---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- 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: 0.5025
- Accuracy: 0.8652
- F1: 0.9030

## 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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 0.6475        | 0.2174 | 50   | 0.6013          | 0.6863   | 0.8134 |
| 0.524         | 0.4348 | 100  | 0.5868          | 0.7108   | 0.8239 |
| 0.5462        | 0.6522 | 150  | 0.5164          | 0.7647   | 0.8486 |
| 0.5212        | 0.8696 | 200  | 0.4979          | 0.7868   | 0.8612 |
| 0.3795        | 1.0870 | 250  | 0.4238          | 0.8113   | 0.8675 |
| 0.3491        | 1.3043 | 300  | 0.4333          | 0.8137   | 0.8725 |
| 0.3169        | 1.5217 | 350  | 0.3667          | 0.8284   | 0.8797 |
| 0.2147        | 1.7391 | 400  | 0.3677          | 0.8603   | 0.9036 |
| 0.2552        | 1.9565 | 450  | 0.3500          | 0.8529   | 0.8905 |
| 0.1161        | 2.1739 | 500  | 0.4615          | 0.8652   | 0.9005 |
| 0.1318        | 2.3913 | 550  | 0.5217          | 0.8603   | 0.9039 |
| 0.0617        | 2.6087 | 600  | 0.4821          | 0.8676   | 0.9043 |
| 0.0523        | 2.8261 | 650  | 0.5025          | 0.8652   | 0.9030 |


### Framework versions

- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1