---
license: apache-2.0
base_model: odunola/bert-base-uncased-ag-news-finetuned
tags:
- generated_from_trainer
datasets:
- ag_news
metrics:
- accuracy
model-index:
- name: bert-base-uncased-ag-news-finetuned-2
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: ag_news
      type: ag_news
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9819166666666667
---

<!-- 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-base-uncased-ag-news-finetuned-2

This model is a fine-tuned version of [odunola/bert-base-uncased-ag-news-finetuned](https://huggingface.co/odunola/bert-base-uncased-ag-news-finetuned) on the ag_news dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0712
- Accuracy: 0.9819
- F1(weighted): 0.9819
- Precision(weighted): 0.9819
- Recall(weighted): 0.9819

## 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: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1(weighted) | Precision(weighted) | Recall(weighted) |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------------:|:-------------------:|:----------------:|
| 0.1006        | 1.0   | 6000 | 0.0712          | 0.9819   | 0.9819       | 0.9819              | 0.9819           |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1