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Model: Neelectric/OLMo-2-0425-1B-Instruct_SFT_mathv00.01 Source: Original Platform
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README.md
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README.md
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---
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base_model: allenai/OLMo-2-0425-1B-Instruct
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datasets: Neelectric/OpenR1-Math-220k_all_Llama3_4096toks
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library_name: transformers
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model_name: OLMo-2-0425-1B-Instruct_SFT_mathv00.01
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tags:
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- generated_from_trainer
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- open-r1
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- trl
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- sft
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licence: license
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---
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# Model Card for OLMo-2-0425-1B-Instruct_SFT_mathv00.01
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This model is a fine-tuned version of [allenai/OLMo-2-0425-1B-Instruct](https://huggingface.co/allenai/OLMo-2-0425-1B-Instruct) on the [Neelectric/OpenR1-Math-220k_all_Llama3_4096toks](https://huggingface.co/datasets/Neelectric/OpenR1-Math-220k_all_Llama3_4096toks) dataset.
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It has been trained using [TRL](https://github.com/huggingface/trl).
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## Quick start
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```python
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from transformers import pipeline
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question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
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generator = pipeline("text-generation", model="Neelectric/OLMo-2-0425-1B-Instruct_SFT_mathv00.01", device="cuda")
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output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
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print(output["generated_text"])
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```
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## Training procedure
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/neelectric/open-r1_math/runs/6elaowt2)
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This model was trained with SFT.
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### Framework versions
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- TRL: 1.1.0.dev0
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- Transformers: 4.57.6
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- Pytorch: 2.9.0
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- Datasets: 4.8.5
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- Tokenizers: 0.22.2
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## Citations
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Cite TRL as:
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```bibtex
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@software{vonwerra2020trl,
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title = {{TRL: Transformers Reinforcement Learning}},
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author = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
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license = {Apache-2.0},
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url = {https://github.com/huggingface/trl},
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year = {2020}
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}
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```
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all_results.json
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{
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"total_flos": 9.578088657357636e+18,
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"train_loss": 0.46163898064592473,
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"train_runtime": 11201.6896,
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"train_samples": 125770,
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"train_samples_per_second": 33.683,
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"train_steps_per_second": 2.105
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}
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chat_template.jinja
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{{ bos_token }}
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{%- if messages[0]['role'] == 'system' %}
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{%- set system_message = messages[0]['content']|trim %}
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{%- set messages = messages[1:] %}
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{%- else %}
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{%- set system_message = "You are a helpful AI Assistant that provides well-reasoned and detailed responses. You first think about the reasoning process as an internal monologue and then provide the user with the answer. Respond in the following format: <think>
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...
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</think>
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<answer>
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...
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</answer>" %}
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{%- endif %}
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{{- '<|system|>\n' + system_message + '\n' }}
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{%- for message in messages %}
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{%- if message['role'] == 'user' %}
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{{- '<|user|>\n' + message['content'] + '\n' }}
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{%- elif message['role'] == 'assistant' %}
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{{- '<|assistant|>\n' }}
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{% generation %}
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{%- if not loop.last %}
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{{- message['content'] + eos_token + '\n' }}
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{%- else %}
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{{- message['content'] + eos_token }}
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{%- endif %}
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{% endgeneration %}
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{%- endif %}
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{%- if loop.last and add_generation_prompt %}
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{{- '<|assistant|>\n' }}
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{%- endif %}
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{%- endfor %}
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config.json
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config.json
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{
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"architectures": [
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"Olmo2ForCausalLM"
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],
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"hidden_act": "silu",
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"hidden_size": 2048,
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train_results.json
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train_results.json
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training_args.bin
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training_args.bin
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vocab.json
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