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

# output

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: 0.7643
- Accuracy: 0.8686
- Precision: 0.8681
- Recall: 0.8686
- F1: 0.8673

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.2969        | 1.0   | 505  | 0.6707          | 0.8376   | 0.8375    | 0.8376 | 0.8320 |
| 0.2567        | 2.0   | 1010 | 0.6184          | 0.8572   | 0.8516    | 0.8572 | 0.8519 |
| 0.1496        | 3.0   | 1515 | 0.6471          | 0.8693   | 0.8637    | 0.8693 | 0.8651 |
| 0.0826        | 4.0   | 2020 | 0.6897          | 0.8641   | 0.8600    | 0.8641 | 0.8604 |
| 0.0467        | 5.0   | 2525 | 0.7378          | 0.8676   | 0.8671    | 0.8676 | 0.8663 |
| 0.0229        | 6.0   | 3030 | 0.7521          | 0.8678   | 0.8670    | 0.8678 | 0.8666 |
| 0.01          | 7.0   | 3535 | 0.7643          | 0.8686   | 0.8681    | 0.8686 | 0.8673 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0