license: other
library_name: transformers
tags:
- mergekit
- merge
base_model:
- unsloth/Mistral-Small-Instruct-2409
license_name: mrl
license_link: https://mistral.ai/licenses/MRL-0.1.md
model-index:
- name: MS-Meadowlark-22B
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: 66.97
name: strict accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=allura-org/MS-Meadowlark-22B
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: 30.3
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=allura-org/MS-Meadowlark-22B
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: 14.12
name: exact match
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=allura-org/MS-Meadowlark-22B
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: 10.07
name: acc_norm
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=allura-org/MS-Meadowlark-22B
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: 5.53
name: acc_norm
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=allura-org/MS-Meadowlark-22B
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: 31.37
name: accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=allura-org/MS-Meadowlark-22B
name: Open LLM Leaderboard
MS-Meadowlark-22B
GGUF models: https://huggingface.co/mradermacher/MS-Meadowlark-22B-GGUF/
EXL2 models: https://huggingface.co/CalamitousFelicitousness/MS-Meadowlark-22B-exl2
Datasets used in this model:
- Dampfinchen/Creative_Writing_Multiturn at 16k
- Fizzarolli/rosier-dataset + Alfitaria/body-inflation-org at 16k
- ToastyPigeon/SpringDragon at 8k
Each dataset was trained separately onto Mistral Small Instruct, and then the component models were merged along with nbeerbower/Mistral-Small-Gutenberg-Doppel-22B to create Meadowlark.
I tried different blends of the component models, and this one seems to be the most stable while retaining creativity and unpredictability added by the trained data.
Instruct Format
Rosier/bodyinf and SpringDragon were trained in completion format. This model should work with Kobold Lite in Adventure Mode and Story Mode.
Creative_Writing_Multiturn and Gutenberg-Doppel were trained using the official instruct format of Mistral Small Instruct:
<s>[INST] {User message}[/INST] {Assistant response}</s>
This is the Mistral Small V2&V3 preset in SillyTavern and Kobold Lite.
For SillyTavern in particular I've had better luck getting good output from Mistral Small using a custom instruct template that formats the assembled context as a single user turn. This prevents SillyTavern from confusing the model by assembling user/assistant turns in a nonstandard way. Note: This preset is not compatible with Stepped Thinking, use the Mistral V2&V3 preset for that.
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 26.39 |
| IFEval (0-Shot) | 66.97 |
| BBH (3-Shot) | 30.30 |
| MATH Lvl 5 (4-Shot) | 14.12 |
| GPQA (0-shot) | 10.07 |
| MuSR (0-shot) | 5.53 |
| MMLU-PRO (5-shot) | 31.37 |