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nhatha2004/DSC_xlm-roberta-large-xnli_finetuned

sourceHugging Facemitupdated 1y agoView on Hugging Face
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DSCxlm-roberta-large-xnlifinetuned

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

  • —Loss: 0.8773
  • —Accuracy: 0.7893
  • —F1 Macro: 0.7907

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: 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
  • —lrschedulerwarmup_steps: 100
  • —num_epochs: 20

Training results

Training LossEpochStepValidation LossAccuracyF1 Macro
0.65781.03500.62390.78210.7833
0.52122.07000.62090.76640.7626
0.43033.010500.71220.78140.7837
0.28824.014000.87730.78930.7907
0.18915.017501.18750.77290.7740
0.21846.021001.37310.75710.7555
0.11767.024501.50500.77860.7782
0.10518.028001.63440.7850.7846

Framework versions

  • —Transformers 4.52.4
  • —Pytorch 2.6.0+cu124
  • —Datasets 3.6.0
  • —Tokenizers 0.21.2