---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_with_preprocessing_grid_search
  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. -->

# BERT_with_preprocessing_grid_search

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8836
- Precision: 0.8262
- Recall: 0.8258
- F1: 0.8249
- Accuracy: 0.8724

## 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: 3e-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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.047         | 1.0   | 510  | 0.6171          | 0.7493    | 0.8057 | 0.7716 | 0.8336   |
| 0.4348        | 2.0   | 1020 | 0.4954          | 0.8056    | 0.8646 | 0.8296 | 0.8714   |
| 0.2818        | 3.0   | 1530 | 0.6252          | 0.8181    | 0.8323 | 0.8212 | 0.8660   |
| 0.1793        | 4.0   | 2040 | 0.7381          | 0.8216    | 0.8258 | 0.8227 | 0.8733   |
| 0.1356        | 5.0   | 2550 | 0.8601          | 0.8161    | 0.8219 | 0.8165 | 0.8660   |
| 0.1023        | 6.0   | 3060 | 0.8526          | 0.8363    | 0.8299 | 0.8307 | 0.8758   |
| 0.0944        | 7.0   | 3570 | 0.8459          | 0.8234    | 0.8298 | 0.8251 | 0.8729   |
| 0.0631        | 8.0   | 4080 | 0.8519          | 0.8212    | 0.8325 | 0.8252 | 0.8714   |
| 0.0602        | 9.0   | 4590 | 0.8756          | 0.8200    | 0.8267 | 0.8226 | 0.8719   |
| 0.0532        | 10.0  | 5100 | 0.8836          | 0.8262    | 0.8258 | 0.8249 | 0.8724   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3