CoolFace
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susuahi/results

sourceHugging Faceapache-2.0updated 10mo agoView on Hugging Face
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Model Card

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results

This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5025
  • Accuracy: 0.8652
  • F1: 0.9030

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: 5e-05
  • trainbatchsize: 16
  • evalbatchsize: 16
  • seed: 42
  • 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: 3

Training results

Training LossEpochStepValidation LossAccuracyF1
0.64750.2174500.60130.68630.8134
0.5240.43481000.58680.71080.8239
0.54620.65221500.51640.76470.8486
0.52120.86962000.49790.78680.8612
0.37951.08702500.42380.81130.8675
0.34911.30433000.43330.81370.8725
0.31691.52173500.36670.82840.8797
0.21471.73914000.36770.86030.9036
0.25521.95654500.35000.85290.8905
0.11612.17395000.46150.86520.9005
0.13182.39135500.52170.86030.9039
0.06172.60876000.48210.86760.9043
0.05232.82616500.50250.86520.9030

Framework versions

  • Transformers 4.57.3
  • Pytorch 2.9.0+cu126
  • Datasets 4.0.0
  • Tokenizers 0.22.1