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---
language:
- en
- zh
license: apache-2.0
tags:
- Mixtral
- openbmb/MiniCPM-2B-sft-bf16-llama-format
- MoE
- merge
- mergekit
- moerge
- MiniCPM
base_model:
- openbmb/MiniCPM-2B-sft-bf16-llama-format
model-index:
- name: MoECPM-Untrained-4x2b
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: 46.76
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Inv/MoECPM-Untrained-4x2b
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: 72.58
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Inv/MoECPM-Untrained-4x2b
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: 53.21
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Inv/MoECPM-Untrained-4x2b
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: 38.41
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Inv/MoECPM-Untrained-4x2b
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: 65.51
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Inv/MoECPM-Untrained-4x2b
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: 44.58
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Inv/MoECPM-Untrained-4x2b
name: Open LLM Leaderboard
---
# MoECPM Untrained 4x2b
## Model Details
### Model Description
A MoE model out of 4 MiniCPM-2B-sft models. Intended to be trained. This version probably does not perform well (if it works at all, lol. I haven't tested it).
## Uses
- Training
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
# [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_Inv__MoECPM-Untrained-4x2b)
| Metric |Value|
|---------------------------------|----:|
|Avg. |53.51|
|AI2 Reasoning Challenge (25-Shot)|46.76|
|HellaSwag (10-Shot) |72.58|
|MMLU (5-Shot) |53.21|
|TruthfulQA (0-shot) |38.41|
|Winogrande (5-shot) |65.51|
|GSM8k (5-shot) |44.58|
|