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Adding Evaluation Results (#1)

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- Adding Evaluation Results (076212750ff3729ec56f17c9326b0c72506a9919)


Co-authored-by: Open LLM Leaderboard PR Bot <leaderboard-pr-bot@users.noreply.huggingface.co>

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  1. README.md +119 -11
README.md CHANGED
@@ -1,14 +1,4 @@
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  ---
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- license: apache-2.0
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- datasets:
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- - Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned
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- - anthracite-org/stheno-filtered-v1.1
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- - PJMixers/hieunguyenminh_roleplay-deduped-ShareGPT
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- - Gryphe/Sonnet3.5-Charcard-Roleplay
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- - Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
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- - anthracite-org/kalo-opus-instruct-22k-no-refusal
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- - anthracite-org/nopm_claude_writing_fixed
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- - anthracite-org/kalo_opus_misc_240827
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  language:
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  - en
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  - fr
@@ -19,7 +9,112 @@ language:
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  - ru
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  - zh
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  - ja
 
 
 
 
 
 
 
 
 
 
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  pipeline_tag: text-generation
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  ![image/png](https://cdn-uploads.huggingface.co/production/uploads/64adfd277b5ff762771e4571/NGEOrcWYPDnFmvHinkXVk.png)
@@ -52,4 +147,17 @@ The v0.2 models are trained on ChatML, please use that Context and Instruct temp
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  ## Training
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  Training was done twice over 2 epochs each on two 2x [NVIDIA A6000 GPUs](https://www.nvidia.com/en-us/design-visualization/rtx-a6000/) using LoRA. A two-phased approach was used in which the base model was trained 2 epochs on RP data, the LoRA was then applied to base. Finally, the new modified base was trained 2 epochs on instruct, and the new instruct LoRA was applied to the modified base, resulting in what you see here.
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- [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
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  language:
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  - en
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  - fr
 
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  - ru
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  - zh
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  - ja
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+ license: apache-2.0
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+ datasets:
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+ - Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned
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+ - anthracite-org/stheno-filtered-v1.1
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+ - PJMixers/hieunguyenminh_roleplay-deduped-ShareGPT
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+ - Gryphe/Sonnet3.5-Charcard-Roleplay
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+ - Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
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+ - anthracite-org/kalo-opus-instruct-22k-no-refusal
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+ - anthracite-org/nopm_claude_writing_fixed
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+ - anthracite-org/kalo_opus_misc_240827
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  pipeline_tag: text-generation
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+ model-index:
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+ - name: Azure_Dusk-v0.2
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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: IFEval (0-Shot)
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+ type: HuggingFaceH4/ifeval
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+ args:
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+ num_few_shot: 0
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+ metrics:
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+ - type: inst_level_strict_acc and prompt_level_strict_acc
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+ value: 34.67
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+ name: strict accuracy
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Epiculous/Azure_Dusk-v0.2
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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: BBH (3-Shot)
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+ type: BBH
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+ args:
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+ num_few_shot: 3
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+ metrics:
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+ - type: acc_norm
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+ value: 17.4
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+ name: normalized accuracy
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Epiculous/Azure_Dusk-v0.2
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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: MATH Lvl 5 (4-Shot)
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+ type: hendrycks/competition_math
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+ args:
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+ num_few_shot: 4
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+ metrics:
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+ - type: exact_match
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+ value: 1.66
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+ name: exact match
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Epiculous/Azure_Dusk-v0.2
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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: GPQA (0-shot)
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+ type: Idavidrein/gpqa
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+ args:
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+ num_few_shot: 0
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+ metrics:
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+ - type: acc_norm
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+ value: 1.45
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+ name: acc_norm
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Epiculous/Azure_Dusk-v0.2
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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: MuSR (0-shot)
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+ type: TAUR-Lab/MuSR
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+ args:
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+ num_few_shot: 0
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+ metrics:
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+ - type: acc_norm
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+ value: 6.37
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+ name: acc_norm
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Epiculous/Azure_Dusk-v0.2
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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-PRO (5-shot)
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+ type: TIGER-Lab/MMLU-Pro
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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: 22.6
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+ name: accuracy
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Epiculous/Azure_Dusk-v0.2
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+ name: Open LLM Leaderboard
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  ---
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  ![image/png](https://cdn-uploads.huggingface.co/production/uploads/64adfd277b5ff762771e4571/NGEOrcWYPDnFmvHinkXVk.png)
 
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  ## Training
148
  Training was done twice over 2 epochs each on two 2x [NVIDIA A6000 GPUs](https://www.nvidia.com/en-us/design-visualization/rtx-a6000/) using LoRA. A two-phased approach was used in which the base model was trained 2 epochs on RP data, the LoRA was then applied to base. Finally, the new modified base was trained 2 epochs on instruct, and the new instruct LoRA was applied to the modified base, resulting in what you see here.
149
 
150
+ [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
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+ # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
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+ Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Epiculous__Azure_Dusk-v0.2)
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+
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+ | Metric |Value|
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+ |-------------------|----:|
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+ |Avg. |14.03|
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+ |IFEval (0-Shot) |34.67|
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+ |BBH (3-Shot) |17.40|
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+ |MATH Lvl 5 (4-Shot)| 1.66|
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+ |GPQA (0-shot) | 1.45|
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+ |MuSR (0-shot) | 6.37|
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+ |MMLU-PRO (5-shot) |22.60|
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+