Shuning2/Qwen2.5-3B-Iterative-SFT-LoRA

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Qwen2.5-3B-Iterative-SFT

This model is a fine-tuned version of Qwen/Qwen2.5-3B-Instruct on the afm_iterative dataset.

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: 0.0001
• —trainbatchsize: 2
• —evalbatchsize: 8
• —seed: 42
• —gradientaccumulationsteps: 4
• —totaltrainbatch_size: 8
• —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• —lrschedulertype: linear
• —num_epochs: 1.0
• —mixedprecisiontraining: Native AMP

Training results

Framework versions

• —PEFT 0.17.1
• —Transformers 4.57.1
• —Pytorch 2.9.0+cu126
• —Datasets 4.0.0
• —Tokenizers 0.22.1