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: 0.2634
- Precision: 0.4559
- Recall: 0.4616
- F1: 0.4587
- Accuracy: 0.9334
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 | 0.2011 | 0.3859 | 0.3371 | 0.3598 | 0.9297 |
| No log | 2.0 | 142 | 0.1970 | 0.3956 | 0.3894 | 0.3925 | 0.9283 |
| No log | 3.0 | 213 | 0.2041 | 0.4140 | 0.3977 | 0.4057 | 0.9307 |
| No log | 4.0 | 284 | 0.2167 | 0.4379 | 0.4110 | 0.4240 | 0.9348 |
| No log | 5.0 | 355 | 0.2293 | 0.4430 | 0.4159 | 0.4290 | 0.9338 |
| No log | 6.0 | 426 | 0.2447 | 0.4615 | 0.4375 | 0.4492 | 0.9356 |
| No log | 7.0 | 497 | 0.2587 | 0.4601 | 0.4500 | 0.4550 | 0.9342 |
| 0.0861 | 8.0 | 568 | 0.2634 | 0.4559 | 0.4616 | 0.4587 | 0.9334 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1