---
library_name: transformers
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: 1.8481
- Accuracy: 0.425
- F1: 0.4068
- Precision: 0.4371
- Recall: 0.425
- Mse: 5.314
- Mae: 1.37

## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall | Mse    | Mae   |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|:-----:|
| 1.9914        | 1.0   | 157  | 1.7086          | 0.404    | 0.2561 | 0.3800    | 0.404  | 10.332 | 1.95  |
| 1.5651        | 2.0   | 314  | 1.6295          | 0.419    | 0.3343 | 0.4048    | 0.419  | 7.397  | 1.591 |
| 1.3878        | 3.0   | 471  | 1.6456          | 0.421    | 0.3666 | 0.4605    | 0.421  | 6.147  | 1.473 |
| 1.1967        | 4.0   | 628  | 1.7054          | 0.42     | 0.3790 | 0.3598    | 0.42   | 5.874  | 1.44  |
| 1.1002        | 5.0   | 785  | 1.7713          | 0.414    | 0.3896 | 0.3701    | 0.414  | 5.647  | 1.419 |
| 0.9412        | 6.0   | 942  | 1.8481          | 0.425    | 0.4068 | 0.4371    | 0.425  | 5.314  | 1.37  |
| 0.8737        | 7.0   | 1099 | 1.9534          | 0.407    | 0.4007 | 0.4025    | 0.407  | 5.141  | 1.375 |
| 0.757         | 8.0   | 1256 | 2.0153          | 0.401    | 0.3932 | 0.3918    | 0.401  | 5.227  | 1.385 |
| 0.6973        | 9.0   | 1413 | 2.0556          | 0.404    | 0.3979 | 0.4004    | 0.404  | 5.176  | 1.376 |
| 0.6573        | 10.0  | 1570 | 2.0672          | 0.408    | 0.4008 | 0.4003    | 0.408  | 5.179  | 1.373 |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3