README.md

metadata

base_model: dmis-lab/biobert-v1.1
tags:
  - generated_from_trainer
model-index:
  - name: JNLPBA_bioBERT_NER
    results: []

JNLPBA_bioBERT_NER

This model is a fine-tuned version of dmis-lab/biobert-v1.1 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.1433

• Seqeval classification report: precision recall f1-score support

     DNA       0.81      0.83      0.82      1593
     RNA       0.79      0.83      0.81      1400
  

  cell_line 0.77 0.82 0.79 1016 cell_type 0.98 0.96 0.97 37439 protein 0.85 0.86 0.85 2992

  micro avg 0.95 0.94 0.95 44440 macro avg 0.84 0.86 0.85 44440

weighted avg 0.95 0.94 0.95 44440

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: 2e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Seqeval classification report
0.2673	1.0	582	0.1492	precision recall f1-score support

     DNA       0.79      0.81      0.80      1593
     RNA       0.78      0.79      0.79      1400

cell_line 0.74 0.84 0.79 1016 cell_type 0.98 0.96 0.97 37439 protein 0.84 0.86 0.85 2992

micro avg 0.95 0.94 0.94 44440 macro avg 0.83 0.85 0.84 44440 weighted avg 0.95 0.94 0.94 44440 | | 0.1408 | 2.0 | 1164 | 0.1469 | precision recall f1-score support

     DNA       0.83      0.80      0.81      1593
     RNA       0.78      0.83      0.80      1400

cell_line 0.75 0.83 0.79 1016 cell_type 0.98 0.96 0.97 37439 protein 0.84 0.87 0.85 2992

micro avg 0.95 0.94 0.95 44440 macro avg 0.84 0.86 0.85 44440 weighted avg 0.95 0.94 0.95 44440 | | 0.1237 | 3.0 | 1746 | 0.1433 | precision recall f1-score support

     DNA       0.81      0.83      0.82      1593
     RNA       0.79      0.83      0.81      1400

cell_line 0.77 0.82 0.79 1016 cell_type 0.98 0.96 0.97 37439 protein 0.85 0.86 0.85 2992

micro avg 0.95 0.94 0.95 44440 macro avg 0.84 0.86 0.85 44440 weighted avg 0.95 0.94 0.95 44440 |

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.0+cu118
• Datasets 2.15.0
• Tokenizers 0.15.0