---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: Yepes_0.0001_29_03
  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. -->

# Yepes_0.0001_29_03

This model is a fine-tuned version of [microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1553
- Precision: 0.5294
- Recall: 0.4091
- F1: 0.4615
- Accuracy: 0.9756

## 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: 0.0001
- 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
- training_steps: 500

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.3757        | 5.0   | 25   | 0.1967          | 0.0       | 0.0    | 0.0    | 0.9697   |
| 0.1852        | 10.0  | 50   | 0.1952          | 0.0       | 0.0    | 0.0    | 0.9697   |
| 0.1766        | 15.0  | 75   | 0.1572          | 0.0       | 0.0    | 0.0    | 0.9697   |
| 0.1231        | 20.0  | 100  | 0.1386          | 0.0       | 0.0    | 0.0    | 0.9697   |
| 0.0827        | 25.0  | 125  | 0.1293          | 0.3846    | 0.2557 | 0.3072 | 0.9729   |
| 0.0422        | 30.0  | 150  | 0.1563          | 0.4545    | 0.2841 | 0.3497 | 0.9744   |
| 0.0205        | 35.0  | 175  | 0.1520          | 0.4138    | 0.2727 | 0.3288 | 0.9744   |
| 0.0102        | 40.0  | 200  | 0.1496          | 0.5124    | 0.3523 | 0.4175 | 0.9758   |
| 0.0062        | 45.0  | 225  | 0.1514          | 0.5522    | 0.4205 | 0.4774 | 0.9763   |
| 0.0047        | 50.0  | 250  | 0.1509          | 0.5581    | 0.4091 | 0.4721 | 0.9764   |
| 0.0035        | 55.0  | 275  | 0.1553          | 0.5294    | 0.4091 | 0.4615 | 0.9756   |


### Framework versions

- Transformers 4.27.4
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2