metadata
base_model:
- unsloth/Meta-Llama-3.1-8B
- unsloth/Meta-Llama-3.1-8B-Instruct
library_name: transformers
tags:
- mergekit
- merge
model-index:
- name: Meta-Llama-3.1-8B-Instruct-TIES
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: 54.24
name: strict accuracy
source:
url: >-
https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=T145/Meta-Llama-3.1-8B-Instruct-TIES
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: 29.77
name: normalized accuracy
source:
url: >-
https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=T145/Meta-Llama-3.1-8B-Instruct-TIES
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: 20.02
name: exact match
source:
url: >-
https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=T145/Meta-Llama-3.1-8B-Instruct-TIES
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: 5.93
name: acc_norm
source:
url: >-
https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=T145/Meta-Llama-3.1-8B-Instruct-TIES
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: 8.04
name: acc_norm
source:
url: >-
https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=T145/Meta-Llama-3.1-8B-Instruct-TIES
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: 30.89
name: accuracy
source:
url: >-
https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=T145/Meta-Llama-3.1-8B-Instruct-TIES
name: Open LLM Leaderboard
Rombo Llama Merge Test
This merge provides a baseline for performance when the instruct model is merged on the base. It follows Rombodawg's merge method on Qwen models, and should prove if it works with Llama models. Running hypothesis is that the IFEval benchmark will get nuked. A success will be little to no performance change over the vanilla instruct model.
Merge Details
Merge Method
This model was merged using the TIES merge method using unsloth/Meta-Llama-3.1-8B as a base.
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
base_model: unsloth/Meta-Llama-3.1-8B
dtype: bfloat16
merge_method: ties
parameters:
density: 1.0
weight: 1.0
slices:
- sources:
- layer_range: [0, 32]
model: unsloth/Meta-Llama-3.1-8B-Instruct
parameters:
density: 1.0
weight: 1.0
- layer_range: [0, 32]
model: unsloth/Meta-Llama-3.1-8B
tokenizer_source: unsloth/Meta-Llama-3.1-8B-Instruct
Open LLM Leaderboard Evaluation Results
Detailed results can be found here! Summarized results can be found here!
| Metric | % Value |
|---|---|
| Avg. | 24.81 |
| IFEval (0-Shot) | 54.24 |
| BBH (3-Shot) | 29.77 |
| MATH Lvl 5 (4-Shot) | 20.02 |
| GPQA (0-shot) | 5.93 |
| MuSR (0-shot) | 8.04 |
| MMLU-PRO (5-shot) | 30.89 |