---
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: BERT_ST_DA_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. -->

# BERT_ST_DA_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: 0.1918
- Precision: 0.9710
- Recall: 0.9712
- F1: 0.9711
- Accuracy: 0.9675

## 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: 16
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1075        | 1.0   | 1050  | 0.1338          | 0.9633    | 0.9650 | 0.9641 | 0.9616   |
| 0.0565        | 2.0   | 2100  | 0.1253          | 0.9661    | 0.9687 | 0.9674 | 0.9647   |
| 0.0358        | 3.0   | 3150  | 0.1386          | 0.9691    | 0.9703 | 0.9697 | 0.9666   |
| 0.0211        | 4.0   | 4200  | 0.1516          | 0.9701    | 0.9707 | 0.9704 | 0.9670   |
| 0.0118        | 5.0   | 5250  | 0.1586          | 0.9697    | 0.9726 | 0.9711 | 0.9676   |
| 0.0084        | 6.0   | 6300  | 0.1791          | 0.9685    | 0.9698 | 0.9691 | 0.9654   |
| 0.0054        | 7.0   | 7350  | 0.1849          | 0.9692    | 0.9692 | 0.9692 | 0.9657   |
| 0.0031        | 8.0   | 8400  | 0.1887          | 0.9690    | 0.9708 | 0.9699 | 0.9660   |
| 0.0023        | 9.0   | 9450  | 0.1931          | 0.9705    | 0.9703 | 0.9704 | 0.9669   |
| 0.0017        | 10.0  | 10500 | 0.1918          | 0.9710    | 0.9712 | 0.9711 | 0.9675   |


### Framework versions

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