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metadata
tags:
  - summarization
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: camembert-base-finetuned-sentence-simplification-fr
    results: []

camembert-base-finetuned-sentence-simplification-fr

This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0225
  • Rouge1: 98.9126
  • Rouge2: 96.9479
  • Rougel: 97.9209
  • Rougelsum: 98.9061

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: 2e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum
3.2555 1.0 375 0.7613 41.6446 20.4343 38.0279 41.5954
0.679 2.0 750 0.3463 72.8071 48.9808 60.7026 72.8052
0.4088 3.0 1125 0.1948 85.3976 65.3267 74.3572 85.3705
0.2795 4.0 1500 0.1098 91.8037 78.9948 85.9716 91.8695
0.204 5.0 1875 0.0776 94.6475 84.3954 89.9382 94.6349
0.1544 6.0 2250 0.0454 97.197 91.932 94.8966 97.1919
0.1212 7.0 2625 0.0384 97.5777 93.2443 95.4839 97.5692
0.1037 8.0 3000 0.0315 97.8918 95.2195 96.8449 97.9063
0.0942 9.0 3375 0.0253 98.6234 96.5271 97.6489 98.6284
0.0823 10.0 3750 0.0225 98.9126 96.9479 97.9209 98.9061

Framework versions

  • Transformers 4.23.1
  • Pytorch 1.12.1+cu102
  • Datasets 2.6.1
  • Tokenizers 0.13.1