README.md

metadata

tags:
  - generated_from_trainer
datasets:
  - ncbi_disease
metrics:
  - precision
  - recall
  - f1
  - accuracy
model_index:
  - name: biobert_v1.1_pubmed-finetuned-ner-finetuned-ner
    results:
      - task:
          name: Token Classification
          type: token-classification
        dataset:
          name: ncbi_disease
          type: ncbi_disease
          args: ncbi_disease
        metric:
          name: Accuracy
          type: accuracy
          value: 0.9829142288061745
base_model: fidukm34/biobert_v1.1_pubmed-finetuned-ner

biobert_v1.1_pubmed-finetuned-ner-finetuned-ner

This model is a fine-tuned version of fidukm34/biobert_v1.1_pubmed-finetuned-ner on the ncbi_disease dataset. It achieves the following results on the evaluation set:

• Loss: 0.0715
• Precision: 0.8464
• Recall: 0.8872
• F1: 0.8663
• Accuracy: 0.9829

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
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	340	0.0715	0.8464	0.8872	0.8663	0.9829

Framework versions

• Transformers 4.8.1
• Pytorch 1.9.0+cu102
• Datasets 1.11.0
• Tokenizers 0.10.3