Adding Evaluation Results
#2
by
leaderboard-pr-bot
- opened
README.md
CHANGED
@@ -1,10 +1,9 @@
|
|
1 |
---
|
2 |
-
license: cc-by-nc-4.0
|
3 |
language:
|
4 |
- en
|
5 |
- de
|
|
|
6 |
library_name: transformers
|
7 |
-
pipeline_tag: text-generation
|
8 |
tags:
|
9 |
- finetune
|
10 |
- dpo
|
@@ -13,6 +12,110 @@ tags:
|
|
13 |
- german
|
14 |
datasets:
|
15 |
- argilla/distilabel-math-preference-dpo
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
16 |
---
|
17 |
|
18 |
![Juanako.AI & SauerkrautLM Productions](https://vago-solutions.de/wp-content/uploads/2023/12/sauerkrautlm-solar.png "LUNA-SOLARkrautLM-Instruct")
|
@@ -270,3 +373,17 @@ We are also keenly seeking support and investment for our startup, [VAGO Solutio
|
|
270 |
Big Hug to [VAGO Solutions](https://huggingface.co/VAGOsolutions), we merely used our UNA transformers library on their code and dataset, nothing else. This won't be possible without them, thanks!
|
271 |
|
272 |
Many thanks to [argilla](https://huggingface.co/datasets/argilla) and [Huggingface](https://huggingface.co) for providing such valuable datasets to the Open-Source community. And of course a big thanks to [upstage](https://huggingface.co/upstage) for providing the open source community with their latest technology!
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
---
|
|
|
2 |
language:
|
3 |
- en
|
4 |
- de
|
5 |
+
license: cc-by-nc-4.0
|
6 |
library_name: transformers
|
|
|
7 |
tags:
|
8 |
- finetune
|
9 |
- dpo
|
|
|
12 |
- german
|
13 |
datasets:
|
14 |
- argilla/distilabel-math-preference-dpo
|
15 |
+
pipeline_tag: text-generation
|
16 |
+
model-index:
|
17 |
+
- name: LUNA-SOLARkrautLM-Instruct
|
18 |
+
results:
|
19 |
+
- task:
|
20 |
+
type: text-generation
|
21 |
+
name: Text Generation
|
22 |
+
dataset:
|
23 |
+
name: AI2 Reasoning Challenge (25-Shot)
|
24 |
+
type: ai2_arc
|
25 |
+
config: ARC-Challenge
|
26 |
+
split: test
|
27 |
+
args:
|
28 |
+
num_few_shot: 25
|
29 |
+
metrics:
|
30 |
+
- type: acc_norm
|
31 |
+
value: 71.16
|
32 |
+
name: normalized accuracy
|
33 |
+
source:
|
34 |
+
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fblgit/LUNA-SOLARkrautLM-Instruct
|
35 |
+
name: Open LLM Leaderboard
|
36 |
+
- task:
|
37 |
+
type: text-generation
|
38 |
+
name: Text Generation
|
39 |
+
dataset:
|
40 |
+
name: HellaSwag (10-Shot)
|
41 |
+
type: hellaswag
|
42 |
+
split: validation
|
43 |
+
args:
|
44 |
+
num_few_shot: 10
|
45 |
+
metrics:
|
46 |
+
- type: acc_norm
|
47 |
+
value: 88.28
|
48 |
+
name: normalized accuracy
|
49 |
+
source:
|
50 |
+
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fblgit/LUNA-SOLARkrautLM-Instruct
|
51 |
+
name: Open LLM Leaderboard
|
52 |
+
- task:
|
53 |
+
type: text-generation
|
54 |
+
name: Text Generation
|
55 |
+
dataset:
|
56 |
+
name: MMLU (5-Shot)
|
57 |
+
type: cais/mmlu
|
58 |
+
config: all
|
59 |
+
split: test
|
60 |
+
args:
|
61 |
+
num_few_shot: 5
|
62 |
+
