Text Generation
Transformers
PyTorch
Safetensors
English
llama
finance
Eval Results
text-generation-inference
Inference Endpoints
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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 +119 -3
README.md CHANGED
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  language:
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  - en
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  license: llama2
 
 
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  datasets:
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  - Open-Orca/OpenOrca
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  - GAIR/lima
@@ -9,8 +11,109 @@ datasets:
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  metrics:
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  - accuracy
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  pipeline_tag: text-generation
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- tags:
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- - finance
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  # Domain Adaptation of Large Language Models
@@ -89,4 +192,17 @@ If you find our work helpful, please cite us:
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  journal={arXiv preprint arXiv:2309.09530},
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  year={2023}
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  }
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- ```
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  language:
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  - en
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  license: llama2
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+ tags:
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+ - finance
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  datasets:
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  - Open-Orca/OpenOrca
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  - GAIR/lima
 
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  metrics:
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  - accuracy
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  pipeline_tag: text-generation
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+ model-index:
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+ - name: finance-chat
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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: 53.75
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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=AdaptLLM/finance-chat
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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: 76.6
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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=AdaptLLM/finance-chat
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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: 50.16
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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=AdaptLLM/finance-chat
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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: 44.54
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AdaptLLM/finance-chat
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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: 75.69
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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=AdaptLLM/finance-chat
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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: 18.8
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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=AdaptLLM/finance-chat
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+ name: Open LLM Leaderboard
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  ---
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  # Domain Adaptation of Large Language Models
 
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  journal={arXiv preprint arXiv:2309.09530},
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  year={2023}
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  }
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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_AdaptLLM__finance-chat)
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+
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+ | Metric |Value|
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+ |---------------------------------|----:|
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+ |Avg. |53.26|
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+ |AI2 Reasoning Challenge (25-Shot)|53.75|
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+ |HellaSwag (10-Shot) |76.60|
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+ |MMLU (5-Shot) |50.16|
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+ |TruthfulQA (0-shot) |44.54|
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+ |Winogrande (5-shot) |75.69|
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+ |GSM8k (5-shot) |18.80|
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+