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ribesstefano/RuleBert-v0.3-k0

sourceHugging Facemitupdated 3y agoView on Hugging Face
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ribesstefano/RuleBert-v0.3-k0

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

  • —Loss: 0.3650
  • —F1: 0.4972
  • —Roc Auc: 0.6720
  • —Accuracy: 0.0

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: 5e-06
  • —trainbatchsize: 2
  • —evalbatchsize: 64
  • —seed: 42
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —training_steps: 8000
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepAccuracyF1Validation LossRoc Auc
0.4220.062500.00.49720.39940.6720
0.36060.125000.36040.49720.67200.0
0.33330.197500.35480.49720.67200.0
0.33040.2510000.35630.49720.67200.0
0.34160.3112500.36280.49720.67200.0
0.35580.3715000.36500.49720.67200.0

Framework versions

  • —Transformers 4.36.2
  • —Pytorch 2.1.0+cu121
  • —Datasets 2.16.1
  • —Tokenizers 0.15.0