---
license: apache-2.0
tags:
- dpo
base_model:
- CorticalStack/pastiche-crown-clown-7b-dare
dataset:
- jondurbin/truthy-dpo-v0.1
model-index:
- name: pastiche-crown-clown-7b-dare-dpo
  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: 72.78
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=CorticalStack/pastiche-crown-clown-7b-dare-dpo
      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: 89.15
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=CorticalStack/pastiche-crown-clown-7b-dare-dpo
      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: 64.51
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=CorticalStack/pastiche-crown-clown-7b-dare-dpo
      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: 78.8
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=CorticalStack/pastiche-crown-clown-7b-dare-dpo
      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: 84.85
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=CorticalStack/pastiche-crown-clown-7b-dare-dpo
      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: 68.92
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=CorticalStack/pastiche-crown-clown-7b-dare-dpo
      name: Open LLM Leaderboard
---

# CorticalStack/pastiche-crown-clown-7b-dare-dpo

CorticalStack/pastiche-crown-clown-7b-dare-dpo is a DPO fine-tuned version of [CorticalStack/pastiche-crown-clown-7b-dare](https://huggingface.co/CorticalStack/pastiche-crown-clown-7b-dare) using the [jondurbin/truthy-dpo-v0.1](https://huggingface.co/datasets/jondurbin/truthy-dpo-v0.1) dataset.

### LoRA
- r: 16
- LoRA alpha: 16
- LoRA dropout: 0.05

### Training arguments
- Batch size: 4
- Gradient accumulation steps: 4
- Optimizer: paged_adamw_32bit
- Max steps: 200
- Learning rate: 5e-05
- Learning rate scheduler type: cosine
- Beta: 0.1
- Max prompt length: 1024
- Max length: 1536
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_CorticalStack__pastiche-crown-clown-7b-dare-dpo)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |76.50|
|AI2 Reasoning Challenge (25-Shot)|72.78|
|HellaSwag (10-Shot)              |89.15|
|MMLU (5-Shot)                    |64.51|
|TruthfulQA (0-shot)              |78.80|
|Winogrande (5-shot)              |84.85|
|GSM8k (5-shot)                   |68.92|