ModernBERT-base-2-contract-sections-classification-v4-10-max
This model is a fine-tuned version of answerdotai/ModernBERT-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4801
- Accuracy Evaluate: 0.917
- Precision Evaluate: 0.9221
- Recall Evaluate: 0.9209
- F1 Evaluate: 0.9210
- Accuracy Sklearn: 0.917
- Precision Sklearn: 0.9173
- Recall Sklearn: 0.917
- F1 Sklearn: 0.9166
- Acuracia Rotulo Objeto: 0.9649
- Acuracia Rotulo Obrigacoes: 0.8838
- Acuracia Rotulo Valor: 0.8166
- Acuracia Rotulo Vigencia: 0.9816
- Acuracia Rotulo Rescisao: 0.9474
- Acuracia Rotulo Foro: 0.9385
- Acuracia Rotulo Reajuste: 0.9039
- Acuracia Rotulo Fiscalizacao: 0.8423
- Acuracia Rotulo Publicacao: 0.9951
- Acuracia Rotulo Pagamento: 0.8913
- Acuracia Rotulo Casos Omissos: 0.9015
- Acuracia Rotulo Sancoes: 0.9266
- Acuracia Rotulo Dotacao Orcamentaria: 0.9780
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-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy Evaluate | Precision Evaluate | Recall Evaluate | F1 Evaluate | Accuracy Sklearn | Precision Sklearn | Recall Sklearn | F1 Sklearn | Acuracia Rotulo Objeto | Acuracia Rotulo Obrigacoes | Acuracia Rotulo Valor | Acuracia Rotulo Vigencia | Acuracia Rotulo Rescisao | Acuracia Rotulo Foro | Acuracia Rotulo Reajuste | Acuracia Rotulo Fiscalizacao | Acuracia Rotulo Publicacao | Acuracia Rotulo Pagamento | Acuracia Rotulo Casos Omissos | Acuracia Rotulo Sancoes | Acuracia Rotulo Dotacao Orcamentaria |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2.3971 | 1.0 | 2000 | 0.8286 | 0.7678 | 0.8292 | 0.7831 | 0.7914 | 0.7678 | 0.8077 | 0.7678 | 0.7695 | 0.9504 | 0.6734 | 0.5244 | 0.6115 | 0.8975 | 0.8808 | 0.6512 | 0.7382 | 0.9113 | 0.7754 | 0.8227 | 0.7982 | 0.9451 |
1.3917 | 2.0 | 4000 | 0.6639 | 0.8558 | 0.8777 | 0.8708 | 0.8702 | 0.8558 | 0.8673 | 0.8558 | 0.8557 | 0.9587 | 0.7357 | 0.6619 | 0.8976 | 0.9030 | 0.9231 | 0.8719 | 0.7918 | 0.9655 | 0.8587 | 0.8867 | 0.8991 | 0.9670 |
0.887 | 3.0 | 6000 | 0.5830 | 0.874 | 0.8789 | 0.8885 | 0.8804 | 0.874 | 0.8812 | 0.874 | 0.8743 | 0.9442 | 0.7761 | 0.7421 | 0.9081 | 0.8615 | 0.9346 | 0.9004 | 0.8265 | 0.9852 | 0.8841 | 0.9015 | 0.9083 | 0.9780 |
0.9516 | 4.0 | 8000 | 0.5632 | 0.8885 | 0.8987 | 0.8992 | 0.8979 | 0.8885 | 0.8899 | 0.8885 | 0.8881 | 0.9194 | 0.8081 | 0.7736 | 0.9554 | 0.9474 | 0.9385 | 0.8719 | 0.8297 | 0.9803 | 0.8877 | 0.8818 | 0.9174 | 0.9780 |
0.7614 | 5.0 | 10000 | 0.5290 | 0.8998 | 0.9083 | 0.9102 | 0.9084 | 0.8998 | 0.9021 | 0.8998 | 0.8998 | 0.9628 | 0.8064 | 0.8052 | 0.9370 | 0.9418 | 0.9846 | 0.8897 | 0.8328 | 0.9951 | 0.8804 | 0.9015 | 0.9174 | 0.9780 |
0.6291 | 6.0 | 12000 | 0.5590 | 0.8978 | 0.9029 | 0.9089 | 0.9044 | 0.8978 | 0.9009 | 0.8978 | 0.8975 | 0.9421 | 0.7946 | 0.7880 | 0.9764 | 0.9391 | 0.9385 | 0.9075 | 0.8454 | 0.9951 | 0.8913 | 0.9064 | 0.9083 | 0.9835 |
0.4869 | 7.0 | 14000 | 0.4875 | 0.9103 | 0.9140 | 0.9156 | 0.9143 | 0.9103 | 0.9102 | 0.9103 | 0.9096 | 0.9587 | 0.8737 | 0.7966 | 0.9790 | 0.9446 | 0.9346 | 0.9039 | 0.8139 | 0.9951 | 0.8913 | 0.9064 | 0.9266 | 0.9780 |
0.5691 | 8.0 | 16000 | 0.4929 | 0.9083 | 0.9119 | 0.9162 | 0.9134 | 0.9083 | 0.9093 | 0.9083 | 0.9079 | 0.9607 | 0.8232 | 0.8195 | 0.9843 | 0.9446 | 0.9385 | 0.8932 | 0.8580 | 0.9951 | 0.8913 | 0.9064 | 0.9174 | 0.9780 |
0.3831 | 9.0 | 18000 | 0.4892 | 0.9153 | 0.9184 | 0.9198 | 0.9186 | 0.9153 | 0.9157 | 0.9153 | 0.9149 | 0.9649 | 0.8737 | 0.8138 | 0.9843 | 0.9446 | 0.9385 | 0.8968 | 0.8486 | 0.9951 | 0.8913 | 0.9015 | 0.9266 | 0.9780 |
0.3 | 10.0 | 20000 | 0.4801 | 0.917 | 0.9221 | 0.9209 | 0.9210 | 0.917 | 0.9173 | 0.917 | 0.9166 | 0.9649 | 0.8838 | 0.8166 | 0.9816 | 0.9474 | 0.9385 | 0.9039 | 0.8423 | 0.9951 | 0.8913 | 0.9015 | 0.9266 | 0.9780 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.0
- Tokenizers 0.21.0
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Model tree for marcelovidigal/ModernBERT-base-2-contract-sections-classification-v4-10-max
Base model
answerdotai/ModernBERT-base