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Model: 922CA/Silicon-Monika-7b Source: Original Platform
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README.md
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README.md
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---
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language:
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- en
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license: apache-2.0
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tags:
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- text-generation-inference
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- transformers
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- unsloth
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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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* Yet another model fine-tuned for Monika character from DDLC per a request
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* Base: [SanjiWatsuki/Silicon-Maid-7B](https://huggingface.co/SanjiWatsuki/Silicon-Maid-7B) (Mistral)
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* [GGUF](https://huggingface.co/922CA/Silicon-Monika-7b-gguf)
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* [Lora here](https://huggingface.co/922CA/Silicon-Monika-7b-lora)
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### USAGE
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For best results: replace "Human" and "Assistant" with "Player" and "Monika" like so:
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\nPlayer: (prompt)\nMonika:
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### HYPERPARAMS
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* Trained for 1 epoch
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* rank: 32
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* lora alpha: 32
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* lora dropout: 0
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* lr: 2e-4
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* batch size: 2
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* grad steps: 4
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This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
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[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
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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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