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  - accuracy
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  base_model:
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  - deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
 
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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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- ## 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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- - **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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- [More Information Needed]
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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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@@ -157,28 +80,16 @@ Carbon emissions can be estimated using the [Machine Learning Impact calculator]
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  - **Compute Region:** us-east5
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  - **Carbon Emitted:** 0.07 kg
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- ## Technical Specifications [optional]
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- ### Model Architecture and Objective
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- [More Information Needed]
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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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- [More Information Needed]
 
 
 
 
 
 
 
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  - accuracy
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  base_model:
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  - deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
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+ pipeline_tag: text-generation
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  ---
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+ [![oumi logo](https://oumi.ai/logo_lockup_black.svg)](https://github.com/oumi-ai/oumi)
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+ [![Documentation](https://img.shields.io/badge/Documentation-oumi-blue.svg)](https://oumi.ai/docs/en/latest/index.html)
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+ [![Blog](https://img.shields.io/badge/Blog-oumi-blue.svg)](https://oumi.ai/blog)
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+ [![Discord](https://img.shields.io/discord/1286348126797430814?label=Discord)](https://discord.gg/oumi)
 
 
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+ # MiniMath-R1-1.5B
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+ <!-- Provide a quick summary of what the model is/does. -->
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+ Supervised fine-tune of [DeepSeek-R1-Distill-Qwen-1.5B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B) using [oumi-ai/MetaMathQA-R1](https://huggingface.co/datasets/oumi-ai/MetaMathQA-R1).
 
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+ Achieves **44.4% accuracy on MMLU-Pro-Math**, the **highest of any model with <=1.5B parameters**.
 
 
 
 
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+ Improves the base model's accuracy by **+6 points**.
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+ - **Developed by:** [Oumi AI](https://oumi.ai/)
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+ - **Model type:** Small Language Model
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+ - **Language(s) (NLP):** English
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+ - **License:** [Apache 2.0](https://opensource.org/license/apache-2-0)
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+ - **Finetuned from model:** [DeepSeek-R1-Distill-Qwen-1.5B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B)
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+ - **Demo:** [Fine-Tuning Notebook](https://github.com/oumi-ai/oumi/blob/307436bd98706cb9ce7b0bbf31204770af2b7c8c/notebooks/Oumi%20-%20MiniMath-R1-1.5B.ipynb)
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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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+ Use as a conversational assistant for solving math problems with an exposed thought process.
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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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+ Smaller LLMs have limited capabilities and should be used with caution. Avoid using this model for purposes outside of mathematics.
 
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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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+ This model was finetuned with DeepSeek-R1 data on top of an R1-distill model, so any biases or risks associated with those models may be present.
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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+ Training data: [oumi-ai/MetaMathQA-R1](https://huggingface.co/datasets/oumi-ai/MetaMathQA-R1)
 
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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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+ Training notebook: [Fine-Tuning Notebook](https://github.com/oumi-ai/oumi/blob/307436bd98706cb9ce7b0bbf31204770af2b7c8c/notebooks/Oumi%20-%20MiniMath-R1-1.5B.ipynb)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ## Evaluation
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  <!-- This section describes the evaluation protocols and provides the results. -->
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  ## Environmental Impact
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  - **Compute Region:** us-east5
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  - **Carbon Emitted:** 0.07 kg
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+ ## Citation
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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+ ```
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+ @software{oumi2025,
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+ author = {Oumi Community},
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+ title = {Oumi: an Open, End-to-end Platform for Building Large Foundation Models},
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+ month = {January},
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+ year = {2025},
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+ url = {https://github.com/oumi-ai/oumi}
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+ }
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+ ```