Luciano
/

bertimbau-base-finetuned-lener-br-finetuned-brazilian_court_decisions

@@ -16,8 +16,8 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [Luciano/bertimbau-base-finetuned-lener-br](https://huggingface.co/Luciano/bertimbau-base-finetuned-lener-br) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.5456
-- Accuracy: 0.7822
 ## Model description
@@ -37,8 +37,8 @@ More information needed
 The following hyperparameters were used during training:
 - learning_rate: 2e-05
-- train_batch_size: 16
-- eval_batch_size: 16
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
@@ -48,21 +48,21 @@ The following hyperparameters were used during training:
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 1.0   | 203  | 0.7854          | 0.6683   |
-| No log        | 2.0   | 406  | 0.6289          | 0.7574   |
-| 0.6974        | 3.0   | 609  | 0.6930          | 0.7822   |
-| 0.6974        | 4.0   | 812  | 0.7168          | 0.7649   |
-| 0.2928        | 5.0   | 1015 | 0.8712          | 0.7822   |
-| 0.2928        | 6.0   | 1218 | 0.9827          | 0.7772   |
-| 0.2928        | 7.0   | 1421 | 1.1399          | 0.7624   |
-| 0.1056        | 8.0   | 1624 | 1.2653          | 0.7847   |
-| 0.1056        | 9.0   | 1827 | 1.3478          | 0.7673   |
-| 0.0403        | 10.0  | 2030 | 1.4290          | 0.7673   |
-| 0.0403        | 11.0  | 2233 | 1.4404          | 0.7797   |
-| 0.0403        | 12.0  | 2436 | 1.4250          | 0.7797   |
-| 0.016         | 13.0  | 2639 | 1.5548          | 0.7797   |
-| 0.016         | 14.0  | 2842 | 1.5110          | 0.7871   |
-| 0.0055        | 15.0  | 3045 | 1.5456          | 0.7822   |
 ### Framework versions

 This model is a fine-tuned version of [Luciano/bertimbau-base-finetuned-lener-br](https://huggingface.co/Luciano/bertimbau-base-finetuned-lener-br) on an unknown dataset.
 It achieves the following results on the evaluation set:
+- Loss: 1.8017
+- Accuracy: 0.7698
 ## Model description
 The following hyperparameters were used during training:
 - learning_rate: 2e-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
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 405  | 0.7790          | 0.6535   |
+| 0.8276        | 2.0   | 810  | 0.6739          | 0.7277   |
+| 0.5818        | 3.0   | 1215 | 0.8767          | 0.7302   |
+| 0.4147        | 4.0   | 1620 | 0.8229          | 0.7896   |
+| 0.287         | 5.0   | 2025 | 0.9874          | 0.7921   |
+| 0.287         | 6.0   | 2430 | 1.2301          | 0.7772   |
+| 0.1727        | 7.0   | 2835 | 1.2864          | 0.7946   |
+| 0.1179        | 8.0   | 3240 | 1.5097          | 0.7772   |
+| 0.0709        | 9.0   | 3645 | 1.4772          | 0.7921   |
+| 0.0437        | 10.0  | 4050 | 1.5581          | 0.7797   |
+| 0.0437        | 11.0  | 4455 | 1.6317          | 0.7896   |
+| 0.0318        | 12.0  | 4860 | 1.7295          | 0.7822   |
+| 0.0158        | 13.0  | 5265 | 1.7333          | 0.7797   |
+| 0.0108        | 14.0  | 5670 | 1.8008          | 0.7772   |
+| 0.0137        | 15.0  | 6075 | 1.8017          | 0.7698   |
 ### Framework versions