metadata
license: apache-2.0
tags:
- merge
model-index:
- name: MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp
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: 64.59
name: normalized accuracy
- type: acc_norm
value: 64.59
name: normalized accuracy
- type: acc_norm
value: 64.59
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=PulsarAI/MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp
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: 85.39
name: normalized accuracy
- type: acc_norm
value: 85.39
name: normalized accuracy
- type: acc_norm
value: 85.37
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=PulsarAI/MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp
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: 64.27
name: accuracy
- type: acc
value: 64.27
name: accuracy
- type: acc
value: 64.29
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=PulsarAI/MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp
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: 55.14
- type: mc2
value: 55.14
- type: mc2
value: 55.14
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=PulsarAI/MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp
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: 79.64
name: accuracy
- type: acc
value: 79.64
name: accuracy
- type: acc
value: 79.08
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=PulsarAI/MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp
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: 71.65
name: accuracy
- type: acc
value: 71.65
name: accuracy
- type: acc
value: 71.04
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=PulsarAI/MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp
name: Open LLM Leaderboard
MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp
This is the model for MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp. I used mergekit to merge models.
Yaml Config to reproduce
slices:
- sources:
- model: meta-math/MetaMath-Mistral-7B
layer_range: [0, 32]
- model: PulsarAI/OpenHermes-2.5-neural-chat-v3-3-Slerp
layer_range: [0, 32]
merge_method: slerp
base_model: mistralai/Mistral-7B-v0.1
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5 # fallback for rest of tensors
dtype: bfloat16
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 69.92 |
AI2 Reasoning Challenge (25-Shot) | 64.59 |
HellaSwag (10-Shot) | 85.37 |
MMLU (5-Shot) | 64.29 |
TruthfulQA (0-shot) | 55.14 |
Winogrande (5-shot) | 79.08 |
GSM8k (5-shot) | 71.04 |