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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - EMBO/SourceData
metrics:
  - precision
  - recall
  - f1
model-index:
  - name: SourceData_GP-CHEM-ROLES_v_1-0-1_BioLinkBERT_large
    results:
      - task:
          name: Token Classification
          type: token-classification
        dataset:
          name: source_data
          type: source_data
          args: ROLES_MULTI
        metrics:
          - name: Precision
            type: precision
            value: 0.9542316038666404
          - name: Recall
            type: recall
            value: 0.9629703364523193
          - name: F1
            type: f1
            value: 0.958581054300436

SourceData_GP-CHEM-ROLES_v_1-0-1_BioLinkBERT_large

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

  • Loss: 0.0108
  • Accuracy Score: 0.9973
  • Precision: 0.9542
  • Recall: 0.9630
  • F1: 0.9586

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: 1.5e-05
  • train_batch_size: 32
  • eval_batch_size: 256
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • optimizer: Adafactor
  • lr_scheduler_type: linear
  • num_epochs: 1.0

Training results

Training Loss Epoch Step Validation Loss Accuracy Score Precision Recall F1
0.0073 1.0 863 0.0108 0.9973 0.9542 0.9630 0.9586

Framework versions

  • Transformers 4.20.1
  • Pytorch 1.11.0a0+bfe5ad2
  • Datasets 2.10.1
  • Tokenizers 0.12.1