Adding Evaluation Results
#2
by
leaderboard-pr-bot
- opened
README.md
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---
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license: apache-2.0
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datasets:
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- cognitivecomputations/dolphin
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- cognitivecomputations/dolphin-coder
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- ise-uiuc/Magicoder-OSS-Instruct-75K
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- teknium/openhermes
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- migtissera/Synthia-v1.3
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language:
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- en
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tags:
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- merge
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- fine-tuned
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base_model:
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- mistralai/Mistral-7B-Instruct-v0.2
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- ehartford/dolphin-2.2.1-mistral-7b
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@@ -26,6 +26,109 @@ base_model:
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- teknium/OpenHermes-2.5-Mistral-7B
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- Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp
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- mlabonne/NeuralHermes-2.5-Mistral-7B
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---
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# Model Description
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@@ -57,4 +160,17 @@ The model is scheduled to be fine-tuned for 3 epochs on 4 A100s using axolotl.
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# Shout-Out to OSS
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Thank you to the Open Source AI community for bringing together marvelous code frameworks and datasets.
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| 1 |
---
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+
language:
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| 3 |
+
- en
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license: apache-2.0
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+
tags:
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+
- merge
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+
- fine-tuned
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datasets:
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- cognitivecomputations/dolphin
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- cognitivecomputations/dolphin-coder
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- ise-uiuc/Magicoder-OSS-Instruct-75K
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- teknium/openhermes
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- migtissera/Synthia-v1.3
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base_model:
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- mistralai/Mistral-7B-Instruct-v0.2
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- ehartford/dolphin-2.2.1-mistral-7b
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- teknium/OpenHermes-2.5-Mistral-7B
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- Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp
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- mlabonne/NeuralHermes-2.5-Mistral-7B
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model-index:
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- name: Mistral-7B-Merge-14-v0.3-ft-step-9984
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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: 62.54
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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=EmbeddedLLM/Mistral-7B-Merge-14-v0.3-ft-step-9984
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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: 82.18
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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=EmbeddedLLM/Mistral-7B-Merge-14-v0.3-ft-step-9984
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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: 62.92
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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=EmbeddedLLM/Mistral-7B-Merge-14-v0.3-ft-step-9984
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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: 53.7
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=EmbeddedLLM/Mistral-7B-Merge-14-v0.3-ft-step-9984
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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: 75.61
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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=EmbeddedLLM/Mistral-7B-Merge-14-v0.3-ft-step-9984
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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: 25.25
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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=EmbeddedLLM/Mistral-7B-Merge-14-v0.3-ft-step-9984
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name: Open LLM Leaderboard
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---
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# Model Description
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# Shout-Out to OSS
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Thank you to the Open Source AI community for bringing together marvelous code frameworks and datasets.
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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_EmbeddedLLM__Mistral-7B-Merge-14-v0.3-ft-step-9984)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |60.37|
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|AI2 Reasoning Challenge (25-Shot)|62.54|
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|HellaSwag (10-Shot) |82.18|
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|MMLU (5-Shot) |62.92|
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|TruthfulQA (0-shot) |53.70|
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|Winogrande (5-shot) |75.61|
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|GSM8k (5-shot) |25.25|
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