Kuongan / Halphobert-large_finetuned

huggingface.co
Total runs: 16
24-hour runs: 0
7-day runs: -2
30-day runs: 6
Model's Last Updated: 2025年9月23日
text-classification

Introduction of Halphobert-large_finetuned

Model Details of Halphobert-large_finetuned

Halphobert-large_finetuned

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

  • Loss: 0.7409
  • Accuracy: 0.7486
  • F1 Macro: 0.7478
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: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 20
  • mixed_precision_training: Native AMP
Training results
Training Loss Epoch Step Validation Loss Accuracy F1 Macro
1.0965 1.0 88 0.8876 0.6014 0.5940
0.7658 2.0 176 0.7050 0.735 0.7361
0.6118 3.0 264 0.7218 0.7407 0.7425
0.4813 4.0 352 0.7409 0.7486 0.7478
0.3701 5.0 440 0.7899 0.7393 0.7405
0.2655 6.0 528 0.8799 0.7329 0.7335
0.2237 7.0 616 0.9862 0.7207 0.7215
0.1591 8.0 704 1.0564 0.7307 0.7317
Framework versions
  • Transformers 4.52.4
  • Pytorch 2.6.0+cu124
  • Datasets 3.6.0
  • Tokenizers 0.21.2

Runs of Kuongan Halphobert-large_finetuned on huggingface.co

16
Total runs
0
24-hour runs
1
3-day runs
-2
7-day runs
6
30-day runs

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Halphobert-large_finetuned install

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