---
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: 0.9072
- Precision: 0.8332
- Recall: 0.8192
- F1: 0.8259
- Accuracy: 0.8660

## 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: 2e-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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.0741        | 1.0   | 510  | 0.6328          | 0.7761    | 0.8093 | 0.7820 | 0.8292   |
| 0.465         | 2.0   | 1020 | 0.5751          | 0.8326    | 0.8237 | 0.8265 | 0.8625   |
| 0.2979        | 3.0   | 1530 | 0.5442          | 0.8285    | 0.8482 | 0.8370 | 0.8719   |
| 0.2312        | 4.0   | 2040 | 0.6811          | 0.8434    | 0.8298 | 0.8350 | 0.8665   |
| 0.1609        | 5.0   | 2550 | 0.6873          | 0.8216    | 0.8338 | 0.8271 | 0.8635   |
| 0.14          | 6.0   | 3060 | 0.8476          | 0.8386    | 0.8175 | 0.8265 | 0.8640   |
| 0.1135        | 7.0   | 3570 | 0.8456          | 0.8302    | 0.8202 | 0.8249 | 0.8630   |
| 0.0973        | 8.0   | 4080 | 0.8595          | 0.8307    | 0.8186 | 0.8243 | 0.8625   |
| 0.0758        | 9.0   | 4590 | 0.8828          | 0.8306    | 0.8201 | 0.8251 | 0.8655   |
| 0.0669        | 10.0  | 5100 | 0.9072          | 0.8332    | 0.8192 | 0.8259 | 0.8660   |


### Framework versions

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