Numina_QwQ_5k
This model is a fine-tuned version of Qwen/Qwen2.5-Math-7B on the Numina_QwQ_5k dataset. It achieves the following results on the evaluation set:
- Loss: 0.3973
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 4
- total_eval_batch_size: 4
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.3313 | 0.8065 | 100 | 0.3167 |
| 0.2301 | 1.6129 | 200 | 0.3129 |
| 0.1709 | 2.4194 | 300 | 0.3392 |
| 0.1012 | 3.2258 | 400 | 0.3712 |
| 0.0717 | 4.0323 | 500 | 0.3763 |
| 0.0587 | 4.8387 | 600 | 0.3976 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.6.0+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3
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