---
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: 2.0300
- Accuracy: 0.5894
- F1: 0.5891
- Precision: 0.5918
- Recall: 0.5894

## 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.1618        | 1.0   | 367  | 1.0932          | 0.5433   | 0.5350 | 0.5951    | 0.5433 |
| 0.8085        | 2.0   | 734  | 1.0683          | 0.5806   | 0.5769 | 0.5769    | 0.5806 |
| 0.5055        | 3.0   | 1101 | 1.2485          | 0.5711   | 0.5728 | 0.5867    | 0.5711 |
| 0.1641        | 4.0   | 1468 | 1.7630          | 0.5925   | 0.5917 | 0.5916    | 0.5925 |
| 0.0525        | 5.0   | 1835 | 2.0300          | 0.5894   | 0.5891 | 0.5918    | 0.5894 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Tokenizers 0.19.1