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
OpenThinker-7B
This model is a fine-tuned version of Qwen/Qwen2.5-7B-Instruct on the OpenThoughts-114k dataset dataset.
The dataset is derived by distilling DeepSeek-R1 using the data pipeline available on github. More info about the dataset can be found on the dataset card at OpenThoughts-114k dataset.
This model improves upon the Bespoke-Stratos-7B model, which used 17k examples (Bespoke-Stratos-17k dataset). The numbers reported in the table below are evaluated with our open-source tool Evalchemy.
| AIME24 | MATH500 | GPQA-Diamond | LCBv2 Easy | LCBv2 Medium | LCBv2 Hard | LCBv2 All | |
|---|---|---|---|---|---|---|---|
| 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 | 85.6 | 60 | 92.8 | 74.7 | 39.8 | 72.8 |
We are fully open-source. Our model weights, datasets, data generation code, evaluation code, and training code are all publicly available.
| Open Weights | Open Data | Open Code | |
|---|---|---|---|
| OpenThinker-7B | ✅ | ✅ | ✅ |
| Bespoke-Stratos-7B | ✅ | ✅ | ✅ |
| 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.