MATH_training_Qwen_QwQ_32B_Preview
This model is a fine-tuned version of Qwen/Qwen2.5-0.5B-Instruct on the MATH_training_Qwen_QwQ_32B_Preview dataset.
It achieves the following results on the evaluation set:
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: 4
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 16
- 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: 2
Training results
| Training Loss |
Epoch |
Step |
Validation Loss |
| 0.4245 |
0.5988 |
200 |
0.4776 |
| 0.4159 |
1.1976 |
400 |
0.4649 |
| 0.405 |
1.7964 |
600 |
0.4576 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3