readme: ---
  license: mit
  tags:
  - generated_from_trainer
  model-index:
  - name: mdeberta_tcm_0.9_10_epochs
    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. -->
  
  # mdeberta_tcm_0.9_10_epochs
  
  This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0244
  - Criterio Julgamento Precision: 0.8187
  - Criterio Julgamento Recall: 0.9225
  - Criterio Julgamento F1: 0.8675
  - Criterio Julgamento Number: 142
  - Data Sessao Precision: 0.7619
  - Data Sessao Recall: 0.8989
  - Data Sessao F1: 0.8247
  - Data Sessao Number: 89
  - Modalidade Licitacao Precision: 0.9593
  - Modalidade Licitacao Recall: 0.9876
  - Modalidade Licitacao F1: 0.9732
  - Modalidade Licitacao Number: 644
  - Numero Exercicio Precision: 0.9444
  - Numero Exercicio Recall: 0.9878
  - Numero Exercicio F1: 0.9656
  - Numero Exercicio Number: 327
  - Objeto Licitacao Precision: 0.5714
  - Objeto Licitacao Recall: 0.7238
  - Objeto Licitacao F1: 0.6387
  - Objeto Licitacao Number: 105
  - Valor Objeto Precision: 0.9394
  - Valor Objeto Recall: 0.9688
  - Valor Objeto F1: 0.9538
  - Valor Objeto Number: 32
  - Overall Precision: 0.8893
  - Overall Recall: 0.9537
  - Overall F1: 0.9204
  - Overall Accuracy: 0.9958
  
  ## 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: 16
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 32
  - 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-----------------------------:|:--------------------------:|:----------------------:|:--------------------------:|:---------------------:|:------------------:|:--------------:|:------------------:|:------------------------------:|:---------------------------:|:-----------------------:|:---------------------------:|:--------------------------:|:-----------------------:|:-------------------:|:-----------------------:|:--------------------------:|:-----------------------:|:-------------------:|:-----------------------:|:----------------------:|:-------------------:|:---------------:|:-------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
  | 0.1224        | 1.0   | 874  | 0.0200          | 0.8089                        | 0.8944                     | 0.8495                 | 142                        | 0.6484                | 0.9326             | 0.7650         | 89                 | 0.9519                         | 0.9829                      | 0.9672                  | 644                         | 0.9145                     | 0.9817                  | 0.9469              | 327                     | 0.2658                     | 0.4                     | 0.3194              | 105                     | 0.7027                 | 0.8125              | 0.7536          | 32                  | 0.8235            | 0.9201         | 0.8691     | 0.9942           |
  | 0.0178        | 2.0   | 1748 | 0.0190          | 0.7927                        | 0.9155                     | 0.8497                 | 142                        | 0.68                  | 0.9551             | 0.7944         | 89                 | 0.9550                         | 0.9876                      | 0.9710                  | 644                         | 0.9235                     | 0.9969                  | 0.9588              | 327                     | 0.4564                     | 0.6476                  | 0.5354              | 105                     | 0.8378                 | 0.9688              | 0.8986          | 32                  | 0.8541            | 0.9529         | 0.9008     | 0.9953           |
  | 0.0119        | 3.0   | 2622 | 0.0210          | 0.7952                        | 0.9296                    