---
base_model: bert-base-uncased
library_name: transformers
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: Finetuning_BERT_BBCNews
  results: []
---

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

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1125
- Accuracy: 0.9775

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 195  | 0.0810          | 0.9775   |
| No log        | 2.0   | 390  | 0.1163          | 0.9730   |
| 0.1923        | 3.0   | 585  | 0.1213          | 0.9820   |
| 0.1923        | 4.0   | 780  | 0.0941          | 0.9775   |
| 0.1923        | 5.0   | 975  | 0.1148          | 0.9820   |
| 0.0098        | 6.0   | 1170 | 0.1389          | 0.9820   |
| 0.0098        | 7.0   | 1365 | 0.1032          | 0.9730   |
| 0.0044        | 8.0   | 1560 | 0.1165          | 0.9820   |
| 0.0044        | 9.0   | 1755 | 0.1126          | 0.9820   |
| 0.0044        | 10.0  | 1950 | 0.1125          | 0.9775   |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0