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kanak8278/xlnet-large-cased-ner-food-combined-v2

sourceHugging Facemitupdated 3y agoView on Hugging Face
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xlnet-large-cased-ner-food-combined-v2

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

  • —Loss: 0.0681
  • —Precision: 0.8554
  • —Recall: 0.8743
  • —F1: 0.8647
  • —Accuracy: 0.9769

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: 5e-06
  • —trainbatchsize: 16
  • —evalbatchsize: 24
  • —seed: 42
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —num_epochs: 10

Training results

Training LossEpochStepValidation LossPrecisionRecallF1Accuracy
0.26061.125000.08220.79760.86640.83060.9712
0.08372.2510000.09550.76570.87640.81730.9683
0.07063.3715000.07320.83220.87140.85130.9750
0.06314.4920000.06810.85540.87430.86470.9769
0.05495.6225000.07130.83560.88680.86040.9754
0.05216.7430000.07000.84250.88630.86390.9759
0.04937.8735000.07210.84440.88590.86470.9763

Framework versions

  • —Transformers 4.27.4
  • —Pytorch 2.0.0+cu118
  • —Datasets 2.11.0
  • —Tokenizers 0.13.3