File size: 7,132 Bytes
d9be639
28f6af8
 
 
d9be639
 
 
 
 
 
28f6af8
4470087
 
 
 
 
 
28f6af8
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
d9be639
 
4470087
d9be639
6f63c85
7a45ab9
6f63c85
d9be639
 
4470087
 
 
 
 
 
 
d9be639
4470087
 
d9be639
4470087
 
 
2f3dfcf
4470087
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
de652f7
 
4470087
 
55f1803
4470087
28f6af8
 
 
 
 
 
 
 
 
 
 
 
55f1803
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
---
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- gguf
base_model: unsloth/phi-4-unsloth-bnb-4bit
datasets:
- bespokelabs/Bespoke-Stratos-17k
- bespokelabs/Bespoke-Stratos-35k
- NovaSky-AI/Sky-T1_data_17k
- Quazim0t0/BenfordsLawReasoningJSON
- open-thoughts/OpenThoughts-114k
model-index:
- name: Phi4.Turn.R1Distill_v1.5.1-Tensors
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: IFEval (0-Shot)
      type: HuggingFaceH4/ifeval
      args:
        num_few_shot: 0
    metrics:
    - type: inst_level_strict_acc and prompt_level_strict_acc
      value: 29.95
      name: strict accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Quazim0t0/Phi4.Turn.R1Distill_v1.5.1-Tensors
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: BBH (3-Shot)
      type: BBH
      args:
        num_few_shot: 3
    metrics:
    - type: acc_norm
      value: 49.22
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Quazim0t0/Phi4.Turn.R1Distill_v1.5.1-Tensors
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MATH Lvl 5 (4-Shot)
      type: hendrycks/competition_math
      args:
        num_few_shot: 4
    metrics:
    - type: exact_match
      value: 1.59
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Quazim0t0/Phi4.Turn.R1Distill_v1.5.1-Tensors
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GPQA (0-shot)
      type: Idavidrein/gpqa
      args:
        num_few_shot: 0
    metrics:
    - type: acc_norm
      value: 2.46
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Quazim0t0/Phi4.Turn.R1Distill_v1.5.1-Tensors
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MuSR (0-shot)
      type: TAUR-Lab/MuSR
      args:
        num_few_shot: 0
    metrics:
    - type: acc_norm
      value: 7.04
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Quazim0t0/Phi4.Turn.R1Distill_v1.5.1-Tensors
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU-PRO (5-shot)
      type: TIGER-Lab/MMLU-Pro
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 45.75
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Quazim0t0/Phi4.Turn.R1Distill_v1.5.1-Tensors
      name: Open LLM Leaderboard
---

# TurnPhi Project

> [!WARNING]
  > **Note:**  This was made before GRPO Training was released & is meant to be used as a base.

- **Developed by:** Quazim0t0
- **Finetuned from model :** unsloth/phi-4-unsloth-bnb-4bit
- **GGUF**
- **Trained for 8 Hours on A800 with the Bespoke Stratos 17k Dataset.**
- **Trained for 6 Hours on A800 with the Bespoke Stratos 35k Dataset.**
- **Trained for 2 Hours on A800 with the Benford's Law Reasoning Small 430 Row Dataset, ensuring no overfitting.**
- **Trained for 4 Hours on A800 with the Sky-T1_data_17k Dataset**
- **Trained for 6 Hours on A800 with the Openthoughts 114k Dataset.**
- **18$ Training...I'm actually amazed by the results.**

# OpenWeb UI Function
If using this model for Open WebUI here is a simple function to organize the models responses: https://openwebui.com/f/quaz93/phi4_turn_r1_distill_thought_function_v1

# Phi4 Turn R1Distill LoRA Adapters

## Overview
These **LoRA adapters** were trained using diverse **reasoning datasets** that incorporate structured **Thought** and **Solution** responses to enhance logical inference. This project was designed to **test the R1 dataset** on **Phi-4**, aiming to create a **medium-weight, fast, and efficient reasoning model**.

