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README.md

@@ -22,7 +22,7 @@ model_index:
     metric:
       name: Accuracy
       type: accuracy
-      value: 0.9790177823152056
+      value: 0.9801301293674859
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,11 +32,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [neuralmind/bert-large-portuguese-cased](https://huggingface.co/neuralmind/bert-large-portuguese-cased) on the lener_br dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1064
-- Precision: 0.8676
-- Recall: 0.9204
-- F1: 0.8932
-- Accuracy: 0.9790
+- Loss: 0.1271
+- Precision: 0.8965
+- Recall: 0.9198
+- F1: 0.9080
+- Accuracy: 0.9801
 
 ## Model description
 
@@ -61,15 +61,27 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 3
+- num_epochs: 15
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.0601        | 1.0   | 1957 | 0.1097          | 0.8223    | 0.9004 | 0.8596 | 0.9700   |
-| 0.0301        | 2.0   | 3914 | 0.1148          | 0.8070    | 0.9333 | 0.8656 | 0.9722   |
-| 0.0122        | 3.0   | 5871 | 0.1064          | 0.8676    | 0.9204 | 0.8932 | 0.9790   |
+| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0674        | 1.0   | 1957  | 0.1349          | 0.7617    | 0.8710 | 0.8127 | 0.9594   |
+| 0.0443        | 2.0   | 3914  | 0.1867          | 0.6862    | 0.9194 | 0.7858 | 0.9575   |
+| 0.0283        | 3.0   | 5871  | 0.1185          | 0.8206    | 0.8766 | 0.8477 | 0.9678   |
+| 0.0226        | 4.0   | 7828  | 0.1405          | 0.8072    | 0.8978 | 0.8501 | 0.9708   |
+| 0.0141        | 5.0   | 9785  | 0.1898          | 0.7224    | 0.9194 | 0.8090 | 0.9629   |
+| 0.01          | 6.0   | 11742 | 0.1655          | 0.9062    | 0.8856 | 0.8958 | 0.9741   |
+| 0.012         | 7.0   | 13699 | 0.1271          | 0.8965    | 0.9198 | 0.9080 | 0.9801   |
+| 0.0091        | 8.0   | 15656 | 0.1919          | 0.8890    | 0.8886 | 0.8888 | 0.9719   |
+| 0.0042        | 9.0   | 17613 | 0.1725          | 0.8977    | 0.8985 | 0.8981 | 0.9744   |
+| 0.0043        | 10.0  | 19570 | 0.1530          | 0.8878    | 0.9034 | 0.8955 | 0.9761   |
+| 0.0042        | 11.0  | 21527 | 0.1635          | 0.8792    | 0.9108 | 0.8947 | 0.9774   |
+| 0.0033        | 12.0  | 23484 | 0.2009          | 0.8155    | 0.9138 | 0.8619 | 0.9719   |
+| 0.0008        | 13.0  | 25441 | 0.1766          | 0.8737    | 0.9135 | 0.8932 | 0.9755   |
+| 0.0005        | 14.0  | 27398 | 0.1868          | 0.8616    | 0.9129 | 0.8865 | 0.9743   |
+| 0.0014        | 15.0  | 29355 | 0.1910          | 0.8694    | 0.9101 | 0.8893 | 0.9746   |
 
 
 ### Framework versions

pytorch_model.bin

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 size 1333601457

training_args.bin

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+oid sha256:fbb0c401f020911a7fd2ca37c6530ed5e0a5339f7f0da78700f9b56e57901680
 size 2671