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--- |
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language: |
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- de |
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- en |
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license: cc-by-nc-4.0 |
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tags: |
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- merge |
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- mergekit |
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- lazymergekit |
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base_model: |
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- abideen/AlphaMonarch-dora |
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- mayflowergmbh/Wiedervereinigung-7b-dpo |
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- flemmingmiguel/NeuDist-Ro-7B |
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- ResplendentAI/Flora_DPO_7B |
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- yleo/EmertonMonarch-7B |
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- occiglot/occiglot-7b-de-en-instruct |
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- OpenPipe/mistral-ft-optimized-1227 |
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- DiscoResearch/DiscoLM_German_7b_v1 |
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- LeoLM/leo-mistral-hessianai-7b |
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- DRXD1000/Phoenix |
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- VAGOsolutions/SauerkrautLM-7b-v1-mistral |
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- malteos/hermeo-7b |
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- FelixChao/WestSeverus-7B-DPO-v2 |
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- cognitivecomputations/openchat-3.5-0106-laser |
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model-index: |
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- name: Spaetzle-v69-7b |
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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: 69.54 |
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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=cstr/Spaetzle-v69-7b |
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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: 86.77 |
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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=cstr/Spaetzle-v69-7b |
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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: 64.63 |
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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=cstr/Spaetzle-v69-7b |
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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: 65.61 |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cstr/Spaetzle-v69-7b |
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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: 81.93 |
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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=cstr/Spaetzle-v69-7b |
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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: 68.76 |
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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=cstr/Spaetzle-v69-7b |
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name: Open LLM Leaderboard |
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--- |
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# Spaetzle-v69-7b |
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This is a progressive (mostly dare-ties, but also slerp) merge with the intention of a suitable compromise for English and German local tasks. |
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There is also a 4q_k_m quantized [GGUF](https://huggingface.co/cstr/Spaetzle-v69-7b-GGUF). |
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It should work sufficiently well with ChatML prompt template (for all merged models should have seen ChatML prompts at least in DPO stage). |
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## Evaluation |
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Benchmark scores are not the possible optimum, as the model attempts a compromise with a number of parameters, like German language performance, instruction following, reasoning capabilities, robustness (so far, i did not encounter inserted tokens, e.g.), model licensing, and other criteria. |
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Nevertheless, they are not too bad: |
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It achieves (running quantized) in |
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- German EQ Bench: Score (v2_de): 62.59 (Parseable: 171.0). |
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- English EQ Bench: Score (v2): 76.43 (Parseable: 171.0). |
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| Model |AGIEval|GPT4All|TruthfulQA|Bigbench|Average| |
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|--------------------------------------------------------------|------:|------:|---------:|-------:|------:| |
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|[Spaetzle-v69-7b](https://huggingface.co/cstr/Spaetzle-v69-7b)| 44.48| 75.84| 66.15| 46.59| 58.27| |
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### AGIEval |
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| Task |Version| Metric |Value| |Stderr| |
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|------------------------------|------:|--------|----:|---|-----:| |
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|agieval_aqua_rat | 0|acc |25.98|± | 2.76| |
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| | |acc_norm|23.62|± | 2.67| |
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|agieval_logiqa_en | 0|acc |39.78|± | 1.92| |
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| | |acc_norm|39.48|± | 1.92| |
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|agieval_lsat_ar | 0|acc |23.48|± | 2.80| |
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| | |acc_norm|23.91|± | 2.82| |
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|agieval_lsat_lr | 0|acc |50.00|± | 2.22| |
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| | |acc_norm|51.76|± | 2.21| |
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|agieval_lsat_rc | 0|acc |63.94|± | 2.93| |
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| | |acc_norm|64.31|± | 2.93| |
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|agieval_sat_en | 0|acc |76.70|± | 2.95| |
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| | |acc_norm|77.67|± | 2.91| |
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|agieval_sat_en_without_passage| 0|acc |46.12|± | 3.48| |
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| | |acc_norm|44.17|± | 3.47| |
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|agieval_sat_math | 0|acc |34.09|± | 3.20| |
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| | |acc_norm|30.91|± | 3.12| |
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Average: 44.48% |
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### GPT4All |
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| Task |Version| Metric |Value| |Stderr| |
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|-------------|------:|--------|----:|---|-----:| |
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|arc_challenge| 0|acc |63.23|± | 1.41| |
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| | |acc_norm|64.16|± | 1.40| |
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|arc_easy | 0|acc |85.90|± | 0.71| |
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| | |acc_norm|82.49|± | 0.78| |
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|boolq | 1|acc |87.80|± | 0.57| |
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|hellaswag | 0|acc |67.05|± | 0.47| |
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| | |acc_norm|85.19|± | 0.35| |
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|openbookqa | 0|acc |38.40|± | 2.18| |
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| | |acc_norm|48.40|± | 2.24| |
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|piqa | 0|acc |82.75|± | 0.88| |
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| | |acc_norm|84.28|± | 0.85| |
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|winogrande | 0|acc |78.53|± | 1.15| |
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Average: 75.84% |
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### TruthfulQA |
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| Task |Version|Metric|Value| |Stderr| |
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|-------------|------:|------|----:|---|-----:| |
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|truthfulqa_mc| 1|mc1 |50.67|± | 1.75| |
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| | |mc2 |66.15|± | 1.48| |
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Average: 66.15% |
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### Bigbench |
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| Task |Version| Metric |Value| |Stderr| |
