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camembert_classification_tools_qlora_fr

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

camembert_classification_tools_qlora_fr

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

  • Loss: 0.7280
  • Accuracy: 0.85

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
No log 1.0 5 2.0968 0.075
No log 2.0 10 2.1103 0.075
No log 3.0 15 2.1119 0.075
No log 4.0 20 2.1045 0.1
No log 5.0 25 2.0948 0.125
No log 6.0 30 2.0586 0.125
No log 7.0 35 2.0199 0.2
No log 8.0 40 1.9633 0.25
No log 9.0 45 1.9075 0.35
No log 10.0 50 1.8445 0.5
No log 11.0 55 1.7872 0.55
No log 12.0 60 1.7288 0.6
No log 13.0 65 1.6744 0.625
No log 14.0 70 1.6192 0.65
No log 15.0 75 1.5612 0.65
No log 16.0 80 1.5041 0.65
No log 17.0 85 1.4466 0.7
No log 18.0 90 1.3910 0.675
No log 19.0 95 1.3369 0.7
No log 20.0 100 1.2929 0.725
No log 21.0 105 1.2470 0.725
No log 22.0 110 1.2048 0.725
No log 23.0 115 1.1597 0.725
No log 24.0 120 1.1148 0.775
No log 25.0 125 1.0787 0.775
No log 26.0 130 1.0485 0.775
No log 27.0 135 1.0222 0.75
No log 28.0 140 0.9954 0.8
No log 29.0 145 0.9714 0.85
No log 30.0 150 0.9442 0.825
No log 31.0 155 0.9201 0.85
No log 32.0 160 0.9032 0.85
No log 33.0 165 0.8843 0.85
No log 34.0 170 0.8739 0.85
No log 35.0 175 0.8527 0.85
No log 36.0 180 0.8312 0.85
No log 37.0 185 0.8193 0.85
No log 38.0 190 0.8079 0.85
No log 39.0 195 0.8015 0.85
No log 40.0 200 0.7962 0.85
No log 41.0 205 0.7958 0.85
No log 42.0 210 0.7846 0.85
No log 43.0 215 0.7652 0.85
No log 44.0 220 0.7536 0.85
No log 45.0 225 0.7451 0.85
No log 46.0 230 0.7377 0.85
No log 47.0 235 0.7327 0.85
No log 48.0 240 0.7310 0.85
No log 49.0 245 0.7312 0.85
No log 50.0 250 0.7280 0.85

Framework versions

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