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Ludo33/e5_General_2026_V2

sourceHugging Facemitupdated 2mo agoView on Hugging Face
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e5General2026_V2

This model is a fine-tuned version of intfloat/multilingual-e5-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2693
  • F1 Weighted: 0.8980

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: 2e-05
  • trainbatchsize: 16
  • evalbatchsize: 8
  • seed: 42
  • gradientaccumulationsteps: 2
  • totaltrainbatch_size: 32
  • 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: 10
  • mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossF1 Weighted
0.92591.010470.26130.8027
0.45652.020940.21300.8427
0.34003.031410.21240.8579
0.27214.041880.21090.8694
0.22495.052350.22900.8845
0.18946.062820.23440.8825
0.15687.073290.25070.8949
0.13818.083760.25560.8937
0.11769.094230.27430.8974
0.110810.0104700.26930.8980

Framework versions

  • Transformers 5.13.1
  • Pytorch 2.11.0+cu128
  • Datasets 4.0.0
  • Tokenizers 0.22.2