--- language: en tags: - phi-3.5 - finetuned - essay-evaluation - education - nlp license: mit datasets: private base_model: - microsoft/Phi-3.5-mini-instruct --- # Essay Evaluator - Finetuned Phi-3.5-mini-instruct This model is a fine-tuned version of microsoft/Phi-3.5-mini-instruct, specifically trained for evaluating student written essays and providing numerical scores on a scale of 1-6. ## Model Description - **Model Architecture:** Based on Phi-3.5-mini-instruct (3.8B parameters) - **Training Focus:** Essay evaluation and scoring - **Input Format:** Essays in English - **Output Format:** Numerical score (1-6) - **Fine-tuning Focus:** Holistic essay assessment considering: - Content quality - Organization - Language use ## Intended Use - **Primary Use:** Automated essay scoring in educational contexts - **Target Users:** - Educational institutions - Teachers - Students (for self-assessment) - **Scope:** English academic essays ## Training Details - **Base Model:** microsoft/Phi-3.5-mini-instruct - **Training Type:** Supervised fine-tuning - **Training Data:** Balanced dataset of scored academic essays - **Parameters:** - Learning rate: 2e-5 - Epochs: 2 - Batch size: 1 ## Performance and Limitations ### Strengths - Consistent scoring across similar essays - Fast evaluation time - Structured numerical output ### Limitations - Limited to English language essays - Should be used as an assistive tool, not a replacement for human grading - Best suited for students essay formats ## Example Usage ```python # API request format headers = { "Content-Type": "application/json", "Authorization": f"Bearer {API_KEY}" } data = { "messages": [ { "role": "system", "content": "You are an experienced English teacher specializing in grading high school student essays. Read the following essay carefully and provide a holistic score from 1 to 6 based on content, organization, and language use. Provide only the numerical score." }, { "role": "user", "content": "YOUR_ESSAY_TEXT" } ] }