README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - source_data_nlp
metrics:
  - precision
  - recall
  - f1
model-index:
  - name: sd-panelization-v2
    results:
      - task:
          name: Token Classification
          type: token-classification
        dataset:
          name: source_data_nlp
          type: source_data_nlp
          args: PANELIZATION
        metrics:
          - name: Precision
            type: precision
            value: 0.9134245120169964
          - name: Recall
            type: recall
            value: 0.9494824016563147
          - name: F1
            type: f1
            value: 0.9311044937736871

sd-panelization-v2

This model is a fine-tuned version of michiyasunaga/BioLinkBERT-large on the source_data_nlp dataset. It achieves the following results on the evaluation set:

• Loss: 0.0050
• Accuracy Score: 0.9982
• Precision: 0.9134
• Recall: 0.9495
• F1: 0.9311

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: Adafactor
• lr_scheduler_type: linear
• num_epochs: 1.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy Score	Precision	Recall	F1
0.0048	1.0	431	0.0050	0.9982	0.9134	0.9495	0.9311

Framework versions

• Transformers 4.20.0
• Pytorch 1.11.0a0+bfe5ad2
• Datasets 1.17.0
• Tokenizers 0.12.1