eternite/SFT_think_answer

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SFTthinkanswer

This model is a fine-tuned version of Qwen/Qwen2.5-VL-3B-Instruct on an unknown dataset. It achieves the following results on the evaluation set:

• —Loss: 0.0003

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: 16
• —totaltrainbatch_size: 32
• —totalevalbatch_size: 2
• —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• —lrschedulertype: linear
• —lrschedulerwarmup_steps: 0.05
• —num_epochs: 3

Training results

Framework versions

• —PEFT 0.19.1
• —Transformers 5.10.2
• —Pytorch 2.12.0+cu126
• —Datasets 5.0.0
• —Tokenizers 0.22.2