134 lines
4.1 KiB
Markdown
134 lines
4.1 KiB
Markdown
---
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license: apache-2.0
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model-index:
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- name: mera-mix-4x7B
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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: 72.95
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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=meraGPT/mera-mix-4x7B
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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: 89.17
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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=meraGPT/mera-mix-4x7B
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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: 64.44
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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=meraGPT/mera-mix-4x7B
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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: 77.17
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=meraGPT/mera-mix-4x7B
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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: 85.64
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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=meraGPT/mera-mix-4x7B
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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: 66.11
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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=meraGPT/mera-mix-4x7B
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name: Open LLM Leaderboard
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---
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# Model mera-mix-4x7B
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This is a mixture of experts (MoE) model that is half as large (4 experts instead of 8) as the [Mixtral-8x7B](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1)
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while been comparable to it across different benchmarks. You can use it as a drop in replacement for your Mixtral-8x7B and get much faster inference.
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mera-mix-4x7B achieves the score of 75.91 on the OpenLLM Eval and compares well with 72.7 by Mixtral-8x7B and 74.46 by Mixtral-8x22B.
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You can try the model with the [Mera Mixture Chat](https://huggingface.co/spaces/meraGPT/mera-mixture-chat).
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In addition, to the official Open LLM Leaderboard, the results on OpenLLM Eval have been validated by [others as well (76.59)](https://github.com/saucam/model_evals/tree/main?tab=readme-ov-file#model-eval-results).
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Our own initial eval is available [here (76.37)](https://gist.github.com/codelion/78f88333230801c9bbaa6fc22078d820).
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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_meraGPT__mera-mix-4x7B)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |75.91|
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|AI2 Reasoning Challenge (25-Shot)|72.95|
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|HellaSwag (10-Shot) |89.17|
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|MMLU (5-Shot) |64.44|
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|TruthfulQA (0-shot) |77.17|
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|Winogrande (5-shot) |85.64|
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|GSM8k (5-shot) |66.11|
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