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AntoineD/camembert_ccnet_classification_tools_fr

sourceHugging Faceupdated 3y agoView on Hugging Face
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Model Card

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camembertccnetclassificationtoolsfr

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

  • Loss: 0.5125
  • Accuracy: 0.9
  • Learning Rate: 0.0001

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: 0.0001
  • trainbatchsize: 24
  • evalbatchsize: 192
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • num_epochs: 60

Training results

Training LossEpochStepValidation LossAccuracyRate
No log1.071.88940.5250.0001
No log2.0141.42690.6750.0001
No log3.0211.10380.750.0001
No log4.0280.80140.850.0001
No log5.0350.64060.850.0001
No log6.0420.62200.8759e-05
No log7.0490.46420.8750.0001
No log8.0560.55960.850.0001
No log9.0630.56480.850.0001
No log10.0700.50250.90.0001
No log11.0770.52630.90.0001
No log12.0840.50620.98e-05
No log13.0910.49500.90.0001
No log14.0980.49810.90.0001
No log15.01050.50360.90.0001
No log16.01120.50750.90.0001
No log17.01190.51250.90.0001

Framework versions

  • Transformers 4.34.0
  • Pytorch 2.0.1+cu117
  • Datasets 2.14.5
  • Tokenizers 0.14.1