
+pipeline_tag: text-generation
+pretty_name: MathInstruct v1
+library_name: transformers
+datasets:
+- nvidia/OpenMathInstruct-2
+base_model:
+- Qwen/Qwen3-0.6B
+---
+
+# MathInstruct v1
+
+MathInstruct v1 is a mathematics-focused instruction-tuned language model created by supervised fine-tuning a pretrained base model on curated mathematics training data.
+
+This release aims to improve mathematical instruction following, solution generation, and benchmark performance while maintaining the original capabilities of the base model.
+
+
+## Results
+
+Benchmark performance compared with the original base model is shown below.
+
+![Benchmark Results](./1.png)
+
+MathInstruct v1 demonstrates improvements across mathematical evaluation tasks and stronger instruction-following behavior.
+
+## Training
+
+MathInstruct v1 was trained using supervised fine-tuning (SFT) on the NVIDIA OpenMath dataset.
+
+The model was trained for **0.1 epoch** to adapt the base model toward stronger mathematical instruction following and solution generation while preserving its original capabilities.
+
+Training setup:
+
+* Supervised fine-tuning (SFT)
+* Dataset: NVIDIA OpenMath
+* Training duration: 0.1 epoch
+* No manual filtering or removal of noisy samples
+* Original dataset distribution preserved
+* Minimal preprocessing for training compatibility
+
+
+## Limitations
+
+The model may still generate incorrect reasoning or inaccurate answers. Verify outputs before using them in important scenarios.

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