sft
This model is a fine-tuned version of Qwen/Qwen2.5-Math-1.5B-Instruct on the qwen_train_data dataset. It achieves the following results on the evaluation set:
- Loss: 0.0376
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
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5.0
Training results
Framework versions
- Transformers 4.49.0
- Pytorch 2.2.0+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for Yongce/qwen_2_Math_SFT_symbolic_reasoning
Base model
Qwen/Qwen2.5-1.5B
Finetuned
Qwen/Qwen2.5-Math-1.5B
Finetuned
Qwen/Qwen2.5-Math-1.5B-Instruct