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camembert_ccnet_classification_tools_classifier-only_fr

Text Classification
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PyTorch
camembert
Generated from Trainer
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camembert_ccnet_classification_tools_classifier-only_fr / README.md
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metadata
base_model: camembert/camembert-base-ccnet
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: camembert_ccnet_classification_tools_classifier-only_fr
    results: []

camembert_ccnet_classification_tools_classifier-only_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: 0.2297
  • Accuracy: 0.975
  • Learning Rate: 0.0

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: 0.001
  • 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 1.7771 0.5 0.0010
No log 2.0 14 1.5458 0.425 0.0010
No log 3.0 21 1.2091 0.75 0.0009
No log 4.0 28 1.0227 0.75 0.0009
No log 5.0 35 0.9105 0.7 0.0009
No log 6.0 42 0.7765 0.825 0.0009
No log 7.0 49 0.7397 0.75 0.0009
No log 8.0 56 0.6652 0.825 0.0009
No log 9.0 63 0.6385 0.775 0.0008
No log 10.0 70 0.6051 0.8 0.0008
No log 11.0 77 0.5246 0.9 0.0008
No log 12.0 84 0.5391 0.825 0.0008
No log 13.0 91 0.5511 0.825 0.0008
No log 14.0 98 0.4780 0.85 0.0008
No log 15.0 105 0.4328 0.925 0.0008
No log 16.0 112 0.4016 0.875 0.0007
No log 17.0 119 0.4902 0.8 0.0007
No log 18.0 126 0.4016 0.9 0.0007
No log 19.0 133 0.4164 0.9 0.0007
No log 20.0 140 0.3814 0.825 0.0007
No log 21.0 147 0.3147 0.95 0.0007
No log 22.0 154 0.3544 0.9 0.0006
No log 23.0 161 0.3438 0.9 0.0006
No log 24.0 168 0.3181 0.95 0.0006
No log 25.0 175 0.3433 0.875 0.0006
No log 26.0 182 0.3197 0.95 0.0006
No log 27.0 189 0.3510 0.875 0.0006
No log 28.0 196 0.3495 0.9 0.0005
No log 29.0 203 0.2704 0.95 0.0005
No log 30.0 210 0.3081 0.975 0.0005
No log 31.0 217 0.3389 0.875 0.0005
No log 32.0 224 0.2695 0.95 0.0005
No log 33.0 231 0.2903 0.925 0.0005
No log 34.0 238 0.3012 0.925 0.0004
No log 35.0 245 0.2804 0.95 0.0004
No log 36.0 252 0.2716 0.95 0.0004
No log 37.0 259 0.3125 0.875 0.0004
No log 38.0 266 0.2501 0.925 0.0004
No log 39.0 273 0.2442 0.95 0.0003
No log 40.0 280 0.2284 0.95 0.0003
No log 41.0 287 0.2363 0.975 0.0003
No log 42.0 294 0.2656 0.975 0.0003
No log 43.0 301 0.2723 0.925 0.0003
No log 44.0 308 0.2302 0.95 0.0003
No log 45.0 315 0.2391 0.95 0.0003
No log 46.0 322 0.2414 0.95 0.0002
No log 47.0 329 0.2506 0.975 0.0002
No log 48.0 336 0.2616 0.975 0.0002
No log 49.0 343 0.2376 0.975 0.0002
No log 50.0 350 0.2310 0.975 0.0002
No log 51.0 357 0.2271 0.95 0.0001
No log 52.0 364 0.2484 0.95 0.0001
No log 53.0 371 0.2633 0.95 0.0001
No log 54.0 378 0.2788 0.925 0.0001
No log 55.0 385 0.2626 0.975 0.0001
No log 56.0 392 0.2454 0.975 0.0001
No log 57.0 399 0.2373 0.975 5e-05
No log 58.0 406 0.2340 0.975 0.0000
No log 59.0 413 0.2291 0.975 0.0000
No log 60.0 420 0.2297 0.975 0.0

Framework versions

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