medical_bert_tiny_asymmetric_old_dataset_v2

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medical_bert_tiny_asymmetric_old_dataset_v2

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

• Loss: 0.0096
• Accuracy: 0.9952
• Recall Weighted: 0.9952
• Precision Weighted: 0.9952
• F1 Weighted: 0.9952
• F1 Macro: 0.9931
• F1 Prescription: 0.9889
• F1 Lab Report: 0.9904
• F1 Others: 1.0
• False Alarm Rate: 0.0
• Cross Class Error: 0.0103

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

Training results

Framework versions

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