---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: training-5
  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. -->

# training-5

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co./bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0341
- Accuracy: 0.9952
- Precision: 0.9982
- Recall: 0.9841
- F1: 0.9911

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 0.25  | 151  | 0.0468          | 0.9923   | 1.0       | 0.9717 | 0.9856 |
| No log        | 0.5   | 302  | 0.0497          | 0.9908   | 0.9840    | 0.9823 | 0.9832 |
| No log        | 0.75  | 453  | 0.0571          | 0.9918   | 1.0       | 0.9699 | 0.9847 |
| No log        | 1.0   | 604  | 0.0319          | 0.9961   | 1.0       | 0.9858 | 0.9929 |
| 0.0471        | 1.25  | 755  | 0.0353          | 0.9952   | 0.9982    | 0.9841 | 0.9911 |
| 0.0471        | 1.5   | 906  | 0.0346          | 0.9942   | 0.9929    | 0.9858 | 0.9893 |
| 0.0471        | 1.75  | 1057 | 0.0678          | 0.9899   | 0.9772    | 0.9858 | 0.9815 |
| 0.0471        | 2.0   | 1208 | 0.0380          | 0.9952   | 1.0       | 0.9823 | 0.9911 |
| 0.0156        | 2.25  | 1359 | 0.0362          | 0.9952   | 1.0       | 0.9823 | 0.9911 |
| 0.0156        | 2.5   | 1510 | 0.0388          | 0.9942   | 0.9946    | 0.9841 | 0.9893 |
| 0.0156        | 2.75  | 1661 | 0.0418          | 0.9952   | 1.0       | 0.9823 | 0.9911 |
| 0.0156        | 3.0   | 1812 | 0.0333          | 0.9952   | 0.9982    | 0.9841 | 0.9911 |
| 0.0121        | 3.24  | 1963 | 0.0326          | 0.9952   | 0.9982    | 0.9841 | 0.9911 |
| 0.0121        | 3.49  | 2114 | 0.0309          | 0.9957   | 0.9982    | 0.9858 | 0.9920 |
| 0.0121        | 3.74  | 2265 | 0.0311          | 0.9952   | 0.9982    | 0.9841 | 0.9911 |
| 0.0121        | 3.99  | 2416 | 0.0344          | 0.9952   | 0.9982    | 0.9841 | 0.9911 |
| 0.0084        | 4.24  | 2567 | 0.0334          | 0.9952   | 0.9982    | 0.9841 | 0.9911 |
| 0.0084        | 4.49  | 2718 | 0.0327          | 0.9952   | 0.9982    | 0.9841 | 0.9911 |
| 0.0084        | 4.74  | 2869 | 0.0336          | 0.9952   | 0.9982    | 0.9841 | 0.9911 |
| 0.0084        | 4.99  | 3020 | 0.0341          | 0.9952   | 0.9982    | 0.9841 | 0.9911 |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.2.0.dev20230913+cu121
- Tokenizers 0.13.3