metadata
library_name: transformers
base_model: medicalai/ClinicalBERT
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: section-classification-v2
results: []
section-classification-v2
This model is a fine-tuned version of medicalai/ClinicalBERT on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9439
- Accuracy: 0.7473
- Precision: 0.6549
- Recall: 0.7473
- F1: 0.6918
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: 4
- eval_batch_size: 4
- seed: 42
- 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
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 434 | 1.1859 | 0.6909 | 0.6054 | 0.6909 | 0.6422 |
| 1.2827 | 2.0 | 868 | 1.1446 | 0.7258 | 0.6268 | 0.7258 | 0.6721 |
| 1.1164 | 3.0 | 1302 | 1.0256 | 0.75 | 0.6546 | 0.75 | 0.6946 |
| 1.0728 | 4.0 | 1736 | 0.9982 | 0.7473 | 0.6517 | 0.7473 | 0.6921 |
| 1.0206 | 5.0 | 2170 | 0.9582 | 0.7446 | 0.6530 | 0.7446 | 0.6891 |
| 0.9745 | 6.0 | 2604 | 0.9439 | 0.7473 | 0.6549 | 0.7473 | 0.6918 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Tokenizers 0.21.1