---
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
should probably proofread and complete it, then remove this comment. -->

# 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: 0.2457
- Precision: 0.9489
- Recall: 0.9480
- F1: 0.9485
- Accuracy: 0.9405

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 30   | 0.4723          | 0.8973    | 0.9212 | 0.9091 | 0.8971   |
| No log        | 2.0   | 60   | 0.3328          | 0.9146    | 0.9288 | 0.9217 | 0.9076   |
| No log        | 3.0   | 90   | 0.3022          | 0.9316    | 0.9301 | 0.9308 | 0.9168   |
| No log        | 4.0   | 120  | 0.2758          | 0.9207    | 0.9398 | 0.9301 | 0.9169   |
| No log        | 5.0   | 150  | 0.2592          | 0.9392    | 0.9431 | 0.9411 | 0.9322   |
| No log        | 6.0   | 180  | 0.2586          | 0.9445    | 0.9449 | 0.9447 | 0.9366   |
| No log        | 7.0   | 210  | 0.2519          | 0.9476    | 0.9447 | 0.9461 | 0.9372   |
| No log        | 8.0   | 240  | 0.2468          | 0.9464    | 0.9474 | 0.9469 | 0.9394   |
| No log        | 9.0   | 270  | 0.2475          | 0.9486    | 0.9476 | 0.9481 | 0.9399   |
| No log        | 10.0  | 300  | 0.2457          | 0.9489    | 0.9480 | 0.9485 | 0.9405   |


### Framework versions

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