---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: PubMedBERT-LitCovid-v1.1
  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-v1.1

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: 0.1198
- F1: 0.8985
- Roc Auc: 0.9368
- Accuracy: 0.7937

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.1187        | 1.0   | 1560 | 0.1141          | 0.8923 | 0.9335  | 0.7819   |
| 0.0976        | 2.0   | 3120 | 0.1063          | 0.8983 | 0.9325  | 0.7924   |
| 0.0702        | 3.0   | 4680 | 0.1147          | 0.8970 | 0.9420  | 0.7839   |
| 0.0534        | 4.0   | 6240 | 0.1198          | 0.8985 | 0.9368  | 0.7937   |
| 0.0391        | 5.0   | 7800 | 0.1266          | 0.8982 | 0.9384  | 0.7902   |


### Framework versions

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