library_name: transformers
tags:
- mergekit
- merge
base_model:
- Qwen/Qwen2.5-14B-Instruct
- Lambent/qwen2.5-lumen-rebased-14B
model-index:
- name: qwen2.5-reinstruct-alternate-lumen-14B
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: IFEval (0-Shot)
type: HuggingFaceH4/ifeval
args:
num_few_shot: 0
metrics:
- type: inst_level_strict_acc and prompt_level_strict_acc
value: 47.94
name: strict accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Lambent/qwen2.5-reinstruct-alternate-lumen-14B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: BBH (3-Shot)
type: BBH
args:
num_few_shot: 3
metrics:
- type: acc_norm
value: 48.99
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Lambent/qwen2.5-reinstruct-alternate-lumen-14B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MATH Lvl 5 (4-Shot)
type: hendrycks/competition_math
args:
num_few_shot: 4
metrics:
- type: exact_match
value: 19.79
name: exact match
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Lambent/qwen2.5-reinstruct-alternate-lumen-14B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GPQA (0-shot)
type: Idavidrein/gpqa
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 16.89
name: acc_norm
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Lambent/qwen2.5-reinstruct-alternate-lumen-14B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MuSR (0-shot)
type: TAUR-Lab/MuSR
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 19.62
name: acc_norm
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Lambent/qwen2.5-reinstruct-alternate-lumen-14B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU-PRO (5-shot)
type: TIGER-Lab/MMLU-Pro
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 48.76
name: accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Lambent/qwen2.5-reinstruct-alternate-lumen-14B
name: Open LLM Leaderboard
qwenreinstruct
This is a merge of pre-trained language models created using mergekit.
Merge Details
Extracted an approximate LoRA of v000000/Qwen2.5-Lumen-14B, rank 128 difference between that and Instruct, and first applied this to Lambent/qwen2.5-14B-alternate-instruct-slerp which had no issues with EQ-Bench.
Then, here, re-applied a density and weight of original Instruct which in previous merges gave me no issues with EQ-Bench.
This one has EQ-Bench of 77.6713 and no "emotions don't match reference error" (if possibly still one not parsed). This is similar to Lumen and original Instruct and slightly exceeds both (within margin of error). My hope is that it has healed Instruct somewhat and regained its intelligence.
Merge Method
This model was merged using the della merge method using Lambent/qwen2.5-lumen-rebased-14B as a base.
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
models:
- model: Qwen/Qwen2.5-14B-Instruct
parameters:
weight: 0.3
density: 0.4
merge_method: della
base_model: Lambent/qwen2.5-lumen-rebased-14B
parameters:
epsilon: 0.05
lambda: 1
dtype: bfloat16
tokenizer_source: base
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 33.66 |
| IFEval (0-Shot) | 47.94 |
| BBH (3-Shot) | 48.99 |
| MATH Lvl 5 (4-Shot) | 19.79 |
| GPQA (0-shot) | 16.89 |
| MuSR (0-shot) | 19.62 |
| MMLU-PRO (5-shot) | 48.76 |