173 lines
4.9 KiB
Markdown
173 lines
4.9 KiB
Markdown
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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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tags:
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- merge
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pipeline_tag: text-generation
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model-index:
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- name: Sakura-SOLAR-Instruct
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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: 70.99
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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-SOLAR-Instruct
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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: 88.42
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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-SOLAR-Instruct
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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: 66.33
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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-SOLAR-Instruct
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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: 71.79
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kyujinpy/Sakura-SOLAR-Instruct
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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: 83.66
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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-SOLAR-Instruct
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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: 65.2
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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-SOLAR-Instruct
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name: Open LLM Leaderboard
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---
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# **Sakura-SOLAR-Instruct**
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<img src='./sakura.png' width=512>
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**(주)미디어그룹사람과숲과 (주)마커의 LLM 연구 컨소시엄에서 개발된 모델입니다**
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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 [Mergekit](https://github.com/cg123/mergekit).
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I shared 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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**Blog**
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- [Sakura-SOLAR 모델 제작 과정 및 후기](https://kyujinpy.tistory.com/122).
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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-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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> Rank1 2023.12.27 PM 11:50
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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-SOLAR-Instruct"
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sakura_solar = 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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sakura_solar_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-SOLAR-Instruct)
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| Metric |Value|
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|Avg. |74.40|
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|AI2 Reasoning Challenge (25-Shot)|70.99|
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|HellaSwag (10-Shot) |88.42|
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|MMLU (5-Shot) |66.33|
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|TruthfulQA (0-shot) |71.79|
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|Winogrande (5-shot) |83.66|
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|GSM8k (5-shot) |65.20|
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