File size: 1,822 Bytes
9ec056a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 | ---
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
|