---
license: mit
tags:
- generated_from_trainer
datasets:
- ag_news
model-index:
- name: roberta-base_ag_news
  results: []
widget:
- text: >-
    Oil and Economy Cloud Stocks' Outlook (Reuters) Reuters - Soaring crude
    prices plus worries\about the economy and the outlook for earnings are
    expected to\hang over the stock market next week during the depth of
    the\summer doldrums
- text: >-
    Prediction Unit Helps Forecast Wildfires (AP) AP - It's barely dawn when
    Mike Fitzpatrick starts his shift with a blur of colorful maps, figures and
    endless charts, but already he knows what the day will bring. Lightning will
    strike in places he expects. Winds will pick up, moist places will dry and
    flames will roar
- text: >-
    Venezuelans Flood Polls, Voting Extended CARACAS, Venezuela (Reuters) -
    Venezuelans voted in huge numbers on Sunday in a historic referendum on
    whether to recall left-wing President Hugo Chavez and electoral authorities
    prolonged voting well into the night.
language:
- en
pipeline_tag: text-classification
---

<!-- 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. -->

# roberta-base_ag_news

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the ag_news dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3583

## 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: 5e-05
- 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.3692        | 1.0   | 7500  | 0.4305          |
| 1.6035        | 2.0   | 15000 | 1.8071          |
| 0.6766        | 3.0   | 22500 | 0.4494          |
| 0.3733        | 4.0   | 30000 | 0.3943          |
| 0.2483        | 5.0   | 37500 | 0.3583          |


### Framework versions

- Transformers 4.27.3
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2