huner_ncbi_disease

This model is a fine-tuned version of bert-base-cased on the transformer_dataset_ner dataset. It achieves the following results on the evaluation set:

• eval_loss: 0.1707
• eval_precision: 0.8094
• eval_recall: 0.8577
• eval_f1: 0.8328
• eval_accuracy: 0.9829
• eval_runtime: 4.904
• eval_samples_per_second: 185.361
• eval_steps_per_second: 23.247
• epoch: 40.0
• step: 26680

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 50

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.0+cu121
• Datasets 2.16.1
• Tokenizers 0.15.1