---
license: apache-2.0
base_model: bert-large-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_large_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_large_with_preprocessing_grid_search

This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0365
- Precision: 0.8410
- Recall: 0.8308
- F1: 0.8352
- Accuracy: 0.8753

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.9616        | 1.0   | 510  | 0.6482          | 0.7704    | 0.8009 | 0.7781 | 0.8360   |
| 0.4395        | 2.0   | 1020 | 0.7507          | 0.8422    | 0.7993 | 0.8157 | 0.8552   |
| 0.2995        | 3.0   | 1530 | 0.7064          | 0.8445    | 0.8213 | 0.8287 | 0.8684   |
| 0.2117        | 4.0   | 2040 | 0.7889          | 0.8262    | 0.8325 | 0.8245 | 0.8679   |
| 0.1805        | 5.0   | 2550 | 0.9295          | 0.8406    | 0.8161 | 0.8271 | 0.8670   |
| 0.1225        | 6.0   | 3060 | 0.9491          | 0.8429    | 0.8260 | 0.8333 | 0.8758   |
| 0.0983        | 7.0   | 3570 | 0.9901          | 0.8444    | 0.8299 | 0.8359 | 0.8773   |
| 0.0869        | 8.0   | 4080 | 1.0300          | 0.8377    | 0.8278 | 0.8319 | 0.8719   |
| 0.0745        | 9.0   | 4590 | 1.0220          | 0.8439    | 0.8341 | 0.8379 | 0.8773   |
| 0.0591        | 10.0  | 5100 | 1.0365          | 0.8410    | 0.8308 | 0.8352 | 0.8753   |


### Framework versions

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