Biobert-base-cased-v1.2-finetuned-ner-CRAFT_es_en

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

• Loss: 0.1811
• Precision: 0.8555
• Recall: 0.8539
• F1: 0.8547
• Accuracy: 0.9706

Model description

This model performs Named Entity Recognition for 6 entity tags: Sequence, Cell, Protein, Gene, Taxon, and Chemical from the CRAFT(Colorado Richly Annotated Full Text) Corpus in Spanish and English. Entity tags have been normalized and replaced from the original three letter code to a full name e.g. B-Protein, I-Chemical.

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: 3e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.052	1.0	1360	0.1413	0.8300	0.8442	0.8370	0.9677
0.0199	2.0	2720	0.1673	0.8461	0.8458	0.8459	0.9689
0.011	3.0	4080	0.1647	0.8588	0.8528	0.8558	0.9704
0.0031	4.0	5440	0.1811	0.8555	0.8539	0.8547	0.9706

Framework versions

• Transformers 4.17.0
• Pytorch 1.10.0+cu111
• Datasets 1.18.4
• Tokenizers 0.11.6