---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: Bio_ClinicalBERT_fold_1_binary_v1
  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. -->

# Bio_ClinicalBERT_fold_1_binary_v1

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: 1.7063
- F1: 0.8114

## 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: 25

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 288  | 0.4168          | 0.7949 |
| 0.3981        | 2.0   | 576  | 0.4124          | 0.8137 |
| 0.3981        | 3.0   | 864  | 0.6691          | 0.8002 |
| 0.1779        | 4.0   | 1152 | 0.8402          | 0.8122 |
| 0.1779        | 5.0   | 1440 | 0.9786          | 0.8007 |
| 0.082         | 6.0   | 1728 | 1.0425          | 0.7981 |
| 0.0332        | 7.0   | 2016 | 1.2070          | 0.8006 |
| 0.0332        | 8.0   | 2304 | 1.3305          | 0.8028 |
| 0.0149        | 9.0   | 2592 | 1.4515          | 0.8009 |
| 0.0149        | 10.0  | 2880 | 1.3826          | 0.8160 |
| 0.01          | 11.0  | 3168 | 1.5267          | 0.7963 |
| 0.01          | 12.0  | 3456 | 1.5158          | 0.8112 |
| 0.0084        | 13.0  | 3744 | 1.5919          | 0.7998 |
| 0.0027        | 14.0  | 4032 | 1.6206          | 0.8060 |
| 0.0027        | 15.0  | 4320 | 1.6861          | 0.8014 |
| 0.0061        | 16.0  | 4608 | 1.6660          | 0.8001 |
| 0.0061        | 17.0  | 4896 | 1.5061          | 0.8054 |
| 0.0133        | 18.0  | 5184 | 1.5813          | 0.8025 |
| 0.0133        | 19.0  | 5472 | 1.6314          | 0.7968 |
| 0.0032        | 20.0  | 5760 | 1.6282          | 0.8117 |
| 0.0007        | 21.0  | 6048 | 1.6378          | 0.8153 |
| 0.0007        | 22.0  | 6336 | 1.6710          | 0.8033 |
| 0.0018        | 23.0  | 6624 | 1.6999          | 0.8066 |
| 0.0018        | 24.0  | 6912 | 1.7045          | 0.8109 |
| 0.0001        | 25.0  | 7200 | 1.7063          | 0.8114 |


### Framework versions

- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1