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  library_name: transformers
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- tags: []
 
 
 
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  # Model Card for Model ID
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  <!-- Provide a quick summary of what the model is/does. -->
 
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- ## Model Details
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- ### Model Description
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- <!-- Provide a longer summary of what this model is. -->
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- This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- - **Developed by:** [More Information Needed]
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- - **Funded by [optional]:** [More Information Needed]
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- - **Shared by [optional]:** [More Information Needed]
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- - **Model type:** [More Information Needed]
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- - **Language(s) (NLP):** [More Information Needed]
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- - **License:** [More Information Needed]
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- - **Finetuned from model [optional]:** [More Information Needed]
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- ### Model Sources [optional]
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- <!-- Provide the basic links for the model. -->
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- - **Repository:** [More Information Needed]
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- - **Paper [optional]:** [More Information Needed]
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- - **Demo [optional]:** [More Information Needed]
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- ## Uses
 
 
 
 
 
 
 
 
 
 
 
 
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- <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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- ### Direct Use
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- <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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- [More Information Needed]
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- ### Downstream Use [optional]
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- <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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- [More Information Needed]
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- ### Out-of-Scope Use
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- <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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- [More Information Needed]
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- ## Bias, Risks, and Limitations
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- <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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- [More Information Needed]
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- ### Recommendations
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- <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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- Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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- ## How to Get Started with the Model
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- Use the code below to get started with the model.
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- [More Information Needed]
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- ## Training Details
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- ### Training Data
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- <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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- [More Information Needed]
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- ### Training Procedure
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- <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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- #### Preprocessing [optional]
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- [More Information Needed]
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- #### Training Hyperparameters
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- - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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- #### Speeds, Sizes, Times [optional]
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- <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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- [More Information Needed]
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- ## Evaluation
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- <!-- This section describes the evaluation protocols and provides the results. -->
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- ### Testing Data, Factors & Metrics
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- #### Testing Data
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- <!-- This should link to a Dataset Card if possible. -->
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- [More Information Needed]
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- #### Factors
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- <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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- #### Metrics
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- <!-- These are the evaluation metrics being used, ideally with a description of why. -->
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- ### Results
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- #### Summary
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- ## Model Examination [optional]
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- <!-- Relevant interpretability work for the model goes here -->
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- [More Information Needed]
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- ## Environmental Impact
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- <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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- Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- - **Hardware Type:** [More Information Needed]
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- - **Hours used:** [More Information Needed]
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- - **Cloud Provider:** [More Information Needed]
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- - **Compute Region:** [More Information Needed]
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- - **Carbon Emitted:** [More Information Needed]
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- ## Technical Specifications [optional]
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- ### Model Architecture and Objective
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- ### Compute Infrastructure
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- #### Software
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- ## Citation [optional]
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- <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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- **BibTeX:**
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- **APA:**
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- ## Glossary [optional]
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- <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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- ## More Information [optional]
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- ## Model Card Authors [optional]
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- ## Model Card Contact
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- [More Information Needed]
 
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  ---
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  library_name: transformers
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+ license: apache-2.0
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+ language:
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+ - ko
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+ - en
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  ---
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  # Model Card for Model ID
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  <!-- Provide a quick summary of what the model is/does. -->
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+ aeolian83/Llama-3-Open-Ko-8B-aeolian83-chatvec 모델은
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+ chat-vector 논문( https://arxiv.org/abs/2310.04799v2 )에 근거하여,
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+ llama3의 pre-trained 모델의 parameter와 instruction 모델의 매개변수의 차이를
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+ beomi님의 Llama-3-Open-Ko-8B에 적용한 모델
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+ 방법이 가능하다면 llama3의 instruction 모델에
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+ llama3의 pre-trained 모델과 한국어 CP모델인 Llama-3-Open-Ko-8B 모델의 매개변수 차이를
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+ instruction 모델에 넣었을 어떻게 되는지 확인하는 모델
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+ 매개변수에 가중치를 0.7
 
 
 
 
 
 
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+ # Metric
 
 
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+ results/all/aeolian83/Llama-3-8B-Instruct-cp-transfer_0.7
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+ | | 0 | 5 |
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+ |:---------------------------------|---------:|---------:|
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+ | kobest_boolq (macro_f1) | 0.786414 | 0.775213 |
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+ | kobest_copa (macro_f1) | 0.67162 | 0.719676 |
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+ | kobest_hellaswag (macro_f1) | 0.436275 | 0.423664 |
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+ | kobest_sentineg (macro_f1) | 0.503784 | 0.901741 |
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+ | kohatespeech (macro_f1) | 0.260168 | 0.339337 |
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+ | kohatespeech_apeach (macro_f1) | 0.337667 | 0.611894 |
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+ | kohatespeech_gen_bias (macro_f1) | 0.124535 | 0.505005 |
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+ | korunsmile (f1) | 0.410636 | 0.323403 |
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+ | nsmc (acc) | 0.53778 | 0.81346 |
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+ | pawsx_ko (acc) | 0.5485 | 0.486 |
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+ # Used Model
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+ - Base model(weight diff를 구하기 위한 베이스 모델) : meta-llama/Meta-Llama-3-8B
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+ - Chat model(weight diff를 제공하는 cp model) : beomi/Llama-3-Open-Ko-8B
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+ - Target model(weight diff를 적용해서 instruction 튠을 하고자 하는 모델) : meta-llama/Meta-Llama-3-8B-Instruct