StivenLancheros/roberta-base-biomedical-clinical-es-finetuned-ner-CRAFT_Augmented_EN

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roberta-base-biomedical-clinical-es-finetuned-ner-CRAFTAugmentedEN

This model is a fine-tuned version of PlanTL-GOB-ES/roberta-base-biomedical-clinical-es on the CRAFT dataset. It achieves the following results on the evaluation set:

• —Loss: 0.2276
• —Precision: 0.8078
• —Recall: 0.8258
• —F1: 0.8167
• —Accuracy: 0.9629

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 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. Both datasets (original, augmented) 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
• —trainbatchsize: 8
• —evalbatchsize: 8
• —seed: 42
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —num_epochs: 4

Training results

Framework versions

• —Transformers 4.17.0
• —Pytorch 1.10.0+cu111
• —Datasets 2.0.0
• —Tokenizers 0.11.6