README.md

metadata

license: mit
base_model: Clinical-AI-Apollo/Medical-NER
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: Medical-NER
    results: []

Medical-NER

This model is a fine-tuned version of Clinical-AI-Apollo/Medical-NER on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.1694
• Precision: 0.9149
• Recall: 0.8666
• F1: 0.8901
• Accuracy: 0.9427

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.2
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.0013	1.0	4159	0.1694	0.9149	0.8666	0.8901	0.9427

Framework versions

• Transformers 4.37.0
• Pytorch 2.1.2
• Datasets 2.1.0
• Tokenizers 0.15.1