--- language: - en license: cc-by-nc-4.0 model-index: - name: Iambe-20b-DARE-v2 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: 62.8 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=athirdpath/Iambe-20b-DARE-v2 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: 84.53 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=athirdpath/Iambe-20b-DARE-v2 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: 60.45 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=athirdpath/Iambe-20b-DARE-v2 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: 53.85 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=athirdpath/Iambe-20b-DARE-v2 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: 77.03 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=athirdpath/Iambe-20b-DARE-v2 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: 33.28 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=athirdpath/Iambe-20b-DARE-v2 name: Open LLM Leaderboard ---

Strange quirk: This model seems to need a context size of EXACTLY 4096 ONLY. I'm assuming this is a dares_ties effect?

Iambe-20b-DARE-v2

Alpaca prompt formatting

### Description Named after a charming daughter of Echo and Pan in Greek myth, Iambe-20b-DARE-v2 is an improved [DARE](https://github.com/yule-BUAA/MergeLM) merge building on my recent experiments. Iambe is intended to have the best realistically possible understanding of anatomy and of a scene's state for a 20b merge, while remaining personable and authentic in "voice". ### Update Methodology Noromaid and the general "no-robots" vibe didn't come through like I'd hoped in v1. My hypothesis is that the "soul" MythoMax and Noromaid have is probably distributed widely over many low-value deltas, due to the "ephemeral" nature of such a thing. My old base model was likely giving DARE conniption fits, so I replaced that with a truly vanilla 20b base model. CleverGirl was updated to the DARE version, as Sir Hillary said, simply because it was there. Without a large base of dare_ties models to compare to, I'm basically feeling my way through this intuitively, so here's to good results! ### Recipe merge_method: dare_ties - base_model: athirdpath/BigLlama-20b-v1.1 - model: Noromaid-20b-v0.1.1 weight: 0.38 / density: 0.60 - model: athirdpath/athirdpath/Eileithyia-20b weight: 0.22 / density: 0.40 - model: athirdpath/CleverGirl-20b-Blended-v1.1-DARE weight: 0.40 / density: 0.33 int8_mask: true dtype: bfloat16 # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_athirdpath__Iambe-20b-DARE-v2) | Metric |Value| |---------------------------------|----:| |Avg. |61.99| |AI2 Reasoning Challenge (25-Shot)|62.80| |HellaSwag (10-Shot) |84.53| |MMLU (5-Shot) |60.45| |TruthfulQA (0-shot) |53.85| |Winogrande (5-shot) |77.03| |GSM8k (5-shot) |33.28|