Adding Evaluation Results (#1)
Browse files- Adding Evaluation Results (10751caed3485fec3453fc4bf9fd09723e29a60b)
README.md
CHANGED
@@ -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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| 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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