---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- ag_news
metrics:
- f1
model-index:
- name: ag-news-twitter-9600-bert-base-uncased
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: ag_news
      type: ag_news
      config: default
      split: test
      args: default
    metrics:
    - name: F1
      type: f1
      value: 0.9162249767982196
---

<!-- 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. -->

# ag-news-twitter-9600-bert-base-uncased

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the ag_news dataset.
It achieves the following results on the evaluation set:
- F1: 0.9162
- Acc: 0.9162
- Loss: 0.6033

## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | F1     | Acc    | Validation Loss |
|:-------------:|:-----:|:----:|:------:|:------:|:---------------:|
| 0.8065        | 1.0   | 600  | 0.9060 | 0.9059 | 0.3013          |
| 0.2872        | 2.0   | 1200 | 0.9171 | 0.9170 | 0.2598          |
| 0.2156        | 3.0   | 1800 | 0.9178 | 0.9184 | 0.3117          |
| 0.1486        | 4.0   | 2400 | 0.9200 | 0.9197 | 0.3631          |
| 0.0683        | 5.0   | 3000 | 0.9202 | 0.9201 | 0.3782          |
| 0.045         | 6.0   | 3600 | 0.9186 | 0.9188 | 0.4846          |
| 0.0218        | 7.0   | 4200 | 0.9155 | 0.9155 | 0.5898          |
| 0.0245        | 8.0   | 4800 | 0.9162 | 0.9162 | 0.6033          |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1