Kuongan / Hal_videberta-base_finetuned

huggingface.co
Total runs: 12
24-hour runs: 0
7-day runs: 0
30-day runs: 8
Model's Last Updated: September 25 2025
text-classification

Introduction of Hal_videberta-base_finetuned

Model Details of Hal_videberta-base_finetuned

Hal_videberta-base_finetuned

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

  • Loss: 0.8824
  • Accuracy: 0.6907
  • F1: 0.6907
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: 16
  • eval_batch_size: 16
  • 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
Training results
Training Loss Epoch Step Validation Loss Accuracy F1
1.104 1.0 350 1.0995 0.3493 0.3493
1.1055 2.0 700 1.0982 0.3493 0.3493
1.0983 3.0 1050 1.0992 0.35 0.35
1.0974 4.0 1400 1.0983 0.35 0.35
1.0959 5.0 1750 1.0954 0.3507 0.3507
0.834 6.0 2100 0.8176 0.6471 0.6471
0.7454 7.0 2450 0.8176 0.6571 0.6571
0.7321 8.0 2800 0.7939 0.6693 0.6693
0.6003 9.0 3150 0.8458 0.6657 0.6657
0.602 10.0 3500 0.8261 0.6821 0.6821
0.4936 11.0 3850 0.9280 0.6629 0.6629
0.4742 12.0 4200 0.8824 0.6907 0.6907
0.452 13.0 4550 1.0194 0.6714 0.6714
0.3957 14.0 4900 1.0482 0.6657 0.6657
0.4032 15.0 5250 1.0783 0.6686 0.6686
Framework versions
  • Transformers 4.48.0
  • Pytorch 2.6.0+cu124
  • Datasets 3.2.0
  • Tokenizers 0.21.0

Runs of Kuongan Hal_videberta-base_finetuned on huggingface.co

12
Total runs
0
24-hour runs
0
3-day runs
0
7-day runs
8
30-day runs

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Hal_videberta-base_finetuned install

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