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Model: kyujinpy/Sakura-SOLRCA-Math-Instruct-DPO-v1 Source: Original Platform
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README.md
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README.md
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---
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language:
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- en
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license: cc-by-nc-sa-4.0
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datasets:
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- Intel/orca_dpo_pairs
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- argilla/distilabel-math-preference-dpo
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- kyujinpy/orca_math_dpo
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pipeline_tag: text-generation
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model-index:
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- name: Sakura-SOLRCA-Math-Instruct-DPO-v1
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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: 71.25
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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=kyujinpy/Sakura-SOLRCA-Math-Instruct-DPO-v1
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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: 88.48
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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=kyujinpy/Sakura-SOLRCA-Math-Instruct-DPO-v1
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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: 66.21
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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=kyujinpy/Sakura-SOLRCA-Math-Instruct-DPO-v1
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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: 72.12
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kyujinpy/Sakura-SOLRCA-Math-Instruct-DPO-v1
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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: 82.87
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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=kyujinpy/Sakura-SOLRCA-Math-Instruct-DPO-v1
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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: 63.84
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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=kyujinpy/Sakura-SOLRCA-Math-Instruct-DPO-v1
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name: Open LLM Leaderboard
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---
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# **Sakura-SOLRCA-Math-Instruct-DPO-v1**
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<img src='./sakura.png' width=512>
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## Model Details
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**Model Developers** Kyujin Han (kyujinpy)
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**Method**
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Using DPO method.
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With [Intel/orca_dpo_pairs](https://huggingface.co/datasets/Intel/orca_dpo_pairs) and [argilla/distilabel-math-preference-dpo](https://huggingface.co/datasets/argilla/distilabel-math-preference-dpo).
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I shared the merge version [kyujinpy/orca_math_dpo](https://huggingface.co/datasets/kyujinpy/orca_math_dpo).
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I will share the information about my model. (training and code)
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Please see: ⭐[Sakura-SOLAR](https://github.com/KyujinHan/Sakura-SOLAR-DPO).
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# **Model Benchmark**
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## Open leaderboard
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- Follow up as [link](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
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| Model | Average | ARC | HellaSwag | MMLU | TruthfulQA | Winogrande | GSM8K |
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| --- | --- | --- | --- | --- | --- | --- | --- |
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| Sakura-SOLRCA-Math-Instruct-DPO-v2 | 74.17 | 71.25 | 88.52 | 66.13 | 72.16 | 83.03 | 63.91 |
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| Sakura-SOLRCA-Math-Instruct-DPO-v1 | 74.13 | 71.25 | 88.48 | 66.21 | 72.12 | 82.87 | 63.84 |
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| Sakura-SOLRCA-Instruct-DPO | 74.05 | 71.16 | 88.49 | 66.17 | 72.10 | 82.95 | 63.46 |
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| Sakura-SOLAR-Instruct-DPO-v2 | 74.14 | 70.90 | 88.41 | 66.48 | 71.86 | 83.43 | 63.76 |
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| [kyujinpy/Sakura-SOLAR-Instruct](https://huggingface.co/kyujinpy/Sakura-SOLAR-Instruct) | 74.40 | 70.99 | 88.42 | 66.33 | 71.79 | 83.66 | 65.20 |
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# Implementation Code
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```python
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### KO-Platypus
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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repo = "kyujinpy/Sakura-SOLRCA-Math-Instruct-DPO-v1"
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OpenOrca = AutoModelForCausalLM.from_pretrained(
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repo,
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return_dict=True,
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torch_dtype=torch.float16,
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device_map='auto'
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)
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OpenOrca_tokenizer = AutoTokenizer.from_pretrained(repo)
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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_kyujinpy__Sakura-SOLRCA-Math-Instruct-DPO-v1)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |74.13|
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|AI2 Reasoning Challenge (25-Shot)|71.25|
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|HellaSwag (10-Shot) |88.48|
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|MMLU (5-Shot) |66.21|
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|TruthfulQA (0-shot) |72.12|
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|Winogrande (5-shot) |82.87|
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|GSM8k (5-shot) |63.84|
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