---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: training-6
  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-6

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: 0.0431
- Accuracy: 0.9923
- Precision: 0.9942
- Recall: 0.9752
- F1: 0.9846

## 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: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 0.5   | 302  | 0.0633          | 0.9894   | 0.9980    | 0.9599 | 0.9786 |
| No log        | 1.0   | 604  | 0.0501          | 0.9846   | 0.9713    | 0.9676 | 0.9694 |
| 0.0875        | 1.5   | 906  | 0.0621          | 0.9899   | 0.9980    | 0.9618 | 0.9796 |
| 0.0875        | 2.0   | 1208 | 0.0420          | 0.9928   | 0.9961    | 0.9752 | 0.9855 |
| 0.0269        | 2.5   | 1510 | 0.0509          | 0.9923   | 0.9980    | 0.9714 | 0.9845 |
| 0.0269        | 3.0   | 1812 | 0.0456          | 0.9932   | 1.0       | 0.9733 | 0.9865 |
| 0.0159        | 3.49  | 2114 | 0.0452          | 0.9937   | 1.0       | 0.9752 | 0.9874 |
| 0.0159        | 3.99  | 2416 | 0.0431          | 0.9923   | 0.9942    | 0.9752 | 0.9846 |


### Framework versions

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