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Kuongan/xlm-roberta-base-pcm-finetuned

sourceHugging Facemitupdated 2y agoView on Hugging Face
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xlm-roberta-base-pcm-finetuned

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

  • —Loss: 0.4237
  • —F1: 0.4302
  • —Roc Auc: 0.6457
  • —Accuracy: 0.3081

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: 32
  • —evalbatchsize: 32
  • —seed: 42
  • —optimizer: Use adamwtorch with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • —lrschedulertype: cosine
  • —lrschedulerwarmup_steps: 100
  • —num_epochs: 20

Training results

Training LossEpochStepValidation LossF1Roc AucAccuracy
0.49491.01590.45920.10740.53190.1726
0.4282.03180.41540.29900.59720.2952
0.38043.04770.41160.35520.62470.3016
0.33294.06360.42370.43020.64570.3081
0.31165.07950.43020.42570.64170.3097
0.26846.09540.44450.42700.64630.3145
0.24337.011130.46190.42500.64550.3194
0.22218.012720.49650.41850.64950.3194

Framework versions

  • —Transformers 4.47.0
  • —Pytorch 2.5.1+cu121
  • —Datasets 3.2.0
  • —Tokenizers 0.21.0