metadata
base_model: medicalai/ClinicalBERT
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: working
results: []
working
This model is a fine-tuned version of medicalai/ClinicalBERT on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0108
- F1: 0.9834
- Roc Auc: 0.9930
- Accuracy: 0.9853
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| No log | 1.0 | 136 | 0.0223 | 0.9834 | 0.9930 | 0.9853 |
| No log | 2.0 | 272 | 0.0163 | 0.9881 | 0.9959 | 0.9926 |
| No log | 3.0 | 408 | 0.0137 | 0.9834 | 0.9930 | 0.9853 |
| 0.0216 | 4.0 | 544 | 0.0120 | 0.9834 | 0.9930 | 0.9853 |
| 0.0216 | 5.0 | 680 | 0.0108 | 0.9834 | 0.9930 | 0.9853 |
Framework versions
- Transformers 4.37.0
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0