README.md

metadata

library_name: transformers
base_model: dmis-lab/biobert-base-cased-v1.2
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: BioBERT-full-finetuned-ner-pablo
    results: []

BioBERT-full-finetuned-ner-pablo

This model is a fine-tuned version of dmis-lab/biobert-base-cased-v1.2 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0618
• Precision: 0.8316
• Recall: 0.8346
• F1: 0.8331
• Accuracy: 0.9809

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: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 2
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	231	0.0878	0.7579	0.8072	0.7818	0.9737
No log	2.0	462	0.0618	0.8316	0.8346	0.8331	0.9809

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.1+cu121
• Datasets 2.21.0
• Tokenizers 0.19.1