Evangelion-7B

<img src="https://cdn-uploads.huggingface.co/production/uploads/63ae02ff20176b2d21669dd6/AID8texkGhpCPrxEtb2MF.png" width="300" />

🌐 Company Website 🔗 Mozaic AI Solutions

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✨ Overview

We were curious to see what happens if one uses:
$$ \text{{high-quality DPO dataset}} + \text{{merge of DPO optimized and non-DPO optimized model}} $$

The underlying model used was:
/Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp

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Dataset

Dataset: /argilla/distilabel-intel-orca-dpo-pairs

The dataset was roughly ~3000 samples but they were high quality (according to the chosen_score).
The following filters were applied to the original dataset:

dataset = dataset.filter(
    lambda r:
        r["status"] != "tie" and
        r["chosen_score"] >= 8 and
        not r["in_gsm8k_train"]
)

Chat Template

I decided to go with the ChatML which is used for OpenHermes2.5 By the way I integreated the chat template into the models tokenizer.

<|im_start|>system
{system}<|im_end|>
<|im_start|>user
{user}<|im_end|>
<|im_start|>assistant
{asistant}<|im_end|>

Open LLM Leaderboard Evaluation Results

Detailed results can be found here