---
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: 2.0736
- Precision: 0.0187
- Recall: 0.125
- F1: 0.0326
- Accuracy: 0.1497

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 2.1138        | 1.0   | 510  | 2.0795          | 0.0041    | 0.125  | 0.0080 | 0.0329   |
| 2.1114        | 2.0   | 1020 | 2.0853          | 0.0194    | 0.125  | 0.0336 | 0.1551   |
| 2.106         | 3.0   | 1530 | 2.0806          | 0.0345    | 0.125  | 0.0541 | 0.2759   |
| 2.1015        | 4.0   | 2040 | 2.0758          | 0.0284    | 0.125  | 0.0462 | 0.2268   |
| 2.0997        | 5.0   | 2550 | 2.0808          | 0.0041    | 0.125  | 0.0080 | 0.0329   |
| 2.0998        | 6.0   | 3060 | 2.0754          | 0.0284    | 0.125  | 0.0462 | 0.2268   |
| 2.099         | 7.0   | 3570 | 2.0737          | 0.0194    | 0.125  | 0.0336 | 0.1551   |
| 2.0945        | 8.0   | 4080 | 2.0812          | 0.0045    | 0.125  | 0.0086 | 0.0358   |
| 2.0986        | 9.0   | 4590 | 2.0731          | 0.0187    | 0.125  | 0.0326 | 0.1497   |
| 2.0958        | 10.0  | 5100 | 2.0736          | 0.0187    | 0.125  | 0.0326 | 0.1497   |


### Framework versions

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