---
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: 0.9426
- Precision: 0.8396
- Recall: 0.8182
- F1: 0.8282
- Accuracy: 0.8655

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.9585        | 1.0   | 510  | 0.5849          | 0.7825    | 0.8293 | 0.8002 | 0.8473   |
| 0.4334        | 2.0   | 1020 | 0.6323          | 0.8394    | 0.8127 | 0.8226 | 0.8625   |
| 0.281         | 3.0   | 1530 | 0.5389          | 0.8259    | 0.8476 | 0.8348 | 0.8704   |
| 0.2117        | 4.0   | 2040 | 0.7155          | 0.8381    | 0.8243 | 0.8297 | 0.8675   |
| 0.1556        | 5.0   | 2550 | 0.6981          | 0.8420    | 0.8411 | 0.8414 | 0.8729   |
| 0.1216        | 6.0   | 3060 | 0.9238          | 0.8441    | 0.8089 | 0.8237 | 0.8606   |
| 0.108         | 7.0   | 3570 | 0.8514          | 0.8334    | 0.8215 | 0.8270 | 0.8645   |
| 0.0817        | 8.0   | 4080 | 0.8539          | 0.8341    | 0.8245 | 0.8288 | 0.8660   |
| 0.0659        | 9.0   | 4590 | 0.9233          | 0.8441    | 0.8202 | 0.8313 | 0.8655   |
| 0.0588        | 10.0  | 5100 | 0.9426          | 0.8396    | 0.8182 | 0.8282 | 0.8655   |


### Framework versions

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