bert-biobert1

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

• eval_loss: 3.2066
• eval_model_preparation_time: 0.0032
• eval_precision: 0.0233
• eval_recall: 0.0765
• eval_f1: 0.0358
• eval_accuracy: 0.1289
• eval_runtime: 79.3742
• eval_samples_per_second: 34.747
• eval_steps_per_second: 2.18
• step: 0

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: 10

Framework versions

• Transformers 4.46.2
• Pytorch 2.5.1+cu121
• Datasets 3.1.0
• Tokenizers 0.20.3