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graf/Qwen3-4B-SFT-science-1e-5

sourceHugging Faceotherupdated 5mo agoView on Hugging Face
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Qwen3-4B-SFT-science-1e-5

This model is a fine-tuned version of Qwen/Qwen3-4B on the dolcisciencetrain dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.6778

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: 2
  • —evalbatchsize: 2
  • —seed: 42
  • —distributed_type: multi-GPU
  • —num_devices: 4
  • —gradientaccumulationsteps: 16
  • —totaltrainbatch_size: 128
  • —totalevalbatch_size: 8
  • —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • —lrschedulertype: cosine
  • —lrschedulerwarmup_steps: 0.05
  • —num_epochs: 3.0

Training results

Training LossEpochStepValidation Loss
0.80650.29852300.7250
0.67630.59694600.7040
0.70300.89546900.6914
0.61221.19339200.6877
0.63611.491811500.6827
0.64991.790313800.6778
0.58792.088216100.6838
0.53902.386718400.6826
0.60582.685220700.6820
0.60972.983623000.6816

Framework versions

  • —Transformers 5.0.0
  • —Pytorch 2.10.0+cu128
  • —Datasets 4.0.0
  • —Tokenizers 0.22.2