Adding Evaluation Results (#1)
Browse files- Adding Evaluation Results (63b39a1c5ee1e5ed44f2ff839804824bdd20fe3d)
Co-authored-by: Open LLM Leaderboard PR Bot <[email protected]>
README.md
CHANGED
@@ -9,9 +9,112 @@ tags:
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- mistral
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- trl
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- sft
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base_model: SanjiWatsuki/Silicon-Maid-7B
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datasets:
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- 922-CA/MoCha_v1
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---
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# Silicon-Monika-7b
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@@ -36,4 +139,17 @@ This mistral model was trained 2x faster with [Unsloth](https://github.com/unslo
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### WARNINGS AND DISCLAIMERS
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This model is meant to closely reflect the characteristics of Monika. Despite this, there is always the chance that "Monika" will hallucinate and get information about herself wrong or act out of character (for example, in testing she usually knows her own club and its members, her game, and even her height and favorite ice cream flavor, but may still get her eye color wrong or mistake her developer as being a member of her club).
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-
Finally, this model is not guaranteed to output aligned or safe outputs, use at your own risk.
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- mistral
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- trl
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- sft
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datasets:
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- 922-CA/MoCha_v1
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base_model: SanjiWatsuki/Silicon-Maid-7B
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model-index:
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- name: Silicon-Monika-7b
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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: 63.14
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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=922CA/Silicon-Monika-7b
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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: 82.64
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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=922CA/Silicon-Monika-7b
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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: 62.67
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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=922CA/Silicon-Monika-7b
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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: 52.14
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=922CA/Silicon-Monika-7b
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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: 78.22
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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=922CA/Silicon-Monika-7b
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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: 60.5
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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=922CA/Silicon-Monika-7b
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name: Open LLM Leaderboard
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---
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# Silicon-Monika-7b
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### WARNINGS AND DISCLAIMERS
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This model is meant to closely reflect the characteristics of Monika. Despite this, there is always the chance that "Monika" will hallucinate and get information about herself wrong or act out of character (for example, in testing she usually knows her own club and its members, her game, and even her height and favorite ice cream flavor, but may still get her eye color wrong or mistake her developer as being a member of her club).
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Finally, this model is not guaranteed to output aligned or safe outputs, use at your own risk.
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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_922CA__Silicon-Monika-7b)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |66.55|
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|AI2 Reasoning Challenge (25-Shot)|63.14|
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|HellaSwag (10-Shot) |82.64|
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|MMLU (5-Shot) |62.67|
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|TruthfulQA (0-shot) |52.14|
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|Winogrande (5-shot) |78.22|
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|GSM8k (5-shot) |60.50|
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