EMBO / SourceData_RolesMulti_v1_0_0_PubMedBERT_large

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Model's Last Updated: September 17 2025
token-classification

Introduction of SourceData_RolesMulti_v1_0_0_PubMedBERT_large

Model Details of SourceData_RolesMulti_v1_0_0_PubMedBERT_large

SourceData_RolesMulti_v1_0_0_PubMedBERT_large

This model is a fine-tuned version of microsoft/BiomedNLP-BiomedBERT-large-uncased-abstract on the source_data dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0068
  • Accuracy Score: 0.9981
  • Precision: 0.9613
  • Recall: 0.9695
  • F1: 0.9654
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: 16
  • eval_batch_size: 64
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • optimizer: Use adafactor and the args are: No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 1.0
Training results
Training Loss Epoch Step Validation Loss Accuracy Score Precision Recall F1
0.0046 0.9994 863 0.0068 0.9981 0.9613 0.9695 0.9654
Framework versions
  • Transformers 4.46.3
  • Pytorch 1.13.1+cu117
  • Datasets 3.1.0
  • Tokenizers 0.20.3

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SourceData_RolesMulti_v1_0_0_PubMedBERT_large install

SourceData_RolesMulti_v1_0_0_PubMedBERT_large is an open source model from GitHub that offers a free installation service, and any user can find SourceData_RolesMulti_v1_0_0_PubMedBERT_large on GitHub to install. At the same time, huggingface.co provides the effect of SourceData_RolesMulti_v1_0_0_PubMedBERT_large install, users can directly use SourceData_RolesMulti_v1_0_0_PubMedBERT_large installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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