siddharthtumre / biobert-finetuned-ner

huggingface.co
Total runs: 43.2K
24-hour runs: 10.0K
7-day runs: 31.1K
30-day runs: 8.7K
Model's Last Updated: August 23 2022
token-classification

Introduction of biobert-finetuned-ner

Model Details of biobert-finetuned-ner

biobert-finetuned-ner

This model is a fine-tuned version of dmis-lab/biobert-base-cased-v1.2 on the jnlpba dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5113
  • Precision: 0.6551
  • Recall: 0.7646
  • F1: 0.7056
  • Accuracy: 0.9108
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: 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: 5
Training results
Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.1815 1.0 2319 0.2706 0.6538 0.7704 0.7073 0.9160
0.1226 2.0 4638 0.3230 0.6524 0.7675 0.7053 0.9118
0.0813 3.0 6957 0.3974 0.6483 0.7611 0.7002 0.9101
0.0521 4.0 9276 0.4529 0.6575 0.7652 0.7073 0.9121
0.0356 5.0 11595 0.5113 0.6551 0.7646 0.7056 0.9108
Framework versions
  • Transformers 4.21.1
  • Pytorch 1.12.1+cu113
  • Datasets 2.4.0
  • Tokenizers 0.12.1

Runs of siddharthtumre biobert-finetuned-ner on huggingface.co

43.2K
Total runs
10.0K
24-hour runs
28.0K
3-day runs
31.1K
7-day runs
8.7K
30-day runs

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