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jangmin/rectifier-goods-name-xlm-roberta

sourceHugging Facemitupdated 3y agoView on Hugging Face
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refine-good-name-xlm-roberta

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: 0.2236
  • F1: 0.8688

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: 64
  • evalbatchsize: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • num_epochs: 6

Training results

Training LossEpochStepValidation LossF1
0.26181.05530.23570.8314
0.20252.011060.22090.8661
0.1863.016590.20750.8588
0.1624.022120.22340.8609
0.14285.027650.22330.8700
0.13286.033180.22360.8688

Framework versions

  • Transformers 4.32.0.dev0
  • Pytorch 2.0.0
  • Datasets 2.14.0
  • Tokenizers 0.13.3