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distilbert-base-uncased-finetuned-ag_news

This model is a fine-tuned version of distilbert-base-uncased on the ag_news dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1691
  • Accuracy: 0.9443
  • F1: 0.9444

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: 32
  • eval_batch_size: 32
  • 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 F1
0.2253 1.0 3750 0.1749 0.9411 0.9413
0.1335 2.0 7500 0.1691 0.9443 0.9444

Framework versions

  • Transformers 4.16.2
  • Pytorch 2.1.0+cu121
  • Datasets 1.16.1
  • Tokenizers 0.15.0
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Dataset used to train TingTing0104/distilbert-base-uncased-finetuned-ag_news

Evaluation results