MATH_training_Qwen_QwQ_32B_Preview
This model is a fine-tuned version of TaiGary/llama3.2_3b_OpenMathInstruct-2_100k on the MATH_training_Qwen_QwQ_32B_Preview dataset. It achieves the following results on the evaluation set:
- Loss: 0.4267
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: 2
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 8
- 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 |
|---|---|---|---|
| 0.4378 | 0.2999 | 200 | 0.4793 |
| 0.4611 | 0.5997 | 400 | 0.4510 |
| 0.4964 | 0.8996 | 600 | 0.4300 |
| 0.3247 | 1.1994 | 800 | 0.4394 |
| 0.2468 | 1.4993 | 1000 | 0.4303 |
| 0.2096 | 1.7991 | 1200 | 0.4272 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3
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Model tree for cutelemonlili/llama3.2_3b_OpenMathInstruct-2_100k_MATH_training_Qwen_QwQ_32B_Preview
Base model
TaiGary/llama3.2_3b_OpenMathInstruct-2_100k