---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_without_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_without_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: 0.6213
- Precision: 0.8399
- Recall: 0.8622
- F1: 0.8498
- Accuracy: 0.8798

## 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: 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   | 257  | 0.6305          | 0.7254    | 0.8018 | 0.7512 | 0.8180   |
| 0.8689        | 2.0   | 514  | 0.4877          | 0.8120    | 0.8500 | 0.8245 | 0.8667   |
| 0.8689        | 3.0   | 771  | 0.4490          | 0.7911    | 0.8590 | 0.8148 | 0.8599   |
| 0.2702        | 4.0   | 1028 | 0.4748          | 0.8291    | 0.8689 | 0.8457 | 0.8730   |
| 0.2702        | 5.0   | 1285 | 0.5217          | 0.8326    | 0.8543 | 0.8413 | 0.8783   |
| 0.1505        | 6.0   | 1542 | 0.5288          | 0.8351    | 0.8650 | 0.8481 | 0.8754   |
| 0.1505        | 7.0   | 1799 | 0.5801          | 0.8417    | 0.8585 | 0.8487 | 0.8769   |
| 0.092         | 8.0   | 2056 | 0.5721          | 0.8402    | 0.8694 | 0.8535 | 0.8818   |
| 0.092         | 9.0   | 2313 | 0.6135          | 0.8453    | 0.8618 | 0.8522 | 0.8808   |
| 0.0723        | 10.0  | 2570 | 0.6213          | 0.8399    | 0.8622 | 0.8498 | 0.8798   |


### Framework versions

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