All adapters were fine-tuned using an **NVIDIA A800 GPU**, ensuring high performance and compatibility for continued training, merging, or direct deployment.  
As part of an open-source initiative, all resources are made **publicly available** for unrestricted research and development.

---

## LoRA Adapters  
Below are the currently available LoRA fine-tuned adapters (**as of January 30, 2025**):

- [Phi4.Turn.R1Distill-Lora1](https://huggingface.co/Quazim0t0/Phi4.Turn.R1Distill-Lora1)  
- [Phi4.Turn.R1Distill-Lora2](https://huggingface.co/Quazim0t0/Phi4.Turn.R1Distill-Lora2)  
- [Phi4.Turn.R1Distill-Lora3](https://huggingface.co/Quazim0t0/Phi4.Turn.R1Distill-Lora3)  
- [Phi4.Turn.R1Distill-Lora4](https://huggingface.co/Quazim0t0/Phi4.Turn.R1Distill-Lora4)  
- [Phi4.Turn.R1Distill-Lora5](https://huggingface.co/Quazim0t0/Phi4.Turn.R1Distill-Lora5)  
- [Phi4.Turn.R1Distill-Lora6](https://huggingface.co/Quazim0t0/Phi4.Turn.R1Distill-Lora6)  
- [Phi4.Turn.R1Distill-Lora7](https://huggingface.co/Quazim0t0/Phi4.Turn.R1Distill-Lora7)  
- [Phi4.Turn.R1Distill-Lora8](https://huggingface.co/Quazim0t0/Phi4.Turn.R1Distill-Lora8)  

---

## GGUF Full & Quantized Models  
To facilitate broader testing and real-world inference, **GGUF Full and Quantized versions** have been provided for evaluation on **Open WebUI** and other LLM interfaces.

### **Version 1**
- [Phi4.Turn.R1Distill.Q8_0](https://huggingface.co/Quazim0t0/Phi4.Turn.R1Distill.Q8_0)  
- [Phi4.Turn.R1Distill.Q4_k](https://huggingface.co/Quazim0t0/Phi4.Turn.R1Distill.Q4_k)  
- [Phi4.Turn.R1Distill.16bit](https://huggingface.co/Quazim0t0/Phi4.Turn.R1Distill.16bit)  

### **Version 1.1**
- [Phi4.Turn.R1Distill_v1.1_Q4_k](https://huggingface.co/Quazim0t0/Phi4.Turn.R1Distill_v1.1_Q4_k)  

### **Version 1.2**
- [Phi4.Turn.R1Distill_v1.2_Q4_k](https://huggingface.co/Quazim0t0/Phi4.Turn.R1Distill_v1.2_Q4_k)  

### **Version 1.3**
- [Phi4.Turn.R1Distill_v1.3_Q4_k-GGUF](https://huggingface.co/Quazim0t0/Phi4.Turn.R1Distill_v1.3_Q4_k-GGUF)  

### **Version 1.4**
- [Phi4.Turn.R1Distill_v1.4_Q4_k-GGUF](https://huggingface.co/Quazim0t0/Phi4.Turn.R1Distill_v1.4_Q4_k-GGUF)  

### **Version 1.5**
- [Phi4.Turn.R1Distill_v1.5_Q4_k-GGUF](https://huggingface.co/Quazim0t0/Phi4.Turn.R1Distill_v1.5_Q4_k-GGUF)  

---

## OpenLLM Leadboards
### **Score:**


```python

# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/Quazim0t0__Phi4.Turn.R1Distill_v1.5.1-Tensors-details)

|      Metric       |Value|
|-------------------|----:|
|Avg.               |22.67|
|IFEval (0-Shot)    |29.95|
|BBH (3-Shot)       |49.22|
|MATH Lvl 5 (4-Shot)| 1.59|
|GPQA (0-shot)      | 2.46|
|MuSR (0-shot)      | 7.04|
|MMLU-PRO (5-shot)  |45.75|