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End of training
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metadata
base_model: camembert/camembert-base-ccnet
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: camembert_ccnet_classification_tools_fr
    results: []

camembert_ccnet_classification_tools_fr

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
  • train_batch_size: 24
  • eval_batch_size: 192
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 60

Training results

Training Loss Epoch Step Validation Loss Accuracy Rate
No log 1.0 7 1.8894 0.525 0.0001
No log 2.0 14 1.4269 0.675 0.0001
No log 3.0 21 1.1038 0.75 0.0001
No log 4.0 28 0.8014 0.85 0.0001
No log 5.0 35 0.6406 0.85 0.0001
No log 6.0 42 0.6220 0.875 9e-05
No log 7.0 49 0.4642 0.875 0.0001
No log 8.0 56 0.5596 0.85 0.0001
No log 9.0 63 0.5648 0.85 0.0001
No log 10.0 70 0.5025 0.9 0.0001
No log 11.0 77 0.5263 0.9 0.0001
No log 12.0 84 0.5062 0.9 8e-05
No log 13.0 91 0.4950 0.9 0.0001
No log 14.0 98 0.4981 0.9 0.0001
No log 15.0 105 0.5036 0.9 0.0001
No log 16.0 112 0.5075 0.9 0.0001
No log 17.0 119 0.5125 0.9 0.0001

Framework versions

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