---
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: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# NLP-HIBA_DisTEMIST_fine_tuned_ClinicalBERT-pretrained-model

This model is a fine-tuned version of [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2644
- Precision: 0.5331
- Recall: 0.5170
- F1: 0.5249
- Accuracy: 0.9319

## 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 71   | 0.2155          | 0.4953    | 0.4904 | 0.4929 | 0.9230   |
| No log        | 2.0   | 142  | 0.2250          | 0.5350    | 0.4910 | 0.5121 | 0.9314   |
| No log        | 3.0   | 213  | 0.2293          | 0.5373    | 0.5071 | 0.5218 | 0.9327   |
| No log        | 4.0   | 284  | 0.2374          | 0.5562    | 0.4978 | 0.5254 | 0.9344   |
| No log        | 5.0   | 355  | 0.2644          | 0.5331    | 0.5170 | 0.5249 | 0.9319   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1