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|------------------------------------------------|------:|---------------------|----:|---|-----:| |
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|bigbench_causal_judgement | 0|multiple_choice_grade|56.84|± | 3.60| |
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|bigbench_date_understanding | 0|multiple_choice_grade|66.67|± | 2.46| |
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|bigbench_disambiguation_qa | 0|multiple_choice_grade|40.70|± | 3.06| |
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|bigbench_geometric_shapes | 0|multiple_choice_grade|24.79|± | 2.28| |
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| | |exact_str_match |10.58|± | 1.63| |
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|bigbench_logical_deduction_five_objects | 0|multiple_choice_grade|31.00|± | 2.07| |
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|bigbench_logical_deduction_seven_objects | 0|multiple_choice_grade|23.00|± | 1.59| |
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|bigbench_logical_deduction_three_objects | 0|multiple_choice_grade|58.00|± | 2.85| |
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|bigbench_movie_recommendation | 0|multiple_choice_grade|45.80|± | 2.23| |
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|bigbench_navigate | 0|multiple_choice_grade|52.10|± | 1.58| |
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|bigbench_reasoning_about_colored_objects | 0|multiple_choice_grade|69.55|± | 1.03| |
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|bigbench_ruin_names | 0|multiple_choice_grade|48.88|± | 2.36| |
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|bigbench_salient_translation_error_detection | 0|multiple_choice_grade|30.96|± | 1.46| |
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|bigbench_snarks | 0|multiple_choice_grade|73.48|± | 3.29| |
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|bigbench_sports_understanding | 0|multiple_choice_grade|74.14|± | 1.40| |
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|bigbench_temporal_sequences | 0|multiple_choice_grade|42.70|± | 1.56| |
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|bigbench_tracking_shuffled_objects_five_objects | 0|multiple_choice_grade|23.60|± | 1.20| |
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|bigbench_tracking_shuffled_objects_seven_objects| 0|multiple_choice_grade|18.40|± | 0.93| |
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|bigbench_tracking_shuffled_objects_three_objects| 0|multiple_choice_grade|58.00|± | 2.85| |
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Average: 46.59% |
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Average score: 58.27% |
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## 🧩 Merge Configuration |
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Spaetzle-v69-7b is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing): |
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* [abideen/AlphaMonarch-dora](https://huggingface.co/abideen/AlphaMonarch-dora) |
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* [cstr/Spaetzle-v68-7b](https://huggingface.co/cstr/Spaetzle-v68-7b) |
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The merge tree in total involves the following original models: |
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- [abideen/AlphaMonarch-dora](https://huggingface.co/abideen/AlphaMonarch-dora) |
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- [mayflowergmbh/Wiedervereinigung-7b-dpo](https://huggingface.co/mayflowergmbh/Wiedervereinigung-7b-dpo) |
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- [flemmingmiguel/NeuDist-Ro-7B](https://huggingface.co/flemmingmiguel/NeuDist-Ro-7B) |
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- [ResplendentAI/Flora_DPO_7B](https://huggingface.co/ResplendentAI/Flora_DPO_7B) |
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- [yleo/EmertonMonarch-7B](https://huggingface.co/yleo/EmertonMonarch-7B) |
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- [occiglot/occiglot-7b-de-en-instruct](https://huggingface.co/occiglot/occiglot-7b-de-en-instruct) |
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- [OpenPipe/mistral-ft-optimized-1227](https://huggingface.co/OpenPipe/mistral-ft-optimized-1227) |
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- [yleo/EmertonMonarch-7B](https://huggingface.co/yleo/EmertonMonarch-7B) |
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- [DiscoResearch/DiscoLM_German_7b_v1](https://huggingface.co/DiscoResearch/DiscoLM_German_7b_v1) |
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- [LeoLM/leo-mistral-hessianai-7b](https://huggingface.co/LeoLM/leo-mistral-hessianai-7b) |
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- [DRXD1000/Phoenix](https://huggingface.co/DRXD1000/Phoenix) |
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- [VAGOsolutions/SauerkrautLM-7b-v1-mistral](https://huggingface.co/VAGOsolutions/SauerkrautLM-7b-v1-mistral) |
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- [malteos/hermeo-7b](https://huggingface.co/malteos/hermeo-7b) |
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- [FelixChao/WestSeverus-7B-DPO-v2](https://huggingface.co/FelixChao/WestSeverus-7B-DPO-v2) |
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- [cognitivecomputations/openchat-3.5-0106-laser](https://huggingface.co/cognitivecomputations/openchat-3.5-0106-laser) |
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For this last merge: |
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```yaml |
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models: |
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- model: cstr/Spaetzle-v68-7b |
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# no parameters necessary for base model |
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- model: abideen/AlphaMonarch-dora |
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parameters: |
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density: 0.60 |
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weight: 0.30 |
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merge_method: dare_ties |
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base_model: cstr/Spaetzle-v68-7b |
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parameters: |
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int8_mask: true |
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dtype: bfloat16 |
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random_seed: 0 |
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tokenizer_source: base |
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``` |
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## 💻 Usage |
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```python |
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!pip install -qU transformers accelerate |
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from transformers import AutoTokenizer |
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import transformers |
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import torch |
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model = "cstr/Spaetzle-v69-7b" |
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messages = [{"role": "user", "content": "What is a large language model?"}] |
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tokenizer = AutoTokenizer.from_pretrained(model) |
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prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) |
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pipeline = transformers.pipeline( |
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"text-generation", |
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model=model, |
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torch_dtype=torch.float16, |
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device_map="auto", |
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) |
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outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95) |
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print(outputs[0]["generated_text"]) |
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``` |
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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_cstr__Spaetzle-v69-7b) |
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| Metric |Value| |
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|---------------------------------|----:| |
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|Avg. |72.87| |
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|AI2 Reasoning Challenge (25-Shot)|69.54| |
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|HellaSwag (10-Shot) |86.77| |
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|MMLU (5-Shot) |64.63| |
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|TruthfulQA (0-shot) |65.61| |
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|Winogrande (5-shot) |81.93| |
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|GSM8k (5-shot) |68.76| |
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