---
license: mit
base_model: microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: NLP-HIBA_BiomedNLP-BiomedBERT-base-pretrained-model
  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. -->

# NLP-HIBA_BiomedNLP-BiomedBERT-base-pretrained-model

This model is a fine-tuned version of [microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1766
- Precision: 0.5977
- Recall: 0.5730
- F1: 0.5851
- Accuracy: 0.9539

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 71   | 0.1981          | 0.2581    | 0.2239 | 0.2398 | 0.9266   |
| No log        | 2.0   | 142  | 0.1616          | 0.4514    | 0.3692 | 0.4062 | 0.9444   |
| No log        | 3.0   | 213  | 0.1514          | 0.5233    | 0.4727 | 0.4967 | 0.9482   |
| No log        | 4.0   | 284  | 0.1863          | 0.4522    | 0.5546 | 0.4982 | 0.9352   |
| No log        | 5.0   | 355  | 0.1582          | 0.5665    | 0.5245 | 0.5447 | 0.9498   |
| No log        | 6.0   | 426  | 0.1571          | 0.5915    | 0.5305 | 0.5593 | 0.9529   |
| No log        | 7.0   | 497  | 0.1652          | 0.5849    | 0.5586 | 0.5714 | 0.9527   |
| 0.1311        | 8.0   | 568  | 0.1676          | 0.5858    | 0.5738 | 0.5798 | 0.9528   |
| 0.1311        | 9.0   | 639  | 0.1748          | 0.5990    | 0.5562 | 0.5768 | 0.9537   |
| 0.1311        | 10.0  | 710  | 0.1766          | 0.5977    | 0.5730 | 0.5851 | 0.9539   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1