Just a test of a very high density DARE ties merge, for benchmarking on the open llm leaderboard.
You probably shouldn't use this model, use this one instead: https://huggingface.co/brucethemoose/CaPlatTessDolXaBoros-Yi-34B-200K-DARE-Ties-HighDensity
mergekit config:
models:
- model: /home/alpha/Storage/Models/Raw/chargoddard_Yi-34B-200K-Llama
# no parameters necessary for base model
- model: /home/alpha/Storage/Models/Raw/migtissera_Tess-34B-v1.4
parameters:
weight: 0.19
density: 0.83
- model: /home/alpha//Storage/Models/Raw/bhenrym14_airoboros-3_1-yi-34b-200k
parameters:
weight: 0.14
density: 0.6
- model: /home/alpha/Storage/Models/Raw/Nous-Capybara-34B
parameters:
weight: 0.19
density: 0.83
- model: /home/alpha/Storage/Models/Raw/kyujinpy_PlatYi-34B-200K-Q
parameters:
weight: 0.14
density: 0.6
- model: /home/alpha/FastModels/ehartford_dolphin-2.2-yi-34b-200k
parameters:
weight: 0.19
density: 0.83
- model: /home/alpha/FastModels/fblgit_una-xaberius-34b-v1beta
parameters:
weight: 0.15
density: 0.08
merge_method: dare_ties
base_model: /home/alpha/Storage/Models/Raw/chargoddard_Yi-34B-200K-Llama
parameters:
int8_mask: true
dtype: bfloat16
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 71.57 |
| AI2 Reasoning Challenge (25-Shot) | 66.89 |
| HellaSwag (10-Shot) | 85.69 |
| MMLU (5-Shot) | 77.35 |
| TruthfulQA (0-shot) | 57.63 |
| Winogrande (5-shot) | 82.00 |
| GSM8k (5-shot) | 59.82 |