Kuongan / Hal_phobert-large_finetuned

huggingface.co
Total runs: 15
24-hour runs: 0
7-day runs: -2
30-day runs: 3
Model's Last Updated: September 23 2025
text-classification

Introduction of Hal_phobert-large_finetuned

Model Details of Hal_phobert-large_finetuned

Hal_phobert-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: 0.7847
  • Accuracy: 0.7407
  • F1 Macro: 0.7417
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
1.0956 1.0 88 0.7993 0.6786 0.6786
0.7654 2.0 176 0.7491 0.71 0.7089
0.618 3.0 264 0.7432 0.7257 0.7287
0.4807 4.0 352 0.7847 0.7407 0.7417
0.3665 5.0 440 0.8301 0.7357 0.7376
0.2522 6.0 528 0.8437 0.735 0.7364
0.2095 7.0 616 0.9808 0.7357 0.7362
Framework versions
  • Transformers 4.52.4
  • Pytorch 2.6.0+cu124
  • Datasets 3.6.0
  • Tokenizers 0.21.2

Runs of Kuongan Hal_phobert-large_finetuned on huggingface.co

15
Total runs
0
24-hour runs
1
3-day runs
-2
7-day runs
3
30-day runs

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