CoolFace
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marklicata/M365_h1_base

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

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M365_v3

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: 0.0896

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: Use adamwtorch with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • lrschedulertype: linear
  • num_epochs: 3.0

Training results

Training LossEpochStepValidation Loss
0.3261.09000.1093
0.0592.018000.0841
0.01413.027000.0896

Framework versions

  • Transformers 4.46.1
  • Pytorch 2.4.1+cu121
  • Datasets 3.1.0
  • Tokenizers 0.20.1