---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- ag_news
metrics:
- f1
model-index:
- name: ag-news-twitter-4800-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: 0.9122649070746451
---

<!-- 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-4800-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: 0.9123
- Acc: 0.9126
- Loss: 0.6235

## 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 |
|:-------------:|:-----:|:----:|:------:|:------:|:---------------:|
| No log        | 1.0   | 300  | 0.8951 | 0.8955 | 0.3460          |
| 0.6828        | 2.0   | 600  | 0.8957 | 0.8959 | 0.3295          |
| 0.6828        | 3.0   | 900  | 0.9096 | 0.9095 | 0.3196          |
| 0.1866        | 4.0   | 1200 | 0.9011 | 0.9018 | 0.4358          |
| 0.0804        | 5.0   | 1500 | 0.9116 | 0.9116 | 0.4441          |
| 0.0804        | 6.0   | 1800 | 0.9121 | 0.9124 | 0.4983          |
| 0.0236        | 7.0   | 2100 | 0.9126 | 0.9128 | 0.5473          |
| 0.0236        | 8.0   | 2400 | 0.9082 | 0.9086 | 0.6025          |
| 0.0092        | 9.0   | 2700 | 0.9121 | 0.9124 | 0.6057          |
| 0.0028        | 10.0  | 3000 | 0.9123 | 0.9126 | 0.6235          |


### Framework versions

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