---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: results_bert_full
  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_bert_full

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4327
- Accuracy: 0.8533
- F1: 0.8517

## 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: 8
- eval_batch_size: 8
- 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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 450  | 0.4571          | 0.8367   | 0.7623 |
| 0.4531        | 2.0   | 900  | 0.4590          | 0.8367   | 0.7623 |
| 0.4643        | 3.0   | 1350 | 0.4480          | 0.8367   | 0.7623 |
| 0.4537        | 4.0   | 1800 | 0.4498          | 0.8367   | 0.7623 |
| 0.4508        | 5.0   | 2250 | 0.4466          | 0.8367   | 0.7623 |
| 0.4531        | 6.0   | 2700 | 0.4467          | 0.8367   | 0.7623 |
| 0.4553        | 7.0   | 3150 | 0.4498          | 0.8367   | 0.7623 |
| 0.4388        | 8.0   | 3600 | 0.4473          | 0.8367   | 0.7623 |
| 0.3981        | 9.0   | 4050 | 0.3563          | 0.8722   | 0.8472 |
| 0.2981        | 10.0  | 4500 | 0.4327          | 0.8533   | 0.8517 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0