zhengbang0707/Qwen3.5-9B-eSFT

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Qwen3.5-9B-full-eSFT

This model is a fine-tuned version of Qwen/Qwen3.5-9B on the vlguardQwen3.5-9BeSFT dataset. It achieves the following results on the evaluation set:

• —Loss: 1.1175

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
• —trainbatchsize: 1
• —evalbatchsize: 1
• —seed: 42
• —distributed_type: multi-GPU
• —num_devices: 2
• —gradientaccumulationsteps: 128
• —totaltrainbatch_size: 256
• —totalevalbatch_size: 2
• —optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
• —lrschedulertype: cosine
• —lrschedulerwarmup_steps: 0.03
• —num_epochs: 3.0

Training results

Framework versions

• —Transformers 5.6.0
• —Pytorch 2.5.1+cu121
• —Datasets 4.0.0
• —Tokenizers 0.22.2