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
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---
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license: apache-2.0
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datasets:
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- HuggingFaceH4/ultrachat_200k
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- mlabonne/CodeLlama-2-20k
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- Intel/orca_dpo_pairs
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- Sharathhebbar24/Evol-Instruct-Code-80k-v1
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- Sharathhebbar24/sql-create-context
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language:
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- en
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pipeline_tag: text-generation
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---
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This model is a finetuned version of [Sharathhebbar24/code_gpt2_mini_model](https://huggingface.co/Sharathhebbar24/code_gpt2_mini_model) using [Sharathhebbar24/Evol-Instruct-Code-80k-v1](https://huggingface.co/datasets/Sharathhebbar24/Evol-Instruct-Code-80k-v1)
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@@ -47,4 +150,17 @@ prompt.
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>>> prompt = "Can you write a Linear search program in Python"
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>>> res = generate_text(prompt)
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>>> res
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-
```
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---
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language:
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- en
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license: apache-2.0
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tags:
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- gpt2
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- dpo
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- code
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datasets:
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- HuggingFaceH4/ultrachat_200k
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- mlabonne/CodeLlama-2-20k
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- Intel/orca_dpo_pairs
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- Sharathhebbar24/Evol-Instruct-Code-80k-v1
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- Sharathhebbar24/sql-create-context
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pipeline_tag: text-generation
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model-index:
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- name: code_gpt2
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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: 23.29
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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=Sharathhebbar24/code_gpt2
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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: 30.99
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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=Sharathhebbar24/code_gpt2
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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: 25.03
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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=Sharathhebbar24/code_gpt2
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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: 40.6
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Sharathhebbar24/code_gpt2
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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: 49.25
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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=Sharathhebbar24/code_gpt2
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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=Sharathhebbar24/code_gpt2
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name: Open LLM Leaderboard
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---
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This model is a finetuned version of [Sharathhebbar24/code_gpt2_mini_model](https://huggingface.co/Sharathhebbar24/code_gpt2_mini_model) using [Sharathhebbar24/Evol-Instruct-Code-80k-v1](https://huggingface.co/datasets/Sharathhebbar24/Evol-Instruct-Code-80k-v1)
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>>> prompt = "Can you write a Linear search program in Python"
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>>> res = generate_text(prompt)
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>>> res
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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_Sharathhebbar24__code_gpt2)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |28.19|
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|AI2 Reasoning Challenge (25-Shot)|23.29|
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|HellaSwag (10-Shot) |30.99|
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|MMLU (5-Shot) |25.03|
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|TruthfulQA (0-shot) |40.60|
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|Winogrande (5-shot) |49.25|
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|GSM8k (5-shot) | 0.00|
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