metadata
license: cc-by-nc-4.0
tags:
- merge
model-index:
- name: Nyxene-v1-11B
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: 67.49
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=beberik/Nyxene-v1-11B
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: 84.52
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=beberik/Nyxene-v1-11B
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: 65.12
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=beberik/Nyxene-v1-11B
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: 57.28
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=beberik/Nyxene-v1-11B
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: 79.01
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=beberik/Nyxene-v1-11B
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: 52.08
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=beberik/Nyxene-v1-11B
name: Open LLM Leaderboard
Description
This repo contains bf16 files of Nyxene-v1-11B. Same as the previous version but I used newer models and tried to repeat what I experimented with when there were older models.
Model used
- berkeley-nest/Starling-LM-7B-alpha
- openaccess-ai-collective/DPOpenHermes-7B
- fblgit/juanako-7b-UNA
- chargoddard/loyal-piano-m7
- argilla/notus-7b-v1
I added a new model because after the same action but using zephyr and dolphin the model turned out to be more creative.
Prompt template
The best one after further testing is this one:
<|system|>
Below is an instruction that describes a task. Write a response that appropriately completes the request.
<|user|>
{prompt}
<|assistant|>
The secret sauce
loyal-piano with 1% of notus :
slices:
- sources:
- model: chargoddard/loyal-piano-m7
layer_range: [0, 48]
- model: argilla/notus-7b-v1
layer_range: [0, 48]
merge_method: slerp
base_model: argilla/notus-7b-v1
parameters:
t:
- filter: lm_head
value: [0.75]
- filter: embed_tokens
value: [0.75]
- filter: self_attn
value: [0.75, 0.25]
- filter: mlp
value: [0.25, 0.75]
- filter: layernorm
value: [0.5, 0.5]
- filter: modelnorm
value: [0.75]
- value: 0.99 # fallback for rest of tensors
dtype: bfloat16
loyal-piano-juanako-11B :
slices:
- sources:
- model: fblgit/juanako-7b-UNA
layer_range: [0, 24]
- sources:
- model: chargoddard/loyal-piano-m7
layer_range: [8, 32]
merge_method: passthrough
dtype: bfloat16
Starling-DPOHermes-11B :
slices:
- sources:
- model: berkeley-nest/Starling-LM-7B-alpha
layer_range: [0, 24]
- sources:
- model: openaccess-ai-collective/DPOpenHermes-7B
layer_range: [8, 32]
merge_method: passthrough
dtype: bfloat16
Nyxene-11B :
slices:
- sources:
- model: loyal-piano-juanako-11B
layer_range: [0, 48]
- model: Starling-NeuralHermes-11B
layer_range: [0, 48]
merge_method: slerp
base_model: dolphin-juanako-11B
parameters:
t:
- filter: lm_head
value: [0.75]
- filter: embed_tokens
value: [0.75]
- filter: self_attn
value: [0.75, 0.25]
- filter: mlp
value: [0.25, 0.75]
- filter: layernorm
value: [0.5, 0.5]
- filter: modelnorm
value: [0.75]
- value: 0.5 # fallback for rest of tensors
dtype: bfloat16
I use mergekit for all the manipulation told here.
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 67.58 |
AI2 Reasoning Challenge (25-Shot) | 67.49 |
HellaSwag (10-Shot) | 84.52 |
MMLU (5-Shot) | 65.12 |
TruthfulQA (0-shot) | 57.28 |
Winogrande (5-shot) | 79.01 |
GSM8k (5-shot) | 52.08 |