Adding Evaluation Results
Browse filesThis is an automated PR created with https://huggingface.co/spaces/Weyaxi/open-llm-leaderboard-results-pr
The purpose of this PR is to add evaluation results from the Open LLM Leaderboard to your model card.
If you encounter any issues, please report them to https://huggingface.co/spaces/Weyaxi/open-llm-leaderboard-results-pr/discussions
README.md
CHANGED
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@@ -8,6 +8,109 @@ datasets:
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- wikipedia
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- Open-Orca/OpenOrca
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inference: false
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---
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# phi-2-upscaled-4B-instruct-v0.1
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@@ -174,4 +277,17 @@ print(text)
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Apache 2.0; The license of phi-2 is MIT, but the license of the orca dataset used for training is apache 2.0.
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### Caution
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-
This model was created as a personal experiment, unrelated to the organization I work for. The model may not operate correctly because separate verification was not performed. Please be careful unless it is for personal experimentation or PoC (Proof of Concept)!
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- wikipedia
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- Open-Orca/OpenOrca
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inference: false
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+
model-index:
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- name: phi-2-upscaled-4B-instruct-v0.1
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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: 22.95
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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=daekeun-ml/phi-2-upscaled-4B-instruct-v0.1
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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: 28.68
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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=daekeun-ml/phi-2-upscaled-4B-instruct-v0.1
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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: 26.8
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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=daekeun-ml/phi-2-upscaled-4B-instruct-v0.1
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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: 40.92
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=daekeun-ml/phi-2-upscaled-4B-instruct-v0.1
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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: 50.59
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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=daekeun-ml/phi-2-upscaled-4B-instruct-v0.1
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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: 0.76
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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=daekeun-ml/phi-2-upscaled-4B-instruct-v0.1
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name: Open LLM Leaderboard
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---
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# phi-2-upscaled-4B-instruct-v0.1
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Apache 2.0; The license of phi-2 is MIT, but the license of the orca dataset used for training is apache 2.0.
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### Caution
|
| 280 |
+
This model was created as a personal experiment, unrelated to the organization I work for. The model may not operate correctly because separate verification was not performed. Please be careful unless it is for personal experimentation or PoC (Proof of Concept)!
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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_daekeun-ml__phi-2-upscaled-4B-instruct-v0.1)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |28.45|
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|AI2 Reasoning Challenge (25-Shot)|22.95|
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|HellaSwag (10-Shot) |28.68|
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|MMLU (5-Shot) |26.80|
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|TruthfulQA (0-shot) |40.92|
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|Winogrande (5-shot) |50.59|
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|GSM8k (5-shot) | 0.76|
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