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metadata
license: mit
base_model: camembert-base
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: camembert_classification_tools
    results: []

camembert_classification_tools

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

  • Loss: 0.6969
  • Accuracy: 0.775

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: 30

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 5 2.0733 0.2
No log 2.0 10 2.0478 0.275
No log 3.0 15 1.9161 0.45
No log 4.0 20 1.7607 0.425
No log 5.0 25 1.5895 0.575
No log 6.0 30 1.4201 0.625
No log 7.0 35 1.2944 0.675
No log 8.0 40 1.2193 0.75
No log 9.0 45 1.0974 0.775
No log 10.0 50 1.0429 0.825
No log 11.0 55 0.9602 0.8
No log 12.0 60 0.9059 0.8
No log 13.0 65 0.8365 0.825
No log 14.0 70 0.9396 0.725
No log 15.0 75 0.8271 0.8
No log 16.0 80 0.7762 0.8
No log 17.0 85 0.7847 0.8
No log 18.0 90 0.7012 0.8
No log 19.0 95 0.6971 0.8
No log 20.0 100 0.7186 0.775
No log 21.0 105 0.7946 0.725
No log 22.0 110 0.7721 0.725
No log 23.0 115 0.7642 0.725
No log 24.0 120 0.7298 0.75
No log 25.0 125 0.7191 0.75
No log 26.0 130 0.6978 0.775
No log 27.0 135 0.6913 0.8
No log 28.0 140 0.6949 0.775
No log 29.0 145 0.6961 0.775
No log 30.0 150 0.6969 0.775

Framework versions

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