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distilbert-base-uncased-finetuned-osdg

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.8193
  • F1 Score: 0.7962
  • Accuracy: 0.8434

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-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss F1 Score Accuracy
0.3769 1.0 1017 0.8258 0.7729 0.8257
0.2759 2.0 2034 0.8364 0.7773 0.8262
0.1412 3.0 3051 1.0203 0.7833 0.8379
0.1423 4.0 4068 1.1603 0.7683 0.8224
0.0939 5.0 5085 1.3029 0.7843 0.8329
0.0757 6.0 6102 1.3562 0.7931 0.8379
0.0801 7.0 7119 1.2925 0.7840 0.8395
0.0311 8.0 8136 1.4632 0.7750 0.8318
0.0263 9.0 9153 1.5760 0.7843 0.8312
0.0196 10.0 10170 1.5689 0.7890 0.8417
0.0313 11.0 11187 1.6034 0.7909 0.8417
0.0007 12.0 12204 1.6725 0.7889 0.8406
0.0081 13.0 13221 1.6463 0.7911 0.8395
0.0061 14.0 14238 1.7730 0.7861 0.8345
0.003 15.0 15255 1.8001 0.7847 0.8379
0.0002 16.0 16272 1.7328 0.7912 0.8434
0.0 17.0 17289 1.7914 0.8011 0.8489
0.0009 18.0 18306 1.7772 0.7958 0.8456
0.0 19.0 19323 1.8028 0.7958 0.8434
0.0 20.0 20340 1.8193 0.7962 0.8434

Framework versions

  • Transformers 4.19.2
  • Pytorch 1.11.0+cu113
  • Datasets 2.2.2
  • Tokenizers 0.12.1
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