update model card README.md

README.md

@@ -2,6 +2,8 @@
 license: mit
 tags:
 - generated_from_trainer
+datasets:
+- ricardo-filho/tcm-0.9-no-valor-objeto
 model-index:
 - name: bert_base_tcm_0.9_no_valor_objeto
   results: []
@@ -12,33 +14,33 @@ should probably proofread and complete it, then remove this comment. -->
 
 # bert_base_tcm_0.9_no_valor_objeto
 
-This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on the None dataset.
+This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on the ricardo-filho/tcm-0.9-no-valor-objeto dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0324
-- Criterio Julgamento Precision: 0.8141
-- Criterio Julgamento Recall: 0.8944
-- Criterio Julgamento F1: 0.8523
+- Loss: 0.0176
+- Criterio Julgamento Precision: 0.8310
+- Criterio Julgamento Recall: 0.8310
+- Criterio Julgamento F1: 0.8310
 - Criterio Julgamento Number: 142
-- Data Sessao Precision: 0.7524
-- Data Sessao Recall: 0.8778
-- Data Sessao F1: 0.8103
+- Data Sessao Precision: 0.7909
+- Data Sessao Recall: 0.9667
+- Data Sessao F1: 0.87
 - Data Sessao Number: 90
-- Modalidade Licitacao Precision: 0.9680
+- Modalidade Licitacao Precision: 0.9564
 - Modalidade Licitacao Recall: 0.9815
-- Modalidade Licitacao F1: 0.9747
+- Modalidade Licitacao F1: 0.9688
 - Modalidade Licitacao Number: 648
-- Numero Exercicio Precision: 0.9494
-- Numero Exercicio Recall: 0.9667
-- Numero Exercicio F1: 0.9580
+- Numero Exercicio Precision: 0.9362
+- Numero Exercicio Recall: 0.9788
+- Numero Exercicio F1: 0.9570
 - Numero Exercicio Number: 330
-- Objeto Licitacao Precision: 0.5878
-- Objeto Licitacao Recall: 0.7264
-- Objeto Licitacao F1: 0.6498
+- Objeto Licitacao Precision: 0.4460
+- Objeto Licitacao Recall: 0.5849
+- Objeto Licitacao F1: 0.5061
 - Objeto Licitacao Number: 106
-- Overall Precision: 0.8939
-- Overall Recall: 0.9407
-- Overall F1: 0.9167
-- Overall Accuracy: 0.9954
+- Overall Precision: 0.8751
+- Overall Recall: 0.9316
+- Overall F1: 0.9025
+- Overall Accuracy: 0.9953
 
 ## Model description