CoolFace
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linuxnewbie84/entrenamiento

sourceHugging Faceapache-2.0updated 1y agoView on Hugging Face
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Model Card

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entrenamiento

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

  • Loss: 1.6073
  • Accuracy: 0.25

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 OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • lrschedulertype: linear
  • num_epochs: 5

Training results

Training LossEpochStepValidation LossAccuracy
1.62860.551.63560.15
1.63251.0101.60840.15
1.58721.5151.59850.225
1.58192.0201.59690.225
1.56792.5251.59370.25
1.5333.0301.59350.225
1.51913.5351.59760.275
1.44764.0401.60840.225
1.39394.5451.61220.225
1.46345.0501.60730.25

Framework versions

  • Transformers 4.55.0
  • Pytorch 2.6.0+cu124
  • Datasets 4.0.0
  • Tokenizers 0.21.4