• Model creator: https://huggingface.co/CallComply/
• Original model: https://huggingface.co/CallComply/zephyr-7b-beta-128k/

Original model description:

• en license: mit tags:
• generated_from_trainer datasets:
• HuggingFaceH4/ultrachat_200k
• HuggingFaceH4/ultrafeedback_binarized base_model: mistralai/Mistral-7B-v0.1 widget:
• text: '<|system|>
  You are a pirate chatbot who always responds with Arr!
  <|user|>
  There''s a llama on my lawn, how can I get rid of him?
  <|assistant|>
  ' output: text: Arr! 'Tis a puzzlin' matter, me hearty! A llama on yer lawn be a rare sight, but I've got a plan that might help ye get rid of 'im. Ye'll need to gather some carrots and hay, and then lure the llama away with the promise of a tasty treat. Once he's gone, ye can clean up yer lawn and enjoy the peace and quiet once again. But beware, me hearty, for there may be more llamas where that one came from! Arr! pipeline_tag: text-generation model-index:
• name: zephyr-7b-beta results:
  • task: type: text-generation name: Text Generation dataset: name: AI2 Reasoning Challenge (25-Shot) type: ai2_arc config: ARC-Challenge split: test args: num_few_shot: 25 metrics:
    • type: acc_norm value: 62.03071672354948 name: normalized accuracy
    • type: acc_norm value: 58.28 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=HuggingFaceH4/zephyr-7b-beta name: Open LLM Leaderboard
  • task: type: text-generation name: Text Generation dataset: name: HellaSwag (10-Shot) type: hellaswag split: validation args: num_few_shot: 10 metrics:
    • type: acc_norm value: 84.35570603465445 name: normalized accuracy
    • type: acc_norm value: 81.0 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=HuggingFaceH4/zephyr-7b-beta name: Open LLM Leaderboard
  • task: type: text-generation name: Text Generation dataset: name: Drop (3-Shot) type: drop split: validation args: num_few_shot: 3 metrics:
    • type: f1 value: 9.66243708053691 name: f1 score source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=HuggingFaceH4/zephyr-7b-beta name: Open LLM Leaderboard
  • task: type: text-generation name: Text Generation dataset: name: TruthfulQA (0-shot) type: truthful_qa config: multiple_choice split: validation args: num_few_shot: 0 metrics:
    • type: mc2 value: 57.44916942762855
    • type: mc2 value: 46.1 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=HuggingFaceH4/zephyr-7b-beta name: Open LLM Leaderboard
  • task: type: text-generation name: Text Generation dataset: name: GSM8k (5-shot) type: gsm8k config: main split: test args: num_few_shot: 5 metrics:
    • type: acc value: 12.736921910538287 name: accuracy
    • type: acc value: 13.04 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=HuggingFaceH4/zephyr-7b-beta name: Open LLM Leaderboard
  • task: type: text-generation name: Text Generation dataset: name: MMLU (5-Shot) type: cais/mmlu config: all split: test args: num_few_shot: 5 metrics:
    • type: acc value: 61.07 name: accuracy
    • type: acc value: 53.57 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=HuggingFaceH4/zephyr-7b-beta name: Open LLM Leaderboard
  • task: type: text-generation name: Text Generation dataset: name: Winogrande (5-shot) type: winogrande config: winogrande_xl split: validation args: num_few_shot: 5 metrics:
    • type: acc value: 77.7426992896606 name: accuracy
    • type: acc value: 74.74 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=HuggingFaceH4/zephyr-7b-beta name: Open LLM Leaderboard
  • task: type: text-generation name: Text Generation dataset: name: AlpacaEval type: tatsu-lab/alpaca_eval metrics:
    • type: unknown value: 0.906 name: win rate source: url: https://tatsu-lab.github.io/alpaca_eval/
  • task: type: text-generation name: Text Generation dataset: name: MT-Bench type: unknown metrics:
    • type: unknown value: 7.34 name: score source: url: https://huggingface.co/spaces/lmsys/mt-bench

Model Card for Zephyr 7B β

Model description

• Model type: A 7B parameter GPT-like model fine-tuned on a mix of publicly available, synthetic datasets.
• Language(s) (NLP): Primarily English
• License: MIT
• Finetuned from model: mistralai/Mistral-7B-v0.1

Model Sources

• Repository: https://github.com/huggingface/alignment-handbook
• Demo: https://huggingface.co/spaces/HuggingFaceH4/zephyr-chat
• Chatbot Arena: Evaluate Zephyr 7B against 10+ LLMs in the LMSYS arena: http://arena.lmsys.org

Performance

Intended uses & limitations

Bias, Risks, and Limitations

Training and evaluation data

• Loss: 0.7496
• Rewards/chosen: -4.5221
• Rewards/rejected: -8.3184
• Rewards/accuracies: 0.7812
• Rewards/margins: 3.7963
• Logps/rejected: -340.1541
• Logps/chosen: -299.4561
• Logits/rejected: -2.3081
• Logits/chosen: -2.3531

Training hyperparameters

• learning_rate: 5e-07
• train_batch_size: 2
• eval_batch_size: 4
• seed: 42
• distributed_type: multi-GPU
• num_devices: 16
• total_train_batch_size: 32
• total_eval_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 3.0

Training results

Framework versions

• Transformers 4.35.0.dev0
• Pytorch 2.0.1+cu118
• Datasets 2.12.0
• Tokenizers 0.14.0

Citation

@misc{tunstall2023zephyr,
      title={Zephyr: Direct Distillation of LM Alignment}, 
      author={Lewis Tunstall and Edward Beeching and Nathan Lambert and Nazneen Rajani and Kashif Rasul and Younes Belkada and Shengyi Huang and Leandro von Werra and Clémentine Fourrier and Nathan Habib and Nathan Sarrazin and Omar Sanseviero and Alexander M. Rush and Thomas Wolf},
      year={2023},
      eprint={2310.16944},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}

Open LLM Leaderboard Evaluation Results

Open LLM Leaderboard Evaluation Results