jialicheng / pubmedbert-abstract-ddi

huggingface.co
Total runs: 26
24-hour runs: 0
7-day runs: 0
30-day runs: 0
Model's Last Updated: May 20 2024
text-classification

Introduction of pubmedbert-abstract-ddi

Model Details of pubmedbert-abstract-ddi

ddi_42

This model is a fine-tuned version of microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2085
  • Accuracy: 0.9551
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: 32
  • eval_batch_size: 256
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10
Training results
Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 791 0.1986 0.9383
0.1723 2.0 1582 0.2700 0.9455
0.0772 3.0 2373 0.2085 0.9551
0.0516 4.0 3164 0.2970 0.9427
0.0516 5.0 3955 0.2620 0.9539
0.0341 6.0 4746 0.3973 0.9423
0.0203 7.0 5537 0.3637 0.9423
0.0146 8.0 6328 0.4154 0.9451
0.007 9.0 7119 0.4219 0.9463
0.007 10.0 7910 0.4098 0.9447
Framework versions
  • Transformers 4.39.3
  • Pytorch 2.2.2+cu118
  • Datasets 2.18.0
  • Tokenizers 0.15.2

Runs of jialicheng pubmedbert-abstract-ddi on huggingface.co

26
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3-day runs
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7-day runs
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