---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: PubMedBERT-Large-LitCovid-v1.0
  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-Large-LitCovid-v1.0

This model is a fine-tuned version of [microsoft/BiomedNLP-PubMedBERT-large-uncased-abstract](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-large-uncased-abstract) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1044
- F1: 0.9021
- Roc Auc: 0.9367
- Accuracy: 0.8006

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.1103        | 1.0   | 6240 | 0.1044          | 0.9021 | 0.9367  | 0.8006   |


### Framework versions

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