---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: ec_classfication_0502_emilyalsentzer_Bio_ClinicalBERT
  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. -->

# ec_classfication_0502_emilyalsentzer_Bio_ClinicalBERT

This model is a fine-tuned version of [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4827
- F1: 0.7586

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 59   | 0.6180          | 0.5075 |
| No log        | 2.0   | 118  | 0.5676          | 0.6154 |
| No log        | 3.0   | 177  | 0.4982          | 0.8172 |
| No log        | 4.0   | 236  | 0.8061          | 0.7826 |
| No log        | 5.0   | 295  | 0.9337          | 0.7442 |
| No log        | 6.0   | 354  | 1.0500          | 0.7778 |
| No log        | 7.0   | 413  | 1.4362          | 0.6829 |
| No log        | 8.0   | 472  | 1.2663          | 0.7556 |
| 0.1798        | 9.0   | 531  | 1.2302          | 0.8000 |
| 0.1798        | 10.0  | 590  | 1.5106          | 0.7442 |
| 0.1798        | 11.0  | 649  | 1.4128          | 0.7640 |
| 0.1798        | 12.0  | 708  | 1.3024          | 0.8000 |
| 0.1798        | 13.0  | 767  | 1.5237          | 0.7442 |
| 0.1798        | 14.0  | 826  | 1.4852          | 0.7586 |
| 0.1798        | 15.0  | 885  | 1.4827          | 0.7586 |


### Framework versions

- Transformers 4.27.3
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.2