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
Downloads last month
12
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Dataset used to train EMBO/SourceData_GP-CHEM-ROLES_v_1-0-1_BioLinkBERT_large

Evaluation results