readme: ---
  license: mit
  tags:
  - generated_from_trainer
  model-index:
  - name: bert_base_tcm_0.7
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # bert_base_tcm_0.7
  
  This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0128
  - Criterio Julgamento Precision: 0.8235
  - Criterio Julgamento Recall: 0.9032
  - Criterio Julgamento F1: 0.8615
  - Criterio Julgamento Number: 93
  - Data Sessao Precision: 0.7324
  - Data Sessao Recall: 0.9286
  - Data Sessao F1: 0.8189
  - Data Sessao Number: 56
  - Modalidade Licitacao Precision: 0.9415
  - Modalidade Licitacao Recall: 0.9769
  - Modalidade Licitacao F1: 0.9589
  - Modalidade Licitacao Number: 346
  - Numero Exercicio Precision: 0.9486
  - Numero Exercicio Recall: 0.9486
  - Numero Exercicio F1: 0.9486
  - Numero Exercicio Number: 175
  - Objeto Licitacao Precision: 0.5352
  - Objeto Licitacao Recall: 0.6909
  - Objeto Licitacao F1: 0.6032
  - Objeto Licitacao Number: 55
  - Valor Objeto Precision: 0.8
  - Valor Objeto Recall: 0.8649
  - Valor Objeto F1: 0.8312
  - Valor Objeto Number: 37
  - Overall Precision: 0.8680
  - Overall Recall: 0.9318
  - Overall F1: 0.8987
  - Overall Accuracy: 0.9966
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10.0
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Criterio Julgamento Precision | Criterio Julgamento Recall | Criterio Julgamento F1 | Criterio Julgamento Number | Data Sessao Precision | Data Sessao Recall | Data Sessao F1 | Data Sessao Number | Modalidade Licitacao Precision | Modalidade Licitacao Recall | Modalidade Licitacao F1 | Modalidade Licitacao Number | Numero Exercicio Precision | Numero Exercicio Recall | Numero Exercicio F1 | Numero Exercicio Number | Objeto Licitacao Precision | Objeto Licitacao Recall | Objeto Licitacao F1 | Objeto Licitacao Number | Valor Objeto Precision | Valor Objeto Recall | Valor Objeto F1 | Valor Objeto Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:-----------------------------:|:--------------------------:|:----------------------:|:--------------------------:|:---------------------:|:------------------:|:--------------:|:------------------:|:------------------------------:|:---------------------------:|:-----------------------:|:---------------------------:|:--------------------------:|:-----------------------:|:-------------------:|:-----------------------:|:--------------------------:|:-----------------------:|:-------------------:|:-----------------------:|:----------------------:|:-------------------:|:---------------:|:-------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
  | 0.0267        | 1.0   | 2332  | 0.0175          | 0.8333                        | 0.9140                     | 0.8718                 | 93                         | 0.6825                | 0.7679             | 0.7227         | 56                 | 0.9342                         | 0.9855                      | 0.9592                  | 346                         | 0.9194                     | 0.9771                  | 0.9474              | 175                     | 0.4154                     | 0.4909                  | 0.45                | 55                      | 0.5                    | 0.7568              | 0.6022          | 37                  | 0.8303            | 0.9121         | 0.8693     | 0.9954           |
  | 0.0211        | 2.0   | 4664  | 0.0158          | 0.7154                        | 0.9462                     | 0.8148                 | 93                         | 0.7812                | 0.8929             | 0.8333         | 56                 | 0.9319                         | 0.9884                      | 0.9593                  | 346                         | 0.9605                     | 0.9714                  | 0.9659              | 175                     | 0.4                        | 0.6545                  | 0.4966              | 55                      | 0.8293                 | 0.9189              | 0.8718          | 37                  | 0.8353            | 0.9449         | 0.8867     | 0.9956           |
  | 0.0127        | 3.0   | 6996  | 0.0157          | 0.8218                        | 0.8925                     | 0.8557                 | 93                         | 0.