modelo_test

This model is a fine-tuned version of PlanTL-GOB-ES/roberta-large-bne on the luisgasco/profner_classification_master dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2443
  • Accuracy: 0.9619
  • F1 Score: 0.9224

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: 1e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 69
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Use 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: 6

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Score
0.5843 0.2865 50 0.3705 0.83 0.7231
0.2483 0.5731 100 0.1913 0.942 0.8872
0.2024 0.8596 150 0.1619 0.954 0.9091
0.1972 1.1433 200 0.2304 0.942 0.8872
0.1093 1.4298 250 0.2269 0.958 0.9157
0.0658 1.7163 300 0.2079 0.956 0.9098
0.0806 2.0 350 0.2081 0.954 0.9076
0.0194 2.2865 400 0.2177 0.956 0.9091
0.0165 2.5731 450 0.2319 0.962 0.9224
0.0507 2.8596 500 0.1857 0.956 0.9098
0.0393 3.1433 550 0.2356 0.954 0.9091
0.0057 3.4298 600 0.2623 0.952 0.9055
0.0114 3.7163 650 0.2037 0.962 0.9218
0.0011 4.0 700 0.2164 0.964 0.9268
0.0012 4.2865 750 0.2124 0.966 0.9289
0.0022 4.5731 800 0.2360 0.962 0.9237
0.0087 4.8596 850 0.2205 0.966 0.9306
0.0002 5.1433 900 0.2256 0.964 0.9268
0.0001 5.4298 950 0.2293 0.962 0.9231
0.0001 5.7163 1000 0.2312 0.962 0.9231
0.0001 6.0 1050 0.2318 0.962 0.9231

Framework versions

  • Transformers 4.53.1
  • Pytorch 2.7.1+cu126
  • Datasets 3.6.0
  • Tokenizers 0.21.2
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