eurobert210m_EconomieCirculaire_v1

This model is a fine-tuned version of EuroBERT/EuroBERT-210m on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0142
  • Accuracy: 0.9978
  • F1: 0.9978

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: 5e-05
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 100
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
0.6621 1.0 98 0.2769 0.9096 0.9112
0.296 2.0 196 0.1087 0.9671 0.9671
0.1875 3.0 294 0.1938 0.9457 0.9457
0.1906 4.0 392 0.0815 0.9751 0.9751
0.1295 5.0 490 0.1025 0.9687 0.9688
0.1131 6.0 588 0.1083 0.9729 0.9727
0.0841 7.0 686 0.0665 0.9824 0.9825
0.0708 8.0 784 0.0390 0.9882 0.9882
0.0812 9.0 882 0.0457 0.9895 0.9895
0.0939 10.0 980 0.0423 0.9904 0.9904
0.0609 11.0 1078 0.0196 0.9968 0.9968
0.0299 12.0 1176 0.0372 0.9939 0.9939
0.0192 13.0 1274 0.0203 0.9968 0.9968
0.0267 14.0 1372 0.0201 0.9968 0.9968
0.026 15.0 1470 0.0174 0.9958 0.9958
0.0178 16.0 1568 0.0349 0.9965 0.9965
0.0225 17.0 1666 0.0182 0.9971 0.9971
0.0381 18.0 1764 0.0080 0.9974 0.9974
0.0086 19.0 1862 0.0106 0.9981 0.9981
0.056 20.0 1960 0.0237 0.9949 0.9949
0.0284 21.0 2058 0.0142 0.9978 0.9978

Framework versions

  • Transformers 4.48.3
  • Pytorch 2.5.1+cu124
  • Datasets 3.3.2
  • Tokenizers 0.21.0
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