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pqthinh232/phobert-vsa-restaurant-8k

sourceHugging Facemitupdated 6mo agoView on Hugging Face
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phobert-vsa-restaurant-8k

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: 0.2661
  • —Accuracy: 0.9024
  • —F1: 0.9019
  • —Precision: 0.9017
  • —Recall: 0.9024

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
  • —trainbatchsize: 16
  • —evalbatchsize: 16
  • —seed: 42
  • —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • —lrschedulertype: linear
  • —num_epochs: 5

Training results

Training LossEpochStepValidation LossAccuracyF1PrecisionRecall
0.39041.04000.35580.84730.85250.86560.8473
0.26362.08000.34910.87730.87660.87660.8773
0.15703.012000.45440.86230.86010.86040.8623
0.13294.016000.49980.86860.86990.87180.8686
0.08935.020000.56710.86480.86510.86590.8648

Framework versions

  • —Transformers 5.0.0
  • —Pytorch 2.10.0+cu128
  • —Datasets 4.0.0
  • —Tokenizers 0.22.2