---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: SETH_5e-05_0404_ES6_strict
  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. -->

# SETH_5e-05_0404_ES6_strict

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: 0.0633
- Precision: 0.7953
- Recall: 0.8692
- F1: 0.8306
- Accuracy: 0.9864

## 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: 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: 2000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.3171        | 0.96  | 25   | 0.0921          | 0.6399    | 0.7676 | 0.6980 | 0.9759   |
| 0.0656        | 1.92  | 50   | 0.0588          | 0.7528    | 0.8227 | 0.7862 | 0.9796   |
| 0.04          | 2.88  | 75   | 0.0456          | 0.7641    | 0.8640 | 0.8110 | 0.9837   |
| 0.031         | 3.85  | 100  | 0.0481          | 0.7647    | 0.8726 | 0.8151 | 0.9840   |
| 0.0241        | 4.81  | 125  | 0.0443          | 0.7915    | 0.8623 | 0.8254 | 0.9857   |
| 0.0162        | 5.77  | 150  | 0.0469          | 0.8443    | 0.8399 | 0.8421 | 0.9868   |
| 0.0132        | 6.73  | 175  | 0.0487          | 0.8310    | 0.8296 | 0.8303 | 0.9865   |
| 0.013         | 7.69  | 200  | 0.0545          | 0.7692    | 0.8778 | 0.8199 | 0.9854   |
| 0.0091        | 8.65  | 225  | 0.0539          | 0.8093    | 0.8399 | 0.8243 | 0.9865   |
| 0.0071        | 9.62  | 250  | 0.0691          | 0.7820    | 0.8520 | 0.8155 | 0.9855   |
| 0.0049        | 10.58 | 275  | 0.0633          | 0.7953    | 0.8692 | 0.8306 | 0.9864   |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3