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

# results

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: 0.5341
- Accuracy: 0.8650
- F1: 0.8653
- Precision: 0.8661
- Recall: 0.8650

## 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: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.4791        | 1.0   | 246  | 0.5719          | 0.7483   | 0.7541 | 0.8107    | 0.7483 |
| 0.4459        | 2.0   | 492  | 0.4187          | 0.8467   | 0.8486 | 0.8608    | 0.8467 |
| 0.1932        | 3.0   | 738  | 0.4394          | 0.8581   | 0.8590 | 0.8611    | 0.8581 |
| 0.181         | 4.0   | 984  | 0.5341          | 0.8650   | 0.8653 | 0.8661    | 0.8650 |


### Framework versions

- Transformers 4.36.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0