---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
- precision
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: 0.9742
- Accuracy: 0.878
- F1: 0.8729
- Recall: 0.878
- Precision: 0.8709

## 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 OptimizerNames.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     | Recall | Precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
| 0.3524        | 1.0   | 500  | 0.6161          | 0.867    | 0.8508 | 0.867  | 0.8553    |
| 0.2878        | 2.0   | 1000 | 0.5404          | 0.882    | 0.8706 | 0.882  | 0.8739    |
| 0.1682        | 3.0   | 1500 | 0.7048          | 0.879    | 0.8684 | 0.879  | 0.8699    |
| 0.1006        | 4.0   | 2000 | 0.7590          | 0.877    | 0.8610 | 0.877  | 0.8698    |
| 0.0421        | 5.0   | 2500 | 0.7716          | 0.878    | 0.8742 | 0.878  | 0.8722    |
| 0.0205        | 6.0   | 3000 | 0.8432          | 0.887    | 0.8804 | 0.887  | 0.8798    |
| 0.0294        | 7.0   | 3500 | 0.8998          | 0.884    | 0.8661 | 0.884  | 0.8837    |
| 0.0099        | 8.0   | 4000 | 0.9366          | 0.882    | 0.8746 | 0.882  | 0.8739    |
| 0.0046        | 9.0   | 4500 | 0.9346          | 0.882    | 0.8789 | 0.882  | 0.8771    |
| 0.0028        | 10.0  | 5000 | 0.9742          | 0.878    | 0.8729 | 0.878  | 0.8709    |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.1
- Tokenizers 0.21.0