
# MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp

This is the model for MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp. I used [mergekit](https://github.com/cg123/mergekit) to merge models.

# Yaml Config to reproduce

```yaml

slices:
  - sources:
      - model: meta-math/MetaMath-Mistral-7B
        layer_range: [0, 32]
      - model: PulsarAI/OpenHermes-2.5-neural-chat-v3-3-Slerp
        layer_range: [0, 32]
merge_method: slerp
base_model: mistralai/Mistral-7B-v0.1
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5 # fallback for rest of tensors
dtype: bfloat16

```
{"license": "apache-2.0", "tags": ["merge"], "model-index": [{"name": "MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp", "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": 64.59, "name": "normalized accuracy"}, {"type": "acc_norm", "value": 64.59, "name": "normalized accuracy"}], "source": {"url": "https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=PulsarAI/MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp", "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": 85.39, "name": "normalized accuracy"}, {"type": "acc_norm", "value": 85.39, "name": "normalized accuracy"}], "source": {"url": "https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=PulsarAI/MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp", "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": 64.27, "name": "accuracy"}, {"type": "acc", "value": 64.27, "name": "accuracy"}], "source": {"url": "https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=PulsarAI/MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp", "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": 55.14}, {"type": "mc2", "value": 55.14}], "source": {"url": "https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=PulsarAI/MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp", "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": 79.64, "name": "accuracy"}, {"type": "acc", "value": 79.64, "name": "accuracy"}], "source": {"url": "https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=PulsarAI/MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp", "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": 71.65, "name": "accuracy"}, {"type": "acc", "value": 71.65, "name": "accuracy"}], "source": {"url": "https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=PulsarAI/MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp", "name": "Open LLM Leaderboard"}}]}]}
transformers safetensors mistral text-generation merge license:apache-2.0 model-index autotrain_compatible endpoints_compatible text-generation-inference region:us