---
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
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# VF_BERT_ST_1800

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: 0.1814
- Precision: 0.8104
- Recall: 0.8406
- F1: 0.8252
- Accuracy: 0.9657

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2052        | 1.0   | 569  | 0.1207          | 0.7731    | 0.8082 | 0.7903 | 0.9622   |
| 0.0774        | 2.0   | 1138 | 0.1369          | 0.8062    | 0.7998 | 0.8030 | 0.9629   |
| 0.0507        | 3.0   | 1707 | 0.1351          | 0.8127    | 0.8386 | 0.8254 | 0.9654   |
| 0.0328        | 4.0   | 2276 | 0.1331          | 0.8005    | 0.8414 | 0.8204 | 0.9658   |
| 0.0221        | 5.0   | 2845 | 0.1398          | 0.8144    | 0.8429 | 0.8284 | 0.9668   |
| 0.0157        | 6.0   | 3414 | 0.1481          | 0.8137    | 0.8401 | 0.8267 | 0.9671   |
| 0.0117        | 7.0   | 3983 | 0.1804          | 0.8110    | 0.8439 | 0.8271 | 0.9650   |
| 0.0062        | 8.0   | 4552 | 0.1731          | 0.8133    | 0.8434 | 0.8281 | 0.9658   |
| 0.005         | 9.0   | 5121 | 0.1835          | 0.8100    | 0.8416 | 0.8255 | 0.9660   |
| 0.0043        | 10.0  | 5690 | 0.1814          | 0.8104    | 0.8406 | 0.8252 | 0.9657   |


### Framework versions

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