---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- text-classification
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
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: 0.4186
- Accuracy: 0.9028
- Precision: 0.7440
- Recall: 0.6525
- F1: 0.6953

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.238         | 1.0   | 347  | 0.2861          | 0.8913   | 0.7179    | 0.5932 | 0.6497 |
| 0.2052        | 2.0   | 694  | 0.2654          | 0.9057   | 0.7966    | 0.5975 | 0.6828 |
| 0.024         | 3.0   | 1041 | 0.4186          | 0.9028   | 0.7440    | 0.6525 | 0.6953 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Tokenizers 0.19.1