NextGenInstitute commited on
Commit
73309b0
·
verified ·
1 Parent(s): e97e7a6

Upload README.md with huggingface_hub

Browse files
Files changed (1) hide show
  1. README.md +38 -14
README.md CHANGED
@@ -1,22 +1,46 @@
1
  ---
 
2
  base_model: unsloth/Muse-Glimmer-30B-unsloth-bnb-4bit
3
  tags:
4
- - text-generation-inference
5
- - transformers
6
- - unsloth
7
- - muse_glimmer
8
- - trl
9
- license: apache-2.0
10
- language:
11
- - en
 
 
 
 
 
 
 
12
  ---
13
 
14
- # Uploaded model
 
 
 
 
 
 
 
 
 
 
15
 
16
- - **Developed by:** NextGenInstitute
17
- - **License:** apache-2.0
18
- - **Finetuned from model :** unsloth/Muse-Glimmer-30B-unsloth-bnb-4bit
19
 
20
- This muse_glimmer model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth)
 
 
 
 
 
 
 
21
 
22
- [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
 
 
1
  ---
2
+ license: apache-2.0
3
  base_model: unsloth/Muse-Glimmer-30B-unsloth-bnb-4bit
4
  tags:
5
+ - socratic-tutoring
6
+ - ai-education
7
+ - pedagogy
8
+ - dpo
9
+ - sft
10
+ - unsloth
11
+ - direct-preference-optimization
12
+ - computer-science-education
13
+ datasets:
14
+ - NextGenInstitute/socraticDataset1680
15
+ metrics:
16
+ - direct_code_leakage_rate
17
+ - conceptual_diagnostic_accuracy
18
+ - pedagogical_utility_score
19
+ pipeline_tag: text-generation
20
  ---
21
 
22
+ # Socratic Muse-30B (SFT + DPO Alignment)
23
+
24
+ This repository contains the LoRA adapters for **Socratic Muse-30B**, post-trained using a two-stage **Supervised Fine-Tuning (SFT)** and **Direct Preference Optimization (DPO)** curriculum designed for undergraduate Artificial Intelligence education.
25
+
26
+ ## 🎯 Model Overview & Pedagogical Purpose
27
+ Standard code generation LLMs default to leaking direct copy-paste code solutions when students face programming bugs, eliminating the productive struggle needed for conceptual mastery.
28
+
29
+ **Socratic Muse-30B** is aligned to:
30
+ 1. **Withhold Direct Code Fixes (0.0% Code Leakage)**: Strictly suppresses raw syntax/code blocks and functions.
31
+ 2. **Accurately Diagnose Conceptual Algorithmic Misconceptions (90.0% Conceptual Diagnostic Accuracy)** across 5 AI subject areas.
32
+ 3. **Provide High Pedagogical Scaffolding Utility (4.75 / 5.0 Mean Pedagogical Utility)**, rivaling proprietary frontier models (GPT-5.4-mini at 4.67 and Gemini 3.5 Flash at 4.79).
33
 
34
+ ## 📊 EAAI Benchmark Performance (150 Held-Out AI Debugging Scenarios)
 
 
35
 
36
+ | Model Baseline | Direct Code Leakage (↓) | Pedagogical Utility (1-5) (↑) | Conceptual Accuracy % (↑) |
37
+ | :--- | :---: | :---: | :---: |
38
+ | **Gemini 3.5 Flash (Google Frontier)** | **0.0%** | **4.79 / 5.0** | **98.7%** |
39
+ | **GPT-5.4-mini (Proprietary)** | **0.0%** | **4.67 / 5.0** | **98.7%** |
40
+ | **Socratic Muse-30B (SFT+DPO)** | **0.0%** | **4.75 / 5.0** | **90.0%** |
41
+ | **Socratic Llama-8B (SFT+DPO)** | **0.0%** | **3.54 / 5.0** | **76.0%** |
42
+ | Base Llama-3.1-8B-Instruct | 1.3% | 2.55 / 5.0 | 20.0% |
43
+ | Qwen2.5-Coder-7B-Instruct | 6.0% | 2.37 / 5.0 | 20.0% |
44
 
45
+ ## 📚 Dataset
46
+ The model was aligned on the **[Socratic AI Pedagogy Preference Dataset (1,680 Quadruplets)](https://huggingface.co/datasets/NextGenInstitute/socraticDataset1680)**.