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Adding Evaluation Results

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This 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

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  1. README.md +122 -12
README.md CHANGED
@@ -1,8 +1,8 @@
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  ---
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  license: apache-2.0
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- base_model: BEE-spoke-data/smol_llama-220M-GQA
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  datasets:
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  - VMware/open-instruct
 
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  inference:
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  parameters:
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  do_sample: true
@@ -16,17 +16,114 @@ inference:
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  no_repeat_ngram_size: 6
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  epsilon_cutoff: 0.0006
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  widget:
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- - text: >
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- Below is an instruction that describes a task, paired with an input that
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- provides further context. Write a response that appropriately completes the
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- request.
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-
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- ### Instruction:
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-
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- Write an ode to Chipotle burritos.
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-
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- ### Response:
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  example_title: burritos
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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@@ -83,4 +180,17 @@ Feel free to experiment with the parameters using the model in Python and let us
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  This was trained on `VMware/open-instruct` so do whatever you want, provided it falls under the base apache-2.0 license :)
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  license: apache-2.0
 
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  datasets:
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  - VMware/open-instruct
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+ base_model: BEE-spoke-data/smol_llama-220M-GQA
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  inference:
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  parameters:
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  do_sample: true
 
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  no_repeat_ngram_size: 6
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  epsilon_cutoff: 0.0006
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  widget:
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+ - text: "Below is an instruction that describes a task, paired with an input that\
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+ \ provides further context. Write a response that appropriately completes the\
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+ \ request. \n \n### Instruction: \n \nWrite an ode to Chipotle burritos.\
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+ \ \n \n### Response: \n"
 
 
 
 
 
 
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  example_title: burritos
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+ model-index:
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+ - name: smol_llama-220M-open_instruct
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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: 25.0
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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=BEE-spoke-data/smol_llama-220M-open_instruct
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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: 29.71
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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=BEE-spoke-data/smol_llama-220M-open_instruct
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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: 26.11
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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=BEE-spoke-data/smol_llama-220M-open_instruct
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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: 44.06
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=BEE-spoke-data/smol_llama-220M-open_instruct
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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: 50.28
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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=BEE-spoke-data/smol_llama-220M-open_instruct
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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: 0.0
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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=BEE-spoke-data/smol_llama-220M-open_instruct
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+ name: Open LLM Leaderboard
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  ---
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  This was trained on `VMware/open-instruct` so do whatever you want, provided it falls under the base apache-2.0 license :)
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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_BEE-spoke-data__smol_llama-220M-open_instruct)
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+
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+ | Metric |Value|
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+ |---------------------------------|----:|
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+ |Avg. |29.19|
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+ |AI2 Reasoning Challenge (25-Shot)|25.00|
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+ |HellaSwag (10-Shot) |29.71|
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+ |MMLU (5-Shot) |26.11|
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+ |TruthfulQA (0-shot) |44.06|
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+ |Winogrande (5-shot) |50.28|
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+ |GSM8k (5-shot) | 0.00|
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+