Kuongan / CS221-roberta-base-finetuned-augmentation

huggingface.co
Total runs: 10
24-hour runs: 0
7-day runs: -1
30-day runs: 5
Model's Last Updated: January 23 2025
text-classification

Introduction of CS221-roberta-base-finetuned-augmentation

Model Details of CS221-roberta-base-finetuned-augmentation

CS221-roberta-base-finetuned-augmentation

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

  • Loss: 0.1561
  • F1: 0.9312
  • Roc Auc: 0.9459
  • Accuracy: 0.8638
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: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 20
Training results
Training Loss Epoch Step Validation Loss F1 Roc Auc Accuracy
0.3933 1.0 180 0.3696 0.6352 0.7378 0.4288
0.2905 2.0 360 0.2958 0.7524 0.8079 0.5587
0.2139 3.0 540 0.2298 0.8538 0.8845 0.6769
0.1505 4.0 720 0.1996 0.8757 0.9030 0.7429
0.1218 5.0 900 0.1745 0.9027 0.9200 0.7880
0.0737 6.0 1080 0.1556 0.9199 0.9356 0.8290
0.0604 7.0 1260 0.1541 0.9241 0.9366 0.8485
0.0353 8.0 1440 0.1538 0.9294 0.9468 0.8652
0.024 9.0 1620 0.1561 0.9312 0.9459 0.8638
0.0235 10.0 1800 0.1638 0.9283 0.9459 0.8624
0.0159 11.0 1980 0.1615 0.9310 0.9467 0.8694
0.0158 12.0 2160 0.1625 0.9307 0.9461 0.8687
Framework versions
  • Transformers 4.47.0
  • Pytorch 2.5.1+cu121
  • Datasets 3.2.0
  • Tokenizers 0.21.0

Runs of Kuongan CS221-roberta-base-finetuned-augmentation on huggingface.co

10
Total runs
0
24-hour runs
0
3-day runs
-1
7-day runs
5
30-day runs

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