---
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: 0.5038
- Accuracy: 0.876
- F1: 0.8654

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.4682        | 1.0   | 500  | 0.3929          | 0.838    | 0.8325 |
| 0.4017        | 2.0   | 1000 | 0.4347          | 0.833    | 0.7715 |
| 0.3825        | 3.0   | 1500 | 0.6541          | 0.779    | 0.7984 |
| 0.3609        | 4.0   | 2000 | 0.4493          | 0.851    | 0.8484 |
| 0.3404        | 5.0   | 2500 | 0.4276          | 0.843    | 0.7941 |
| 0.3184        | 6.0   | 3000 | 0.3935          | 0.864    | 0.8509 |
| 0.2792        | 7.0   | 3500 | 0.3839          | 0.867    | 0.8519 |
| 0.2919        | 8.0   | 4000 | 0.5530          | 0.855    | 0.8216 |
| 0.2404        | 9.0   | 4500 | 0.5326          | 0.865    | 0.8603 |
| 0.2139        | 10.0  | 5000 | 0.5038          | 0.876    | 0.8654 |


### Framework versions

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