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Adding Evaluation Results (#1)
Browse files- Adding Evaluation Results (a164f4263a4fd286f62d0b146c471f0cf850e571)
Co-authored-by: Open LLM Leaderboard PR Bot <[email protected]>
README.md
CHANGED
@@ -7,6 +7,109 @@ tags:
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base_model:
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- shadowml/BeagleSempra-7B
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- shadowml/WestBeagle-7B
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---
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# BeagSake-7B
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@@ -59,4 +162,17 @@ pipeline = transformers.pipeline(
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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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base_model:
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- shadowml/BeagleSempra-7B
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- shadowml/WestBeagle-7B
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model-index:
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- name: BeagSake-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: 72.44
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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=shadowml/BeagSake-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: 88.39
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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=shadowml/BeagSake-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: 65.23
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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=shadowml/BeagSake-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: 72.27
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=shadowml/BeagSake-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: 82.16
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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=shadowml/BeagSake-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: 71.8
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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=shadowml/BeagSake-7B
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name: Open LLM Leaderboard
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---
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# BeagSake-7B
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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_shadowml__BeagSake-7B)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |75.38|
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|AI2 Reasoning Challenge (25-Shot)|72.44|
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|HellaSwag (10-Shot) |88.39|
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|MMLU (5-Shot) |65.23|
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|TruthfulQA (0-shot) |72.27|
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|Winogrande (5-shot) |82.16|
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|GSM8k (5-shot) |71.80|
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