medical_bert_tiny_asymmetric_old_dataset_v3

This model is a fine-tuned version of prajjwal1/bert-tiny on an unknown dataset. It achieves the following results on the evaluation set:

• eval_loss: 0.0062
• eval_accuracy: 0.9947
• eval_recall_weighted: 0.9947
• eval_precision_weighted: 0.9948
• eval_f1_weighted: 0.9947
• eval_f1_macro: 0.9926
• eval_f1_prescription: 0.9889
• eval_f1_lab_report: 0.9894
• eval_f1_others: 0.9996
• eval_false_alarm_rate: 0.0009
• eval_cross_class_error: 0.0103
• eval_runtime: 2.6043
• eval_samples_per_second: 801.365
• eval_steps_per_second: 12.671
• epoch: 2.0
• step: 1784

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: 0.0002
• train_batch_size: 8
• eval_batch_size: 64
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 16
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 0.1
• num_epochs: 5
• label_smoothing_factor: 0.1

Framework versions

• Transformers 5.0.0
• Pytorch 2.10.0+cu128
• Datasets 4.8.5
• Tokenizers 0.22.2