metadata
library_name: transformers
license: mit
base_model: emilyalsentzer/Bio_ClinicalBERT
tags:
- generated_from_trainer
metrics:
- precision
- recall
model-index:
- name: lifechart-clinicalbert-classifier-hptuning
results: []
lifechart-clinicalbert-classifier-hptuning
This model is a fine-tuned version of emilyalsentzer/Bio_ClinicalBERT on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9974
- Macro F1: 0.7643
- Precision: 0.7646
- Recall: 0.7719
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: 3.388107847663499e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.12710648271608968
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Precision | Recall |
|---|---|---|---|---|---|---|
| 1.9942 | 1.0 | 1641 | 0.9834 | 0.7390 | 0.7307 | 0.7689 |
| 0.7735 | 2.0 | 3282 | 0.9188 | 0.7621 | 0.7545 | 0.7791 |
| 0.4206 | 3.0 | 4923 | 0.9974 | 0.7643 | 0.7646 | 0.7719 |
Framework versions
- Transformers 4.55.4
- Pytorch 2.8.0+cu128
- Datasets 4.0.0
- Tokenizers 0.21.4