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project-2

This model is a fine-tuned version of vinai/phobert-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2549
  • F1: 0.7177
  • Roc Auc: 0.8111
  • Accuracy: 0.6724

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: 8
  • eval_batch_size: 8
  • 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 F1 Roc Auc Accuracy
0.2526 1.0 73895 0.2578 0.7127 0.8065 0.6596
0.2367 2.0 147790 0.2549 0.7177 0.8111 0.6724

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.1.2
  • Datasets 2.1.0
  • Tokenizers 0.15.2
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