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paulo037/Qwen3-VL-2B-Instruct-legal-extraction-constrained

sourceHugging Faceapache-2.0updated 6mo agoView on Hugging Face
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Model Card

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Qwen3-VL-2B-Instruct-legal-extraction-constrained

This model is a fine-tuned version of Qwen/Qwen3-VL-2B-Instruct on an unknown dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.1706

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: 1
  • —evalbatchsize: 1
  • —seed: 14
  • —gradientaccumulationsteps: 8
  • —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
  • —lrschedulerwarmup_ratio: 0.03
  • —num_epochs: 1

Training results

Training LossEpochStepValidation Loss
0.23620.08082000.1888
0.19390.16164000.1836
0.20710.24246000.1864
0.20150.32328000.1816
0.19420.404110000.1790
0.17690.484912000.1790
0.20150.565714000.1759
0.20560.646516000.1742
0.19060.727318000.1741
0.18920.808120000.1723
0.1830.888922000.1707
0.18530.969724000.1706

Framework versions

  • —PEFT 0.17.1
  • —Transformers 4.57.0
  • —Pytorch 2.11.0a0+eb65b36914.nv26.02
  • —Datasets 4.1.1
  • —Tokenizers 0.22.2