metrics:
|
63 |
+
- type: acc
|
64 |
+
value: 66.11
|
65 |
+
name: accuracy
|
66 |
+
source:
|
67 |
+
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fblgit/LUNA-SOLARkrautLM-Instruct
|
68 |
+
name: Open LLM Leaderboard
|
69 |
+
- task:
|
70 |
+
type: text-generation
|
71 |
+
name: Text Generation
|
72 |
+
dataset:
|
73 |
+
name: TruthfulQA (0-shot)
|
74 |
+
type: truthful_qa
|
75 |
+
config: multiple_choice
|
76 |
+
split: validation
|
77 |
+
args:
|
78 |
+
num_few_shot: 0
|
79 |
+
metrics:
|
80 |
+
- type: mc2
|
81 |
+
value: 73.37
|
82 |
+
source:
|
83 |
+
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fblgit/LUNA-SOLARkrautLM-Instruct
|
84 |
+
name: Open LLM Leaderboard
|
85 |
+
- task:
|
86 |
+
type: text-generation
|
87 |
+
name: Text Generation
|
88 |
+
dataset:
|
89 |
+
name: Winogrande (5-shot)
|
90 |
+
type: winogrande
|
91 |
+
config: winogrande_xl
|
92 |
+
split: validation
|
93 |
+
args:
|
94 |
+
num_few_shot: 5
|
95 |
+
metrics:
|
96 |
+
- type: acc
|
97 |
+
value: 82.95
|
98 |
+
name: accuracy
|
99 |
+
source:
|
100 |
+
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fblgit/LUNA-SOLARkrautLM-Instruct
|
101 |
+
name: Open LLM Leaderboard
|
102 |
+
- task:
|
103 |
+
type: text-generation
|
104 |
+
name: Text Generation
|
105 |
+
dataset:
|
106 |
+
name: GSM8k (5-shot)
|
107 |
+
type: gsm8k
|
108 |
+
config: main
|
109 |
+
split: test
|
110 |
+
args:
|
111 |
+
num_few_shot: 5
|
112 |
+
metrics:
|
113 |
+
- type: acc
|
114 |
+
value: 60.88
|
115 |
+
name: accuracy
|
116 |
+
source:
|
117 |
+
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fblgit/LUNA-SOLARkrautLM-Instruct
|
118 |
+
name: Open LLM Leaderboard
|
119 |
---
|
120 |
|
121 |
![Juanako.AI & SauerkrautLM Productions](https://vago-solutions.de/wp-content/uploads/2023/12/sauerkrautlm-solar.png "LUNA-SOLARkrautLM-Instruct")
|
|
|
373 |
Big Hug to [VAGO Solutions](https://huggingface.co/VAGOsolutions), we merely used our UNA transformers library on their code and dataset, nothing else. This won't be possible without them, thanks!
|
374 |
|
375 |
Many thanks to [argilla](https://huggingface.co/datasets/argilla) and [Huggingface](https://huggingface.co) for providing such valuable datasets to the Open-Source community. And of course a big thanks to [upstage](https://huggingface.co/upstage) for providing the open source community with their latest technology!
|
376 |
+
|
377 |
+
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
|
378 |
+
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_fblgit__LUNA-SOLARkrautLM-Instruct)
|
379 |
+
|
380 |
+
| Metric |Value|
|
381 |
+
|---------------------------------|----:|
|
382 |
+
|Avg. |73.79|
|
383 |
+
|AI2 Reasoning Challenge (25-Shot)|71.16|
|
384 |
+
|HellaSwag (10-Shot) |88.28|
|
385 |
+
|MMLU (5-Shot) |66.11|
|
386 |
+
|TruthfulQA (0-shot) |73.37|
|
387 |
+
|Winogrande (5-shot) |82.95|
|
388 |
+
|GSM8k (5-shot) |60.88|
|
389 |
+
|