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9wimu9/xlm-roberta-large-finetuned-sinquad-v2

sourceHugging Facemitupdated 3y agoView on Hugging Face
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xlm-roberta-large-finetuned-sinquad-v2

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: 0.7850

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: 128
  • —evalbatchsize: 128
  • —seed: 42
  • —gradientaccumulationsteps: 4
  • —totaltrainbatch_size: 512
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —num_epochs: 10

Training results

Training LossEpochStepValidation Loss
1.50610.99231.3749
0.89761.98460.8803
0.75722.97690.7758
0.68544.0930.7380
0.59034.991160.7158
0.51145.981390.7311
0.42916.971620.7533
0.41138.01860.7650
0.35648.992090.7734
0.35169.892300.7850

Framework versions

  • —Transformers 4.30.0.dev0
  • —Pytorch 2.0.1+cu117
  • —Datasets 2.6.1
  • —Tokenizers 0.12.1

{'exact_match': 67.75914634146342, 'f1': 86.42992384115712}