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roberta-base-bne-finetuned-fakeNews-v1

Text Classification
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PyTorch
roberta
Generated from Trainer
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roberta-base-bne-finetuned-fakeNews-v1 / README.md
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metadata
license: apache-2.0
base_model: BSC-TeMU/roberta-base-bne
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: roberta-base-bne-finetuned-amazon_reviews_multi
    results: []

roberta-base-bne-finetuned-amazon_reviews_multi

This model is a fine-tuned version of BSC-TeMU/roberta-base-bne on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0342
  • Accuracy: 0.9862

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: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 2

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.0386 1.0 1250 0.0347 0.9818
0.023 2.0 2500 0.0342 0.9862

Framework versions

  • Transformers 4.34.1
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1