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Model: wandb/gemma-7b-zephyr-dpo Source: Original Platform
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README.md
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---
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license: other
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library_name: transformers
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datasets:
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- HuggingFaceH4/ultrafeedback_binarized
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base_model: wandb/gemma-7b-zephyr-sft
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license_name: gemma-terms-of-use
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license_link: https://ai.google.dev/gemma/terms
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model-index:
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- name: gemma-7b-zephyr-dpo
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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: 60.84
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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=tcapelle/gemma-7b-zephyr-dpo
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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: 80.44
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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=tcapelle/gemma-7b-zephyr-dpo
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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: 60.6
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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=tcapelle/gemma-7b-zephyr-dpo
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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: 42.48
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=tcapelle/gemma-7b-zephyr-dpo
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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: 75.37
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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=tcapelle/gemma-7b-zephyr-dpo
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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: 49.96
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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=tcapelle/gemma-7b-zephyr-dpo
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name: Open LLM Leaderboard
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---
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/llm_surgery/gemma-zephyr)
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# Gemma 7B Zephyr DPO
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The [Zephyr](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta) DPO recipe applied on top of SFT finetuned Gemma 7B
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## Model description
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- **Model type:** A 8.5B parameter GPT-like model fine-tuned on a mix of publicly available, synthetic datasets.
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- **Language(s) (NLP):** Primarily English
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- **Finetuned from model:** [wandb/gemma-7b-zephyr-sft](https://huggingface.co/wandb/gemma-7b-zephyr-sft/)
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## Recipe
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We trained using the DPO script in [alignment handbook recipe](https://github.com/huggingface/alignment-handbook/blob/main/scripts/run_dpo.py) and logging to W&B
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Visit the [W&B workspace here](https://wandb.ai/llm_surgery/gemma-zephyr?nw=nwusercapecape)
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## License
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This model has the same license as the [original Gemma model collection](https://ai.google.dev/gemma/terms)
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## Compute provided by [Lambda Labs](https://lambdalabs.com/) - 8xA100 80GB node
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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_tcapelle__gemma-7b-zephyr-dpo)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |61.62|
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|AI2 Reasoning Challenge (25-Shot)|60.84|
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|HellaSwag (10-Shot) |80.44|
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|MMLU (5-Shot) |60.60|
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|TruthfulQA (0-shot) |42.48|
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|Winogrande (5-shot) |75.37|
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|GSM8k (5-shot) |49.96|
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