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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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- - **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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  <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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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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- #### 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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- ## 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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- #### Hardware
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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 Needed]
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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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- ### Framework versions
 
 
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  - PEFT 0.14.0
 
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  # Model Card for Model ID
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+ This lora is trained for Deepseek R1 Qwen model for providing better replies in Engineering using smaller LLMs.
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+ - **Developed by:** Just some student
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+ - **Model type:** PEFT
 
 
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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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  #### Metrics
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+ Train loss - 1.399200 Eval loss - 1.393927
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ### Results
 
 
 
 
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+ - **Hardware Type:** 2 x Nvidia T4
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+ - **Hours used:** 2h
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+ - **Cloud Provider:** Kaggle
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+ - **Compute Region:** Russia
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  - PEFT 0.14.0