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gasperpre/custom_model

sourceHugging Facemitupdated 2y agoView on Hugging Face
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custom_model

This model is a fine-tuned version of microsoft/mdeberta-v3-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0004
  • Accuracy: 1.0
  • Precision: 1.0
  • Recall: 1.0
  • F1: 1.0

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: 3e-05
  • trainbatchsize: 8
  • evalbatchsize: 8
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • lrschedulertype: linear
  • lrschedulerwarmup_ratio: 0.1
  • num_epochs: 8

Training results

Training LossEpochStepValidation LossAccuracyPrecisionRecallF1
0.68050.5556200.59650.760600.00
0.53061.1111400.48120.760600.00
0.38631.6667600.28570.760600.00
0.2342.2222800.17380.94371.00.76470.8667
0.05832.77781000.08270.98591.00.94120.9697
0.03143.33331200.00361.01.01.01.0
0.09263.88891400.08730.97181.00.88240.9375
0.00194.44441600.00071.01.01.01.0
0.05565.01800.00091.01.01.01.0
0.00185.55562000.04670.98591.00.94120.9697
0.00116.11112200.00051.01.01.01.0
0.00126.66672400.00041.01.01.01.0
0.00117.22222600.00041.01.01.01.0
0.00127.77782800.00041.01.01.01.0

Framework versions

  • Transformers 4.48.3
  • Pytorch 2.6.0+cu124
  • Datasets 3.4.1
  • Tokenizers 0.21.1