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muhammadravi251001/fine-tuned-NLI-idk-mrc-nli-drop-with-xlm-roberta-large

sourceHugging Facemitupdated 3y agoView on Hugging Face
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Model Card

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fine-tuned-NLI-idk-mrc-nli-drop-with-xlm-roberta-large

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

  • —Loss: 0.0610
  • —Accuracy: 0.9777
  • —F1: 0.9777

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: 1e-05
  • —trainbatchsize: 8
  • —evalbatchsize: 8
  • —seed: 42
  • —gradientaccumulationsteps: 16
  • —totaltrainbatch_size: 128
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —num_epochs: 10

Training results

Training LossEpochStepValidation LossAccuracyF1
1.05810.5390.68550.50790.3506
0.72171.0780.21640.92930.9292
0.42391.51170.11410.96860.9686
0.14482.01560.09290.96600.9660
0.14482.51950.06770.97770.9777
0.1033.02340.09330.97510.9751
0.08263.52730.07230.97640.9764
0.05984.03120.06100.97770.9777

Framework versions

  • —Transformers 4.26.1
  • —Pytorch 1.13.1+cu117
  • —Datasets 2.2.0
  • —Tokenizers 0.13.2