metadata

library_name: transformers
license: mit
base_model: microsoft/biogpt
tags:
  - generated_from_trainer
datasets:
  - ncbi_disease
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: biogpt-ner
    results:
      - task:
          name: Token Classification
          type: token-classification
        dataset:
          name: ncbi_disease
          type: ncbi_disease
          config: ncbi_disease
          split: validation
          args: ncbi_disease
        metrics:
          - name: Precision
            type: precision
            value: 0.38144329896907214
          - name: Recall
            type: recall
            value: 0.4239583333333333
          - name: F1
            type: f1
            value: 0.40157868771583616
          - name: Accuracy
            type: accuracy
            value: 0.9519533004041311

biogpt-ner

This model is a fine-tuned version of microsoft/biogpt on the ncbi_disease dataset. It achieves the following results on the evaluation set:

Loss: 0.1530
Precision: 0.3814
Recall: 0.4240
F1: 0.4016
Accuracy: 0.9520

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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Framework versions

Transformers 4.51.2
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1