---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-uncased-AG-News
  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-uncased-AG-News

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: 0.7208
- Balanced Accuracy: 0.8720
- Accuracy: 0.8667

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Balanced Accuracy | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------:|
| 1.3219        | 1.0   | 25   | 0.8636          | 0.7889            | 0.79     |
| 0.6342        | 2.0   | 50   | 0.5691          | 0.8689            | 0.86     |
| 0.2991        | 3.0   | 75   | 0.5546          | 0.8602            | 0.86     |
| 0.1403        | 4.0   | 100  | 0.6923          | 0.8719            | 0.8667   |
| 0.0561        | 5.0   | 125  | 0.7208          | 0.8720            | 0.8667   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1