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twhin-bert-large-finetuned-fintwitter-classification

This model is a fine-tuned version of Twitter/twhin-bert-large on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6936
  • Accuracy: 0.8903
  • F1: 0.8903
  • Precision: 0.8903
  • Recall: 0.8903

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
  • train_batch_size: 128
  • eval_batch_size: 128
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Precision Recall
No log 1.0 75 0.5087 0.7835 0.7594 0.7846 0.7835
No log 2.0 150 0.3652 0.8685 0.8696 0.8735 0.8685
No log 3.0 225 0.3452 0.8723 0.8739 0.8772 0.8723
No log 4.0 300 0.3332 0.8823 0.8830 0.8840 0.8823
No log 5.0 375 0.3618 0.8907 0.8909 0.8912 0.8907
No log 6.0 450 0.3995 0.8802 0.8807 0.8814 0.8802
0.2712 7.0 525 0.4459 0.8886 0.8888 0.8889 0.8886
0.2712 8.0 600 0.5018 0.8903 0.8897 0.8894 0.8903
0.2712 9.0 675 0.5457 0.8836 0.8844 0.8860 0.8836
0.2712 10.0 750 0.5562 0.8723 0.8725 0.8750 0.8723
0.2712 11.0 825 0.6080 0.8827 0.8827 0.8828 0.8827
0.2712 12.0 900 0.5886 0.8853 0.8852 0.8851 0.8853
0.2712 13.0 975 0.6021 0.8874 0.8878 0.8890 0.8874
0.0383 14.0 1050 0.5960 0.8853 0.8849 0.8846 0.8853
0.0383 15.0 1125 0.6393 0.8815 0.8819 0.8827 0.8815
0.0383 16.0 1200 0.6803 0.8844 0.8852 0.8865 0.8844
0.0383 17.0 1275 0.6839 0.8915 0.8915 0.8914 0.8915
0.0383 18.0 1350 0.6968 0.8907 0.8901 0.8899 0.8907
0.0383 19.0 1425 0.6971 0.8865 0.8870 0.8878 0.8865
0.0122 20.0 1500 0.6936 0.8903 0.8903 0.8903 0.8903

Framework versions

  • Transformers 4.25.1
  • Pytorch 1.13.0+cu116
  • Datasets 2.8.0
  • Tokenizers 0.13.2
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