---
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: 0.8335
- Precision: 0.8310
- Recall: 0.8213
- F1: 0.8256
- Accuracy: 0.8640

## 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: 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  | 0.6597          | 0.7225    | 0.7990 | 0.7429 | 0.7968   |
| 0.8033        | 2.0   | 510  | 0.5609          | 0.8155    | 0.8378 | 0.8247 | 0.8596   |
| 0.8033        | 3.0   | 765  | 0.5589          | 0.8119    | 0.8388 | 0.8231 | 0.8591   |
| 0.2454        | 4.0   | 1020 | 0.6598          | 0.8314    | 0.8273 | 0.8279 | 0.8625   |
| 0.2454        | 5.0   | 1275 | 0.6541          | 0.8103    | 0.8393 | 0.8229 | 0.8625   |
| 0.1332        | 6.0   | 1530 | 0.8259          | 0.8424    | 0.8213 | 0.8304 | 0.8665   |
| 0.1332        | 7.0   | 1785 | 0.7644          | 0.8298    | 0.8335 | 0.8312 | 0.8650   |
| 0.0907        | 8.0   | 2040 | 0.7939          | 0.8298    | 0.8255 | 0.8274 | 0.8660   |
| 0.0907        | 9.0   | 2295 | 0.8244          | 0.8310    | 0.8207 | 0.8255 | 0.8655   |
| 0.061         | 10.0  | 2550 | 0.8335          | 0.8310    | 0.8213 | 0.8256 | 0.8640   |


### Framework versions

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