CoolFace
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SednaWorld/transfer-learning

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

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transfer-learning

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

  • Loss: 0.7182
  • Accuracy: 0.8064
  • F1: 0.8460

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: 8
  • evalbatchsize: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • num_epochs: 3

Training results

Training LossEpochStepValidation LossAccuracyF1
0.51761.095000.71270.80150.8541
0.37042.1810000.71820.80640.8460

Framework versions

  • Transformers 4.30.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.13.3