leaderboard-pr-bot commited on
Commit
5752dee
1 Parent(s): f532750

Adding Evaluation Results

Browse files

This is an automated PR created with https://huggingface.co/spaces/Weyaxi/open-llm-leaderboard-results-pr

The purpose of this PR is to add evaluation results from the Open LLM Leaderboard to your model card.

If you encounter any issues, please report them to https://huggingface.co/spaces/Weyaxi/open-llm-leaderboard-results-pr/discussions

Files changed (1) hide show
  1. README.md +118 -2
README.md CHANGED
@@ -1,10 +1,113 @@
1
  ---
2
- license: apache-2.0
3
  language:
4
  - en
5
  - zh
 
6
  library_name: transformers
7
  pipeline_tag: conversational
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
8
  ---
9
  # Model Card for MindLLM
10
 
@@ -187,4 +290,17 @@ This version of model was trained on about 241 billion English tokens and 82 bil
187
 
188
  This version of model was also fine-tuned on 4 million Chinese instruction samples which are collected from open source instruction tuning datasets. The instruction tuning stage make the model can answer questions and perform multi-turns conversation **in Chinese**.
189
 
190
- **For more detailed information, please refer to the paper.**
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
  ---
 
2
  language:
3
  - en
4
  - zh
5
+ license: apache-2.0
6
  library_name: transformers
7
  pipeline_tag: conversational
8
+ model-index:
9
+ - name: MindLLM
10
+ results:
11
+ - task:
12
+ type: text-generation
13
+ name: Text Generation
14
+ dataset:
15
+ name: AI2 Reasoning Challenge (25-Shot)
16
+ type: ai2_arc
17
+ config: ARC-Challenge
18
+ split: test
19
+ args:
20
+ num_few_shot: 25
21
+ metrics:
22
+ - type: acc_norm
23
+ value: 22.44
24
+ name: normalized accuracy
25
+ source:
26
+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=bit-dny/MindLLM
27
+ name: Open LLM Leaderboard
28
+ - task:
29
+ type: text-generation
30
+ name: Text Generation
31
+ dataset:
32
+ name: HellaSwag (10-Shot)
33
+ type: hellaswag
34
+ split: validation
35
+ args:
36
+ num_few_shot: 10
37
+ metrics:
38
+ - type: acc_norm
39
+ value: 34.11
40
+ name: normalized accuracy
41
+ source:
42
+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=bit-dny/MindLLM
43
+ name: Open LLM Leaderboard
44
+ - task:
45
+ type: text-generation
46
+ name: Text Generation
47
+ dataset:
48
+ name: MMLU (5-Shot)
49
+ type: cais/mmlu
50
+ config: all
51
+ split: test
52
+ args:
53
+ num_few_shot: 5
54
+ metrics:
55
+ - type: acc
56
+ value: 25.5
57
+ name: accuracy
58
+ source:
59
+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=bit-dny/MindLLM
60
+ name: Open LLM Leaderboard
61
+ - task:
62
+ type: text-generation
63
+ name: Text Generation
64
+ dataset:
65
+ name: TruthfulQA (0-shot)
66
+ type: truthful_qa
67
+ config: multiple_choice
68
+ split: validation
69
+ args:
70
+ num_few_shot: 0
71
+ metrics:
72
+ - type: mc2
73
+ value: 43.48
74
+ source:
75
+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=bit-dny/MindLLM
76
+ name: Open LLM Leaderboard
77
+ - task:
78
+ type: text-generation
79
+ name: Text Generation
80
+ dataset:
81
+ name: Winogrande (5-shot)
82
+ type: winogrande
83
+ config: winogrande_xl
84
+ split: validation
85
+ args:
86
+ num_few_shot: 5
87
+ metrics:
88
+ - type: acc
89
+ value: 49.33
90
+ name: accuracy
91
+ source:
92
+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=bit-dny/MindLLM
93
+ name: Open LLM Leaderboard
94
+ - task:
95
+ type: text-generation
96
+ name: Text Generation
97
+ dataset:
98
+ name: GSM8k (5-shot)
99
+ type: gsm8k
100
+ config: main
101
+ split: test
102
+ args:
103
+ num_few_shot: 5
104
+ metrics:
105
+ - type: acc
106
+ value: 0.83
107
+ name: accuracy
108
+ source:
109
+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=bit-dny/MindLLM
110
+ name: Open LLM Leaderboard
111
  ---
112
  # Model Card for MindLLM
113
 
 
290
 
291
  This version of model was also fine-tuned on 4 million Chinese instruction samples which are collected from open source instruction tuning datasets. The instruction tuning stage make the model can answer questions and perform multi-turns conversation **in Chinese**.
292
 
293
+ **For more detailed information, please refer to the paper.**
294
+ # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
295
+ Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_bit-dny__MindLLM)
296
+
297
+ | Metric |Value|
298
+ |---------------------------------|----:|
299
+ |Avg. |29.28|
300
+ |AI2 Reasoning Challenge (25-Shot)|22.44|
301
+ |HellaSwag (10-Shot) |34.11|
302
+ |MMLU (5-Shot) |25.50|
303
+ |TruthfulQA (0-shot) |43.48|
304
+ |Winogrande (5-shot) |49.33|
305
+ |GSM8k (5-shot) | 0.83|
306
+