metadata
license: mit
base_model: emilyalsentzer/Bio_ClinicalBERT
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: NLP-HIBA_DisTEMIST_fine_tuned_ClinicalBERT-pretrained-model
results: []
NLP-HIBA_DisTEMIST_fine_tuned_ClinicalBERT-pretrained-model
This model is a fine-tuned version of emilyalsentzer/Bio_ClinicalBERT on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4109
- Precision: 0.5413
- Recall: 0.5693
- F1: 0.5550
- Accuracy: 0.9254
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: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 71 | 0.2386 | 0.5723 | 0.5449 | 0.5583 | 0.9273 |
| No log | 2.0 | 142 | 0.3000 | 0.5767 | 0.5693 | 0.5730 | 0.9240 |
| No log | 3.0 | 213 | 0.2973 | 0.5882 | 0.5830 | 0.5856 | 0.9279 |
| No log | 4.0 | 284 | 0.3333 | 0.5222 | 0.5742 | 0.5470 | 0.9205 |
| No log | 5.0 | 355 | 0.3613 | 0.5012 | 0.5957 | 0.5444 | 0.9184 |
| No log | 6.0 | 426 | 0.3772 | 0.5516 | 0.5693 | 0.5603 | 0.9268 |
| No log | 7.0 | 497 | 0.4006 | 0.5574 | 0.5596 | 0.5585 | 0.9257 |
| 0.0539 | 8.0 | 568 | 0.4109 | 0.5413 | 0.5693 | 0.5550 | 0.9254 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1