---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: training-1
  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-1

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: 0.0188
- Accuracy: 0.9957
- Precision: 0.9979
- Recall: 0.9936
- F1: 0.9957

## 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: 1e-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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 0.99  | 175  | 0.0323          | 0.9925   | 1.0       | 0.9850 | 0.9925 |
| 0.1307        | 1.99  | 350  | 0.0291          | 0.9936   | 1.0       | 0.9872 | 0.9935 |
| 0.0299        | 2.98  | 525  | 0.0201          | 0.9957   | 0.9979    | 0.9936 | 0.9957 |
| 0.024         | 3.98  | 700  | 0.0188          | 0.9957   | 0.9979    | 0.9936 | 0.9957 |
| 0.0183        | 4.97  | 875  | 0.0188          | 0.9957   | 0.9979    | 0.9936 | 0.9957 |


### Framework versions

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