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FrinzTheCoder/xlm-roberta-base-tir

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

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: 0.1727
  • —Accuracy: 0.8480
  • —F1 Binary: 0.0
  • —Precision: 0.0
  • —Recall: 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: 3e-05
  • —trainbatchsize: 32
  • —evalbatchsize: 8
  • —seed: 42
  • —optimizer: Use adamwtorch with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • —lrschedulertype: linear
  • —lrschedulerwarmup_steps: 55
  • —num_epochs: 4

Training results

Training LossEpochStepValidation LossAccuracyF1 BinaryPrecisionRecall
0.17721.05520.17590.15200.26380.15201.0
0.17442.011040.17250.84800.00.00.0
0.17353.016560.17130.84800.00.00.0
0.17434.022080.17270.84800.00.00.0

Framework versions

  • —Transformers 4.48.0
  • —Pytorch 2.5.1+cu124
  • —Datasets 3.1.0
  • —Tokenizers 0.21.0