bert-base-medmentions

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bert-base-medmentions

This model is a fine-tuned version of bert-base-uncased on the Ben10x/MedMentions-NER dataset. It achieves the following results on the evaluation set:

• Loss: 1.5156
• Precision: 0.5821
• Recall: 0.6344
• F1: 0.6071
• Accuracy: 0.8689

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Use OptimizerNames.ADAFACTOR and the args are: No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 15.0
• label_smoothing_factor: 0.2

Training results

Framework versions

• Transformers 4.50.3
• Pytorch 2.6.0+cu124
• Datasets 3.5.0
• Tokenizers 0.21.1