File size: 4,558 Bytes
6e021c8 5bf6671 83cb42d 5bf6671 e35b651 83cb42d af57a4d 83cb42d 6e021c8 5bf6671 362ef1e 5bf6671 17c8d4c 5bf6671 17c8d4c 83cb42d |
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 |
---
language:
- en
license: cc-by-nc-4.0
tags:
- Math
- merge
datasets:
- meta-math/MetaMathQA
pipeline_tag: text-generation
base_model:
- Q-bert/MetaMath-Cybertron
- berkeley-nest/Starling-LM-7B-alpha
model-index:
- name: MetaMath-Cybertron-Starling
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: AI2 Reasoning Challenge (25-Shot)
type: ai2_arc
config: ARC-Challenge
split: test
args:
num_few_shot: 25
metrics:
- type: acc_norm
value: 67.75
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Q-bert/MetaMath-Cybertron-Starling
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: HellaSwag (10-Shot)
type: hellaswag
split: validation
args:
num_few_shot: 10
metrics:
- type: acc_norm
value: 86.23
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Q-bert/MetaMath-Cybertron-Starling
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU (5-Shot)
type: cais/mmlu
config: all
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 65.24
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Q-bert/MetaMath-Cybertron-Starling
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: TruthfulQA (0-shot)
type: truthful_qa
config: multiple_choice
split: validation
args:
num_few_shot: 0
metrics:
- type: mc2
value: 55.94
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Q-bert/MetaMath-Cybertron-Starling
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: Winogrande (5-shot)
type: winogrande
config: winogrande_xl
split: validation
args:
num_few_shot: 5
metrics:
- type: acc
value: 81.45
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Q-bert/MetaMath-Cybertron-Starling
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GSM8k (5-shot)
type: gsm8k
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 71.49
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Q-bert/MetaMath-Cybertron-Starling
name: Open LLM Leaderboard
---
## MetaMath-Cybertron-Starling
Merge [Q-bert/MetaMath-Cybertron](https://huggingface.co/Q-bert/MetaMath-Cybertron) and [berkeley-nest/Starling-LM-7B-alpha](https://huggingface.co/berkeley-nest/Starling-LM-7B-alpha) using slerp merge.
You can use ChatML format.
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [Here](https://huggingface.co/datasets/open-llm-leaderboard/results/blob/main/Q-bert/MetaMath-Cybertron-Starling/results_2023-12-07T21-59-56.458563.json)
| Metric | Value |
|-----------------------|---------------------------|
| Avg. | 71.35 |
| ARC (25-shot) | 67.75 |
| HellaSwag (10-shot) | 86.23 |
| MMLU (5-shot) | 65.24 |
| TruthfulQA (0-shot) | 55.94 |
| Winogrande (5-shot) | 81.45 |
| GSM8K (5-shot) | 71.49 |
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Q-bert__MetaMath-Cybertron-Starling)
| Metric |Value|
|---------------------------------|----:|
|Avg. |71.35|
|AI2 Reasoning Challenge (25-Shot)|67.75|
|HellaSwag (10-Shot) |86.23|
|MMLU (5-Shot) |65.24|
|TruthfulQA (0-shot) |55.94|
|Winogrande (5-shot) |81.45|
|GSM8k (5-shot) |71.49|
|