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

# pretoxtm-sentence-classifier

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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0802
- Precision: 0.9778
- Recall: 0.9801
- Accuracy: 0.9795
- F1: 0.9789

## 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: 7.755382954990098e-06
- 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 | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:------:|
| No log        | 1.0   | 257  | 0.1410          | 0.9593    | 0.9684 | 0.9636   | 0.9628 |
| 0.1997        | 2.0   | 514  | 0.0802          | 0.9778    | 0.9801 | 0.9795   | 0.9789 |
| 0.1997        | 3.0   | 771  | 0.1103          | 0.9824    | 0.9848 | 0.9841   | 0.9836 |
| 0.0514        | 4.0   | 1028 | 0.1139          | 0.9798    | 0.9829 | 0.9818   | 0.9813 |
| 0.0514        | 5.0   | 1285 | 0.1208          | 0.9804    | 0.9821 | 0.9818   | 0.9812 |


### Framework versions

- Transformers 4.39.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2