CoolFace
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Anispiha/ai-detector-model

sourceHugging Faceapache-2.0updated 2mo agoView on Hugging Face
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Model Card

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ai-detector-model

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

  • —Loss: 0.2038
  • —Accuracy: 0.9517
  • —F1: 0.9535

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: 5e-05
  • —trainbatchsize: 16
  • —evalbatchsize: 32
  • —seed: 42
  • —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • —lrschedulertype: linear
  • —num_epochs: 2

Training results

Training LossEpochStepValidation LossAccuracyF1
0.13861.08500.16690.94790.9500
0.04442.017000.20380.95170.9535

Framework versions

  • —Transformers 5.13.1
  • —Pytorch 2.11.0+cu128
  • —Datasets 4.0.0
  • —Tokenizers 0.22.2