---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: PubMedBERT-LitCovid-v1.2
  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. -->

# PubMedBERT-LitCovid-v1.2

This model is a fine-tuned version of [microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0998
- F1: 0.9200
- Roc Auc: 0.9529
- Accuracy: 0.7868

## 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: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:|
| 0.1017        | 1.0   | 2211  | 0.0897          | 0.9155 | 0.9492  | 0.7722   |
| 0.0742        | 2.0   | 4422  | 0.0868          | 0.9177 | 0.9508  | 0.7778   |
| 0.0559        | 3.0   | 6633  | 0.0903          | 0.9191 | 0.9521  | 0.7827   |
| 0.0396        | 4.0   | 8844  | 0.0955          | 0.9184 | 0.9512  | 0.7814   |
| 0.0282        | 5.0   | 11055 | 0.0998          | 0.9200 | 0.9529  | 0.7868   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3