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Adding Evaluation Results (#1)

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  1. README.md +117 -1
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@@ -5,6 +5,109 @@ license: apache-2.0
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  datasets:
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  - Open-Orca/SlimOrca
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  - allenai/ultrafeedback_binarized_cleaned
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  ### TeeZee/GALAXY-XB-v1.03-SFT-DPO ###
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@@ -17,4 +120,17 @@ Experiment, can DUS be taken one or more steps further?
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  ### To evaluate
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- - model performance after DPO, did it recover all initial performance loss after merge?
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  datasets:
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  - Open-Orca/SlimOrca
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  - allenai/ultrafeedback_binarized_cleaned
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+ model-index:
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+ - name: GALAXY_v03_slimorca_1_epoch_50k_DPO_1_epoch_30k
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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: 65.27
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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=TeeZee/GALAXY_v03_slimorca_1_epoch_50k_DPO_1_epoch_30k
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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: 85.62
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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=TeeZee/GALAXY_v03_slimorca_1_epoch_50k_DPO_1_epoch_30k
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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: 65.61
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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=TeeZee/GALAXY_v03_slimorca_1_epoch_50k_DPO_1_epoch_30k
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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: 53.46
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/GALAXY_v03_slimorca_1_epoch_50k_DPO_1_epoch_30k
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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: 82.72
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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=TeeZee/GALAXY_v03_slimorca_1_epoch_50k_DPO_1_epoch_30k
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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: 0.08
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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=TeeZee/GALAXY_v03_slimorca_1_epoch_50k_DPO_1_epoch_30k
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+ name: Open LLM Leaderboard
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  ---
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  ### TeeZee/GALAXY-XB-v1.03-SFT-DPO ###
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  ### To evaluate
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+ - model performance after DPO, did it recover all initial performance loss after merge?
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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_TeeZee__GALAXY_v03_slimorca_1_epoch_50k_DPO_1_epoch_30k)
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+
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+ | Metric |Value|
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+ |---------------------------------|----:|
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+ |Avg. |58.79|
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+ |AI2 Reasoning Challenge (25-Shot)|65.27|
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+ |HellaSwag (10-Shot) |85.62|
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+ |MMLU (5-Shot) |65.61|
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+ |TruthfulQA (0-shot) |53.46|
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+ |Winogrande (5-shot) |82.72|
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+ |GSM8k (5-shot) | 0.08|
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+