Create README.md

README.md

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+---
+license: apache-2.0
+language:
+- en
+base_model: Qwen/Qwen3-1.7B
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- qwen3
+- sft
+- general-knowledge
+- multiple-choice
+- cs-552
+datasets:
+- cais/mmlu
+metrics:
+- accuracy
+---
+
+# General Knowledge Model
+
+This model is a fine-tuned version of [`Qwen/Qwen3-1.7B`](https://huggingface.co/Qwen/Qwen3-1.7B) for the CS-552 Modern NLP course project.
+
+The model targets the **General Knowledge** benchmark, where it answers closed-book multiple-choice factual and reasoning questions. It was trained to return the final answer as a single option letter inside a LaTeX `\boxed{}` expression.
+
+## Intended output format
+
+The model should produce answers in the following format:
+
+```text
+\boxed{C}
+```
+
+Anything outside `\boxed{}` is treated as reasoning and is not used for scoring by the evaluation pipeline.
+
+## Training procedure
+
+This checkpoint was trained using **Supervised Fine-Tuning (SFT)** with LoRA on top of `Qwen/Qwen3-1.7B`.
+
+The SFT data was formatted as instruction-style multiple-choice examples:
+
+```text
+Q: ...
+A) ...
+B) ...
+C) ...
+D) ...
+
+Answer: \boxed{C}
+```
+
+The current checkpoint was trained on a processed General Knowledge dataset derived from MMLU-style multiple-choice examples.
+
+## Model behavior
+
+The model is optimized for:
+
+- closed-book factual question answering
+- multiple-choice reasoning
+- final-answer extraction through `\boxed{}`
+- concise option-letter responses
+
+The tokenizer chat template was configured with non-thinking mode to encourage concise answers.
+
+## Local validation
+
+On the provided General Knowledge validation snapshot from the course starter repository, this checkpoint achieved:
+
+- Extraction rate: `10/10`
+- Accuracy: `6/10`
+
+These validation samples are only a small sanity-check set and are not the hidden evaluation benchmark.
+
+## Framework versions
+
+- Transformers
+- PEFT
+- PyTorch
+- Datasets
+- Hugging Face Hub
+
+## Limitations
+
+This is an intermediate SFT baseline, not the final model. It was trained mainly to establish a working General Knowledge pipeline and verify that the model can produce extractable boxed answers. Performance may vary on broader or harder factual reasoning tasks.