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metadata
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

roberta-base_ag_news

This model is a fine-tuned version of 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