152 lines
5.4 KiB
Markdown
152 lines
5.4 KiB
Markdown
---
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datasets:
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- agentlans/crash-course
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base_model:
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- google/gemma-2-9b-it
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- FuseAI/FuseChat-Gemma-2-9B-Instruct
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- jsgreenawalt/gemma-2-9B-it-advanced-v2.1
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tags:
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- gemma2
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language:
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- en
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pipeline_tag: text-generation
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license: gemma
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model-index:
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- name: Gemma2-9B-AdvancedFuse
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results:
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: IFEval (0-Shot)
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type: wis-k/instruction-following-eval
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split: train
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args:
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num_few_shot: 0
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metrics:
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- type: inst_level_strict_acc and prompt_level_strict_acc
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value: 15.43
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name: averaged accuracy
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FGemma2-9B-AdvancedFuse
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: BBH (3-Shot)
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type: SaylorTwift/bbh
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split: test
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args:
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num_few_shot: 3
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metrics:
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- type: acc_norm
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value: 40.52
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FGemma2-9B-AdvancedFuse
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MATH Lvl 5 (4-Shot)
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type: lighteval/MATH-Hard
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split: test
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args:
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num_few_shot: 4
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metrics:
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- type: exact_match
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value: 7.55
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name: exact match
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FGemma2-9B-AdvancedFuse
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: GPQA (0-shot)
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type: Idavidrein/gpqa
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split: train
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args:
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num_few_shot: 0
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metrics:
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- type: acc_norm
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value: 11.3
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name: acc_norm
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FGemma2-9B-AdvancedFuse
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MuSR (0-shot)
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type: TAUR-Lab/MuSR
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args:
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num_few_shot: 0
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metrics:
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- type: acc_norm
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value: 11.99
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name: acc_norm
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FGemma2-9B-AdvancedFuse
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MMLU-PRO (5-shot)
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type: TIGER-Lab/MMLU-Pro
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config: main
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 33.34
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name: accuracy
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FGemma2-9B-AdvancedFuse
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name: Open LLM Leaderboard
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---
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# Gemma2-9B-AdvancedFuse
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Gemma2-9B-AdvancedFuse is an experimental, open-source large language model (LLM) with 9 billion parameters.
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It aims to combine the strengths of [FuseAI/FuseChat-Gemma-2-9B-Instruct](https://huggingface.co/fuseai/fusechat-gemma-2-9b-instruct) and
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[jsgreenawalt/gemma-2-9B-it-advanced-v2.1](https://huggingface.co/jsgreenawalt/gemma-2-9b-it-advanced-v2.1) through additive linear merging,
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further fine-tuned on a 12K row dataset from [agentlans/crash-course](https://huggingface.co/datasets/agentlans/crash-course)
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for enhanced chat and instruct performance, including math and multilingual prompts.
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## Capabilities
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- **Text Generation:** Generates coherent emails, summaries, and notes. This model card was primarily generated by the model itself.
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- **Instruction Following:** Demonstrates strong ability to understand and execute instructions in conversational settings.
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- **Roleplaying:** Can engage in third-person narrative roleplay but may exhibit common GPT expressions or clichés.
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### Limitations
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As with most large language models:
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- **Factual Errors:** May generate incorrect or outdated information due to data biases.
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- **Mathematical Operations:** Struggles with mathematical calculations requiring symbolic reasoning despite its finetuning data.
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- **Handling Unsafe Input:** May generate unsafe, biased, or malicious content if provided inappropriate input. Careful prompt engineering is recommended.
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### Model Usage Guidelines
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1. Use clear and specific instructions for optimal performance.
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2. Verify generated outputs for factual accuracy when critical information is involved.
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3. Avoid providing inputs that could lead to harmful or unethical responses.
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4. Consider using human review, especially in high-stakes applications.
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/agentlans__Gemma2-9B-AdvancedFuse-details)!
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Summarized results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/contents/viewer/default/train?q=agentlans%2FGemma2-9B-AdvancedFuse&sort[column]=Average%20%E2%AC%86%EF%B8%8F&sort[direction]=desc)!
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| Metric |Value (%)|
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|-------------------|--------:|
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|**Average** | 20.02|
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|IFEval (0-Shot) | 15.43|
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|BBH (3-Shot) | 40.52|
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|MATH Lvl 5 (4-Shot)| 7.55|
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|GPQA (0-shot) | 11.30|
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|MuSR (0-shot) | 11.99|
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|MMLU-PRO (5-shot) | 33.34|
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