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---
library_name: transformers
license: apache-2.0
base_model: Qwen/Qwen2.5-7B-Instruct
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: DCFT-Stratos-Verified-114k-7B-4gpus
results: []
datasets:
- open-thoughts/open-thoughts-114k
---
<p align="center">
<img src="https://huggingface.co./datasets/open-thoughts/open-thoughts-114k/resolve/main/open_thoughts.png" width="50%">
</p>
# OpenThinker-7B
This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co./Qwen/Qwen2.5-7B-Instruct) on the
[OpenThoughts-114k dataset](https://huggingface.co./datasets/open-thoughts/OpenThoughts-114k) dataset.
The dataset is derived by distilling DeepSeek-R1 using the [data pipeline available on github](https://github.com/open-thoughts/open-thoughts).
More info about the dataset can be found on the dataset card at [OpenThoughts-114k dataset](https://huggingface.co./datasets/open-thoughts/open-thoughts-114k).
This model improves upon the [Bespoke-Stratos-7B model](https://huggingface.co./bespokelabs/Bespoke-Stratos-7B), which used 17k examples ([Bespoke-Stratos-17k dataset](https://huggingface.co./datasets/bespokelabs/Bespoke-Stratos-17k)).
The numbers reported in the table below are evaluated with our open-source tool [Evalchemy](https://github.com/mlfoundations/Evalchemy).
| | AIME2024 | MATH500 | GPQA-Diamond | LCB Easy v2 | LCB Medium v2 | LCB Hard v2 | LCB All v2 |
| --------------------------- | -------- | ------- | ------------ | ----------- | ------------- | ----------- | ---------- |
| OpenThinker-7B | 43.3 | 83.0 | 42.4 | 75.3 | 28.6 | 6.5 | 39.9 |
| Bespoke-Stratos-7B | 16.6 | 79.6 | 38.9 | 71.4 | 25.2 | 0.8 | 35.8 |
| DeepSeek-R1-Distill-Qwen-7B | 60 | 88.2 | 46.9 | 79.7 | 45.1 | 14.6 | 50.1 |
| gpt-4o-0513 | 10 | 75.8 | 46.5 | 87.4 | 42.7 | 8.9 | 50.5 |
| o1-mini | 63 | | 60 | 92.8 | 74.7 | 39.8 | 72.8 |
| | Open Weights | Open Data | Open Code |
|--|--------------|-----------| --------- |
|OpenThinker-7B|✅|[✅](https://huggingface.co./datasets/open-thoughts/OpenThoughts-114k)|[✅](https://github.com/open-thoughts/open-thoughts) |
|Bespoke-Stratos-7B|✅|[✅](https://huggingface.co./datasets/bespokelabs/Bespoke-Stratos-17k)|[✅](https://github.com/bespokelabsai/curator/tree/main/examples/bespoke-stratos-data-generation)|
|DeepSeek-R1-Distill-Qwen-7B|✅|❌|❌|
|gpt-4o-0513|-|❌|❌|❌|
|o1-mini|-|❌|❌|❌|
## Intended uses & limitations
Apache 2.0 License
## Training procedure
We used four 8xH100 nodes to train the model for 20 hours.
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 32
- gradient_accumulation_steps: 3
- total_train_batch_size: 96
- total_eval_batch_size: 256
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0
### Framework versions
- Transformers 4.46.1
- Pytorch 2.3.0
- Datasets 3.1.0
- Tokenizers 0.20.3
More info can be found in our repository: [https://github.com/open-thoughts/open-thoughts](https://github.com/open-thoughts/open-thoughts).
# Links
- 📊 [Open Thoughts Launch Blog Post](https://www.open-thoughts.ai/blog/launch)
- 📊 [Open Thoughts GitHub Repository](https://github.com/open-thoughts/open-thoughts)
- 🧠 [OpenThoughts-114k dataset](https://huggingface.co./datasets/open-thoughts/OpenThoughts-114k)
- 🤖 [OpenThinker-7B model](https://huggingface.co./open-thoughts/OpenThinker-7B) - this model.
- 📊 [Bespoke-Stratos Blog Post](https://www.bespokelabs.ai/blog/bespoke-stratos-the-unreasonable-effectiveness-of-reasoning-distillation)
- 🧠 [Bespoke-Stratos-17k dataset](https://huggingface.co./datasets/bespokelabs/Bespoke-Stratos-17k)
- 🤖 [Bespoke-Stratos-32B model](https://huggingface.co./bespokelabs/Bespoke-Stratos-32B)
- 🤖 [Bespoke-Stratos-7B model](https://huggingface.co./bespokelabs/Bespoke-Stratos-7B)
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