---
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: 0.8911
- Precision: 0.8371
- Recall: 0.8239
- F1: 0.8296
- Accuracy: 0.8665

## 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: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 255  | 0.6320          | 0.7746    | 0.8197 | 0.7918 | 0.8360   |
| 0.7073        | 2.0   | 510  | 0.6156          | 0.7967    | 0.8232 | 0.8055 | 0.8473   |
| 0.7073        | 3.0   | 765  | 0.6028          | 0.8104    | 0.8381 | 0.8201 | 0.8552   |
| 0.2389        | 4.0   | 1020 | 0.6896          | 0.8296    | 0.8296 | 0.8290 | 0.8655   |
| 0.2389        | 5.0   | 1275 | 0.7462          | 0.8279    | 0.8353 | 0.8310 | 0.8694   |
| 0.1264        | 6.0   | 1530 | 0.9275          | 0.8488    | 0.8112 | 0.8271 | 0.8684   |
| 0.1264        | 7.0   | 1785 | 0.8244          | 0.8393    | 0.8313 | 0.8347 | 0.8729   |
| 0.0851        | 8.0   | 2040 | 0.8776          | 0.8281    | 0.8226 | 0.8249 | 0.8655   |
| 0.0851        | 9.0   | 2295 | 0.8838          | 0.8440    | 0.8278 | 0.8346 | 0.8675   |
| 0.0546        | 10.0  | 2550 | 0.8911          | 0.8371    | 0.8239 | 0.8296 | 0.8665   |


### Framework versions

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