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SMG0/Model4_withclasess-arabertv2_base_T2_WS_A100v2_F1__BL

sourceHugging Faceupdated 2y agoView on Hugging Face
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Model4withclasess-arabertv2baseT2WSA100v2F1__BL

This model is a fine-tuned version of aubmindlab/bert-base-arabertv02-twitter on an unknown dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.0770
  • —F1-micro: 0.8282
  • —Roc Auc: 0.9072
  • —Accuracy: 0.7912

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.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • —lrschedulertype: linear
  • —num_epochs: 20

Training results

Training LossEpochStepValidation LossF1-microRoc AucAccuracy
0.10281.05070.06440.79040.86390.7297
0.04762.010140.05560.81430.88280.7668
0.03083.015210.05700.82000.89290.7758
0.02064.020280.06240.81790.89790.7828
0.01345.025350.06960.81830.90160.7856
0.00976.030420.07430.82260.90520.7898
0.00777.035490.07790.81660.90390.7793
0.00548.040560.08090.82490.90630.7905
0.00459.045630.07700.82820.90720.7912
0.003610.050700.08120.82280.90490.7849
0.00311.055770.08740.82500.90720.7919
0.002512.060840.08860.82580.90670.7863

Framework versions

  • —Transformers 4.48.2
  • —Pytorch 2.5.1+cu124
  • —Tokenizers 0.21.0