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: 0.2557
- Precision: 0.4943
- Recall: 0.5046
- F1: 0.4994
- Accuracy: 0.9407
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: 12
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 71 | 0.2423 | 0.1951 | 0.1433 | 0.1653 | 0.9109 |
| No log | 2.0 | 142 | 0.2177 | 0.2905 | 0.3474 | 0.3164 | 0.9138 |
| No log | 3.0 | 213 | 0.1822 | 0.3912 | 0.3701 | 0.3804 | 0.9325 |
| No log | 4.0 | 284 | 0.1845 | 0.3839 | 0.4367 | 0.4086 | 0.9298 |
| No log | 5.0 | 355 | 0.2033 | 0.4533 | 0.4271 | 0.4398 | 0.9367 |
| No log | 6.0 | 426 | 0.2005 | 0.4535 | 0.4736 | 0.4633 | 0.9365 |
| No log | 7.0 | 497 | 0.2297 | 0.4352 | 0.5155 | 0.4720 | 0.9321 |
| 0.1436 | 8.0 | 568 | 0.2236 | 0.4854 | 0.4656 | 0.4753 | 0.9395 |
| 0.1436 | 9.0 | 639 | 0.2335 | 0.4935 | 0.5101 | 0.5016 | 0.9397 |
| 0.1436 | 10.0 | 710 | 0.2413 | 0.4829 | 0.5075 | 0.4949 | 0.9405 |
| 0.1436 | 11.0 | 781 | 0.2557 | 0.4849 | 0.5239 | 0.5036 | 0.9383 |
| 0.1436 | 12.0 | 852 | 0.2557 | 0.4943 | 0.5046 | 0.4994 | 0.9407 |
Framework versions
- Transformers 4.35.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1