--- license: mit library_name: transformers tags: - mergekit - merge - math - llama3 - physics - chemistry - biology - dolphin base_model: - cognitivecomputations/dolphin-2.9-llama3-8b - Weyaxi/Einstein-v6.1-Llama3-8B - Locutusque/llama-3-neural-chat-v1-8b model-index: - name: CosmicBun-8B 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: 61.86 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aloobun/CosmicBun-8B 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: 84.29 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aloobun/CosmicBun-8B 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: 65.53 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aloobun/CosmicBun-8B 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: 54.08 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aloobun/CosmicBun-8B 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: 78.85 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aloobun/CosmicBun-8B 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: 68.23 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aloobun/CosmicBun-8B name: Open LLM Leaderboard --- # model This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit). ### Merge Method This model was merged using the [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) merge method using [Locutusque/llama-3-neural-chat-v1-8b](https://huggingface.co/Locutusque/llama-3-neural-chat-v1-8b) as a base. ### Models Merged The following models were included in the merge: * [cognitivecomputations/dolphin-2.9-llama3-8b](https://huggingface.co/cognitivecomputations/dolphin-2.9-llama3-8b) * [Weyaxi/Einstein-v6.1-Llama3-8B](https://huggingface.co/Weyaxi/Einstein-v6.1-Llama3-8B) ### Configuration The following YAML configuration was used to produce this model: ```yaml base_model: Locutusque/llama-3-neural-chat-v1-8b dtype: bfloat16 merge_method: dare_ties parameters: int8_mask: 1.0 normalize: 0.0 slices: - sources: - layer_range: [0, 4] model: cognitivecomputations/dolphin-2.9-llama3-8b parameters: density: 1.0 weight: 0.6 - layer_range: [0, 4] model: Weyaxi/Einstein-v6.1-Llama3-8B parameters: density: 0.6 weight: 0.5 - layer_range: [0, 4] model: Locutusque/llama-3-neural-chat-v1-8b parameters: density: 1.0 weight: 0.5 - sources: - layer_range: [4, 8] model: cognitivecomputations/dolphin-2.9-llama3-8b parameters: density: 0.8 weight: 0.1 - layer_range: [4, 8] model: Weyaxi/Einstein-v6.1-Llama3-8B parameters: density: 1.0 weight: 0.2 - layer_range: [4, 8] model: Locutusque/llama-3-neural-chat-v1-8b parameters: density: 1.0 weight: 0.7 - sources: - layer_range: [8, 12] model: cognitivecomputations/dolphin-2.9-llama3-8b parameters: density: 0.7 weight: 0.1 - layer_range: [8, 12] model: Weyaxi/Einstein-v6.1-Llama3-8B parameters: density: 0.7 weight: 0.2 - layer_range: [8, 12] model: Locutusque/llama-3-neural-chat-v1-8b parameters: density: 0.7 weight: 0.6 - sources: - layer_range: [12, 16] model: cognitivecomputations/dolphin-2.9-llama3-8b parameters: density: 0.9 weight: 0.2 - layer_range: [12, 16] model: Weyaxi/Einstein-v6.1-Llama3-8B parameters: density: 0.6 weight: 0.6 - layer_range: [12, 16] model: Locutusque/llama-3-neural-chat-v1-8b parameters: density: 0.7 weight: 0.3 - sources: - layer_range: [16, 20] model: cognitivecomputations/dolphin-2.9-llama3-8b parameters: density: 1.0 weight: 0.2 - layer_range: [16, 20] model: Weyaxi/Einstein-v6.1-Llama3-8B parameters: density: 1.0 weight: 0.2 - layer_range: [16, 20] model: Locutusque/llama-3-neural-chat-v1-8b parameters: density: 0.9 weight: 0.4 - sources: - layer_range: [20, 24] model: cognitivecomputations/dolphin-2.9-llama3-8b parameters: density: 0.7 weight: 0.2 - layer_range: [20, 24] model: Weyaxi/Einstein-v6.1-Llama3-8B parameters: density: 0.9 weight: 0.3 - layer_range: [20, 24] model: Locutusque/llama-3-neural-chat-v1-8b parameters: density: 1.0 weight: 0.4 - sources: - layer_range: [24, 28] model: cognitivecomputations/dolphin-2.9-llama3-8b parameters: density: 1.0 weight: 0.4 - layer_range: [24, 28] model: Weyaxi/Einstein-v6.1-Llama3-8B parameters: density: 0.8 weight: 0.2 - layer_range: [24, 28] model: Locutusque/llama-3-neural-chat-v1-8b parameters: density: 0.9 weight: 0.4 - sources: - layer_range: [28, 32] model: cognitivecomputations/dolphin-2.9-llama3-8b parameters: density: 1.0 weight: 0.3 - layer_range: [28, 32] model: Weyaxi/Einstein-v6.1-Llama3-8B parameters: density: 0.9 weight: 0.2 - layer_range: [28, 32] model: Locutusque/llama-3-neural-chat-v1-8b parameters: density: 1.0 weight: 0.3 ``` # [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_aloobun__CosmicBun-8B) | Metric |Value| |---------------------------------|----:| |Avg. |68.81| |AI2 Reasoning Challenge (25-Shot)|61.86| |HellaSwag (10-Shot) |84.29| |MMLU (5-Shot) |65.53| |TruthfulQA (0-shot) |54.08| |Winogrande (5-shot) |78.85| |GSM8k (5-shot) |68.23|