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---
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 |