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--- |
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language: |
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- ko |
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- en |
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license: llama2 |
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library_name: transformers |
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model-index: |
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- name: mnsim-dpo-peftmerged-2-eos |
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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: 55.63 |
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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=msy127/mnsim-dpo-peftmerged-2-eos |
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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: 77.82 |
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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=msy127/mnsim-dpo-peftmerged-2-eos |
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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: 51.25 |
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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=msy127/mnsim-dpo-peftmerged-2-eos |
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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: 46.37 |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=msy127/mnsim-dpo-peftmerged-2-eos |
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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: 76.24 |
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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=msy127/mnsim-dpo-peftmerged-2-eos |
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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: 16.91 |
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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=msy127/mnsim-dpo-peftmerged-2-eos |
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name: Open LLM Leaderboard |
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--- |
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--- |
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license: llama2 |
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language: |
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- ko |
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- en |
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library_name: transformers |
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base_model: mncai/llama2-13b-dpo-v7 |
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pipeline_tag: text-generation |
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--- |
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# **mnsim-dpo-peftmerged-2-eos** |
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## Our Team |
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| Research & Engineering | Product Management | |
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| :--------------------: | :----------------: | |
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| David Sohn | David Sohn | |
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## **Model Details** |
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### **Base Model** |
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[mncai/llama2-13b-dpo-v7](https://huggingface.co/mncai/llama2-13b-dpo-v7) |
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### **Trained On** |
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- **OS**: Ubuntu 22.04 |
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- **GPU**: A100 40GB 1ea |
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- **transformers**: v4.35.2 |
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### **Instruction format** |
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It follows **Custom** format. |
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E.g. |
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```python |
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text = """\ |
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<s> |
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<|user|> |
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건κ°ν μμ΅κ΄μ λ§λ€κΈ° μν΄μλ μ΄λ»κ² νλκ²μ΄ μ’μκΉμ? |
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<|assistant|> |
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""" |
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``` |
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## **Implementation Code** |
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This model contains the chat_template instruction format. |
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You can use the code below. |
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```python |
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# Use a pipeline as a high-level helper |
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from transformers import pipeline |
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pipe = pipeline("text-generation", model="msy127/mnsim-dpo-peftmerged-2-eos") |
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# Load model directly |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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tokenizer = AutoTokenizer.from_pretrained("msy127/mnsim-dpo-peftmerged-2-eos") |
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model = AutoModelForCausalLM.from_pretrained("msy127/mnsim-dpo-peftmerged-2-eos") |
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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_msy127__mnsim-dpo-peftmerged-2-eos) |
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| Metric |Value| |
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|---------------------------------|----:| |
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|Avg. |54.04| |
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|AI2 Reasoning Challenge (25-Shot)|55.63| |
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|HellaSwag (10-Shot) |77.82| |
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|MMLU (5-Shot) |51.25| |
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|TruthfulQA (0-shot) |46.37| |
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|Winogrande (5-shot) |76.24| |
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|GSM8k (5-shot) |16.91| |
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