jialicheng / ddi-pubmedbert-abstract

huggingface.co
Total runs: 24
24-hour runs: 0
7-day runs: 3
30-day runs: 17
Model's Last Updated: December 27 2024
text-classification

Introduction of ddi-pubmedbert-abstract

Model Details of ddi-pubmedbert-abstract

pubmedbert-abstract

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: 0.4618
  • Accuracy: 0.9501
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: 20
Training results
Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 791 0.2340 0.9386
0.1776 2.0 1582 0.2716 0.9419
0.0855 3.0 2373 0.2730 0.9431
0.0627 4.0 3164 0.3323 0.9382
0.0627 5.0 3955 0.3308 0.9451
0.0463 6.0 4746 0.3986 0.9412
0.0308 7.0 5537 0.4211 0.9419
0.0312 8.0 6328 0.3616 0.9437
0.0221 9.0 7119 0.4310 0.9396
0.0221 10.0 7910 0.4222 0.9438
0.0181 11.0 8701 0.4185 0.9445
0.0141 12.0 9492 0.4678 0.9456
0.0133 13.0 10283 0.4027 0.9503
0.0082 14.0 11074 0.4504 0.9473
0.0082 15.0 11865 0.4760 0.9505
0.0052 16.0 12656 0.4573 0.9449
0.0042 17.0 13447 0.4356 0.9522
0.0037 18.0 14238 0.4577 0.9487
0.0024 19.0 15029 0.4642 0.9493
0.0024 20.0 15820 0.4618 0.9501
Framework versions
  • Transformers 4.39.3
  • Pytorch 2.2.2+cu118
  • Datasets 2.18.0
  • Tokenizers 0.15.2

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

24
Total runs
0
24-hour runs
0
3-day runs
3
7-day runs
17
30-day runs

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