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muhammadravi251001/fine-tuned-DatasetQAS-TYDI-QA-ID-with-xlm-roberta-large-without-ITTL-without-freeze-LR-1e-05

sourceHugging Facemitupdated 3y agoView on Hugging Face
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fine-tuned-DatasetQAS-TYDI-QA-ID-with-xlm-roberta-large-without-ITTL-without-freeze-LR-1e-05

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: 0.9538
  • —Exact Match: 69.0141
  • —F1: 82.7291

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 LossExact MatchF1
6.20630.5193.69747.922518.1433
6.20630.99382.567320.422530.5107
3.71061.5571.539748.415564.0947
3.71061.99761.207560.915574.9130
3.71062.5951.086761.267675.6856
1.41122.991140.974264.260678.6353
1.41123.51330.950267.781781.5092
0.95223.991520.918466.549380.7104
0.95224.51710.934167.253581.5452
0.95224.991900.935766.197281.2448
0.73345.52090.914967.605681.7638
0.73345.992280.913467.781782.2855
0.73346.52470.916769.190182.3011
0.59386.992660.945368.133882.0887
0.59387.52850.914568.485982.8642
0.52737.993040.940368.485982.5820
0.52738.53230.941568.838082.4565
0.52738.993420.953869.014182.7291

Framework versions

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