---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: VF_BERT_ST_1800_V2
  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. -->

# VF_BERT_ST_1800_V2

This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1698
- Precision: 0.9686
- Recall: 0.9772
- F1: 0.9729
- Accuracy: 0.9683

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2128        | 1.0   | 569  | 0.1128          | 0.9644    | 0.9733 | 0.9688 | 0.9654   |
| 0.0784        | 2.0   | 1138 | 0.1145          | 0.9668    | 0.9753 | 0.9710 | 0.9672   |
| 0.0512        | 3.0   | 1707 | 0.1242          | 0.9680    | 0.9746 | 0.9712 | 0.9663   |
| 0.0327        | 4.0   | 2276 | 0.1227          | 0.9706    | 0.9762 | 0.9734 | 0.9673   |
| 0.022         | 5.0   | 2845 | 0.1298          | 0.9684    | 0.9755 | 0.9719 | 0.9686   |
| 0.0153        | 6.0   | 3414 | 0.1410          | 0.9710    | 0.9778 | 0.9744 | 0.9698   |
| 0.0118        | 7.0   | 3983 | 0.1589          | 0.9681    | 0.9777 | 0.9729 | 0.9686   |
| 0.0058        | 8.0   | 4552 | 0.1617          | 0.9696    | 0.9773 | 0.9735 | 0.9691   |
| 0.005         | 9.0   | 5121 | 0.1731          | 0.9685    | 0.9773 | 0.9729 | 0.9683   |
| 0.0043        | 10.0  | 5690 | 0.1698          | 0.9686    | 0.9772 | 0.9729 | 0.9683   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1