date3k2 / gpt2-text-classification

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Total runs: 7
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Model's Last Updated: May 23 2024
text-classification

Introduction of gpt2-text-classification

Model Details of gpt2-text-classification

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gpt2-text-classification-v2

This model is a fine-tuned version of gpt2 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2002
  • Accuracy: 0.9342
  • F1: 0.9340
  • Recall: 0.9314
  • Precision: 0.9367
Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 3e-05
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 3
  • total_train_batch_size: 96
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10
Training results
Training Loss Epoch Step Accuracy F1 Validation Loss Precision Recall
0.327 0.9974 260 0.8973 0.8929 0.2559 0.9333 0.8558
0.241 1.9987 521 0.919 0.9180 0.2039 0.9296 0.9066
0.244 3.0 782 0.9154 0.9192 0.2156 0.8799 0.9621
0.1843 3.9974 1042 0.9299 0.9288 0.1888 0.9427 0.9154
0.1608 4.9987 1303 0.9301 0.9291 0.1855 0.9428 0.9158
0.124 6.0 1564 0.9322 0.9319 0.1826 0.9357 0.9282
0.112 6.9974 1820 0.2099 0.9315 0.9303 0.9138 0.9473
0.0903 7.9987 2081 0.2002 0.9342 0.9340 0.9314 0.9367
Framework versions
  • Transformers 4.41.0
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1

Runs of date3k2 gpt2-text-classification on huggingface.co

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