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 (MT translated) 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.

This model is trained on augmented data created using Entity Replacement. 20% of the entities were replaced using a list of entities for each entity tag obtained from the official ontologies for each entity class. Three datasets (original, augmented, MT translated CRAFT) were concatenated.

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
0.0549	1.0	4078	0.1673	0.8056	0.8112	0.8084	0.9640
0.0233	2.0	8156	0.1733	0.8321	0.8244	0.8283	0.9662
0.0101	3.0	12234	0.1972	0.8336	0.8391	0.8363	0.9678
0.0036	4.0	16312	0.2251	0.8276	0.8411	0.8343	0.9676

Framework versions

Transformers 4.17.0
Pytorch 1.10.0+cu111
Datasets 2.0.0
Tokenizers 0.11.6

StivenLancheros/biobert-base-cased-v1.2-finetuned-ner-CRAFT_Augmented_ES

biobert-base-cased-v1.2-finetuned-ner-CRAFT_Augmented_ES

Model description