CoolFace
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DayCardoso/modernbert-base-multi-head

sourceHugging Faceapache-2.0updated 1y agoView on Hugging Face
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Model Card

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modernbert-base-multi-head

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

  • Loss: 0.6827
  • F1 Macro: 0.4188

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-06
  • trainbatchsize: 2
  • evalbatchsize: 2
  • seed: 42
  • gradientaccumulationsteps: 8
  • totaltrainbatch_size: 16
  • optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • lrschedulertype: linear
  • lrschedulerwarmup_ratio: 0.05
  • num_epochs: 20

Training results

Training LossEpochStepValidation LossF1 Macro
0.57881.015340.57830.0
0.56752.030680.57140.1304
0.54243.046020.53860.1952
0.5164.061360.54930.2382
0.49225.076700.60150.2394
0.47446.092040.54040.3192
0.44947.0107380.57460.3733
0.43538.0122720.56890.3396
0.41479.0138060.56950.3608
0.400610.0153400.64410.3871
0.384311.0168740.59380.3888
0.376312.0184080.61590.4054
0.360613.0199420.58310.4042
0.347814.0214760.61160.4056
0.344715.0230100.61690.3999
0.321516.0245440.64410.4150
0.319617.0260780.65300.4129
0.318418.0276120.66340.4192
0.306519.0291460.67910.4192
0.29820.0306800.68270.4188

Framework versions

  • Transformers 4.53.1
  • Pytorch 2.6.0+cu124
  • Datasets 2.14.4
  • Tokenizers 0.21.2