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Model: oumi-ai/MiniMath-R1-1.5B Source: Original Platform
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README.md
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---
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tags:
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- math
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license: apache-2.0
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datasets:
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- oumi-ai/MetaMathQA-R1
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language:
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- en
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metrics:
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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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[](https://github.com/oumi-ai/oumi)
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[](https://github.com/oumi-ai/oumi)
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[](https://oumi.ai/docs/en/latest/index.html)
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[](https://oumi.ai/blog)
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[](https://discord.gg/oumi)
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# oumi-ai/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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<!-- 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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- **Hardware Type:** H100
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- **Hours used:** 0.8 (0.1 * 8 GPUs)
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- **Cloud Provider:** Google Cloud Platform
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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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@misc{miniMathR1_2025,
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author = {Jeremiah Greer},
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title = {MiniMath-R1-1.5B},
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month = {February},
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year = {2025},
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url = {https://huggingface.co/oumi-ai/MiniMath-R1-1.5B}
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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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```
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config.json
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{
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"architectures": [
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"Qwen2ForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 151643,
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"eos_token_id": 151643,
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"hidden_act": "silu",
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"hidden_size": 1536,
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"initializer_range": 0.02,
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"intermediate_size": 8960,
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"max_position_embeddings": 131072,
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"max_window_layers": 21,
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"model_type": "qwen2",
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"num_attention_heads": 12,
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"num_hidden_layers": 28,
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"num_key_value_heads": 2,
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"rms_norm_eps": 1e-06,
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"rope_scaling": null,
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"rope_theta": 10000,
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"sliding_window": 4096,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.51.3",
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"use_cache": false,
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"use_mrope": false,
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"use_sliding_window": false,
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"vocab_size": 151936
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}
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configuration.json
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{"framework": "pytorch", "task": "text-generation", "allow_remote": true}
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 151646,
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"do_sample": true,
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"eos_token_id": 151643,
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"temperature": 0.6,
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"top_p": 0.95,
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"transformers_version": "4.51.3"
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}
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version https://git-lfs.github.com/spec/v1
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oid sha256:8f929f4b331971a962757c995839ed59af9fa5b67d7bea59435483a032e59c93
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size 3554214752
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tokenizer.json
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version https://git-lfs.github.com/spec/v1
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oid sha256:88145e3c3249adc2546ede277e9819d6e405e19072456e4b521cbc724bd60773
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size 7031660
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{
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"add_bos_token": true,
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"add_eos_token": false,
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"bos_token": {
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"__type": "AddedToken",
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"content": "<|begin▁of▁sentence|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"clean_up_tokenization_spaces": false,
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"eos_token": {
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"__type": "AddedToken",
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"content": "<|end▁of▁sentence|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"legacy": true,
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"model_max_length": 16384,
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"pad_token": {
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"__type": "AddedToken",
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"content": "<|end▁of▁sentence|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"sp_model_kwargs": {},
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"unk_token": null,
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"tokenizer_class": "LlamaTokenizerFast",
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"chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set ns = namespace(is_first=false, is_tool=false, is_output_first=true, system_prompt='') %}{%- for message in messages %}{%- if message['role'] == 'system' %}{% set ns.system_prompt = message['content'] %}{%- endif %}{%- endfor %}{{bos_token}}{{ns.system_prompt}}{%- for message in messages %}{%- if message['role'] == 'user' %}{%- set ns.is_tool = false -%}{{'<|User|>' + message['content']}}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is none %}{%- set ns.is_tool = false -%}{%- for tool in message['tool_calls']%}{%- if not ns.is_first %}{{'<|Assistant|><|tool▁calls▁begin|><|tool▁call▁begin|>' + tool['type'] + '<|tool▁sep|>' + tool['function']['name'] + '\\n' + '```json' + '\\n' + tool['function']['arguments'] + '\\n' + '```' + '<|tool▁call▁end|>'}}{%- set ns.is_first = true -%}{%- else %}{{'\\n' + '<|tool▁call▁begin|>' + tool['type'] + '<|tool▁sep|>' + tool['function']['name'] + '\\n' + '```json' + '\\n' + tool['function']['arguments'] + '\\n' + '```' + '<|tool▁call▁end|>'}}{{'<|tool▁calls▁end|><|end▁of▁sentence|>'}}{%- endif %}{%- endfor %}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is not none %}{%- if ns.is_tool %}{{'<|tool▁outputs▁end|>' + message['content'] + '<|end▁of▁sentence|>'}}{%- set ns.is_tool = false -%}{%- else %}{% set content = message['content'] %}{% if '</think>' in content %}{% set content = content.split('</think>')[-1] %}{% endif %}{{'<|Assistant|>' + content + '<|end▁of▁sentence|>'}}{%- endif %}{%- endif %}{%- if message['role'] == 'tool' %}{%- set ns.is_tool = true -%}{%- if ns.is_output_first %}{{'<|tool▁outputs▁begin|><|tool▁output▁begin|>' + message['content'] + '<|tool▁output▁end|>'}}{%- set ns.is_output_first = false %}{%- else %}{{'\\n<|tool▁output▁begin|>' + message['content'] + '<|tool▁output▁end|>'}}{%- endif %}{%- endif %}{%- endfor -%}{% if ns.is_tool %}{{'<|tool▁outputs▁end|>'}}{% endif %}{% if add_generation_prompt and not ns.is_tool %}{{'<|Assistant|><think>\\n'}}{% endif %}"
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}
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