Adding Evaluation Results
#1
by
leaderboard-pr-bot
- opened
README.md
CHANGED
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---
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license: mit
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widget:
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---
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I am really enjoying this version of Cinder. More information coming. Training data similar to openhermes2.5 with some added math, STEM, and reasoning mostly from OpenOrca. As well as Cinder character specific data, a mix of RAG generated Q and A of world knowledge, STEM topics, and Cinder Character data. I suplimented the Cinder character with an abreviated Samantha dataset edited for Cinder and removed a lot of the negative responses.
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@@ -23,3 +126,17 @@ Model Overview Cinder is an AI chatbot tailored for engaging users in scientific
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Chat example from LM Studio:
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/6328952f798f8d122ce62a44/qxuCqJgUNRKq9vf7oJ3rr.png)
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---
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license: mit
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widget:
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- text: '<|system|>
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You are a helpful assistant.</s>
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<|user|>
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Can you explain to me how quantum computing works?</s>
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<|assistant|>
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'
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model-index:
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- name: Cinder-Phi-2-V1-F16-gguf
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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: AI2 Reasoning Challenge (25-Shot)
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type: ai2_arc
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config: ARC-Challenge
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split: test
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args:
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num_few_shot: 25
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metrics:
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- type: acc_norm
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value: 58.28
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Josephgflowers/Cinder-Phi-2-V1-F16-gguf
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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: HellaSwag (10-Shot)
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type: hellaswag
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split: validation
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args:
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num_few_shot: 10
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metrics:
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- type: acc_norm
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value: 74.04
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Josephgflowers/Cinder-Phi-2-V1-F16-gguf
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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 (5-Shot)
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type: cais/mmlu
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config: all
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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: 54.46
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Josephgflowers/Cinder-Phi-2-V1-F16-gguf
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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: TruthfulQA (0-shot)
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type: truthful_qa
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config: multiple_choice
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split: validation
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args:
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num_few_shot: 0
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metrics:
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- type: mc2
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value: 44.5
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Josephgflowers/Cinder-Phi-2-V1-F16-gguf
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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: Winogrande (5-shot)
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type: winogrande
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config: winogrande_xl
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split: validation
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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: 74.66
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Josephgflowers/Cinder-Phi-2-V1-F16-gguf
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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: GSM8k (5-shot)
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type: gsm8k
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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: 47.23
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Josephgflowers/Cinder-Phi-2-V1-F16-gguf
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name: Open LLM Leaderboard
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---
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I am really enjoying this version of Cinder. More information coming. Training data similar to openhermes2.5 with some added math, STEM, and reasoning mostly from OpenOrca. As well as Cinder character specific data, a mix of RAG generated Q and A of world knowledge, STEM topics, and Cinder Character data. I suplimented the Cinder character with an abreviated Samantha dataset edited for Cinder and removed a lot of the negative responses.
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Chat example from LM Studio:
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127 |
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/6328952f798f8d122ce62a44/qxuCqJgUNRKq9vf7oJ3rr.png)
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Josephgflowers__Cinder-Phi-2-V1-F16-gguf)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |58.86|
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|AI2 Reasoning Challenge (25-Shot)|58.28|
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|HellaSwag (10-Shot) |74.04|
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|MMLU (5-Shot) |54.46|
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|TruthfulQA (0-shot) |44.50|
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|Winogrande (5-shot) |74.66|
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|GSM8k (5-shot) |47.23|
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