---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- ag_news
metrics:
- f1
model-index:
- name: ag-news-twitter-76800-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: 0.9414991482921289
---

<!-- 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-76800-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: 0.9415
- Acc: 0.9416
- Loss: 0.5192

## 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 |
|:-------------:|:-----:|:-----:|:------:|:------:|:---------------:|
| 0.2328        | 1.0   | 4800  | 0.9289 | 0.9289 | 0.2082          |
| 0.2061        | 2.0   | 9600  | 0.9366 | 0.9367 | 0.2154          |
| 0.1488        | 3.0   | 14400 | 0.9401 | 0.9401 | 0.2181          |
| 0.114         | 4.0   | 19200 | 0.9280 | 0.9275 | 0.3199          |
| 0.0818        | 5.0   | 24000 | 0.9399 | 0.94   | 0.2953          |
| 0.051         | 6.0   | 28800 | 0.9402 | 0.9403 | 0.3828          |
| 0.0413        | 7.0   | 33600 | 0.9404 | 0.9403 | 0.4327          |
| 0.0342        | 8.0   | 38400 | 0.9395 | 0.9395 | 0.4291          |
| 0.0192        | 9.0   | 43200 | 0.9422 | 0.9422 | 0.4170          |
| 0.0204        | 10.0  | 48000 | 0.9374 | 0.9374 | 0.4761          |
| 0.0125        | 11.0  | 52800 | 0.9358 | 0.9359 | 0.5126          |
| 0.0124        | 12.0  | 57600 | 0.9415 | 0.9416 | 0.5192          |


### Framework versions

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