End of training

README.md

@@ -5,6 +5,9 @@ tags:
 - generated_from_trainer
 metrics:
 - accuracy
+- precision
+- f1
+- recall
 model-index:
 - name: newsdata-bertimbal
   results: []
@@ -17,8 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 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: 0.3387
-- Accuracy: 0.9045
+- Loss: 0.2924
+- Accuracy: 0.9183
+- Precision: 0.9118
+- F1: 0.9144
+- Recall: 0.9183
 
 ## Model description
 
@@ -49,11 +55,17 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
-|:-------------:|:------:|:----:|:---------------:|:--------:|
-| 0.5125        | 0.2749 | 2000 | 0.4810          | 0.8749   |
-| 0.3874        | 0.5498 | 4000 | 0.3903          | 0.8938   |
-| 0.3425        | 0.8247 | 6000 | 0.3387          | 0.9045   |
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | F1     | Recall |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.7154        | 0.1024 | 1000 | 0.5830          | 0.856    | 0.8352    | 0.8399 | 0.856  |
+| 0.5232        | 0.2048 | 2000 | 0.4769          | 0.874    | 0.8647    | 0.8633 | 0.874  |
+| 0.4342        | 0.3071 | 3000 | 0.3966          | 0.891    | 0.8800    | 0.8826 | 0.891  |
+| 0.3969        | 0.4095 | 4000 | 0.3509          | 0.9023   | 0.8900    | 0.8949 | 0.9023 |
+| 0.3719        | 0.5119 | 5000 | 0.3263          | 0.9102   | 0.9055    | 0.9054 | 0.9102 |
+| 0.3638        | 0.6143 | 6000 | 0.3209          | 0.909    | 0.9017    | 0.9035 | 0.909  |
+| 0.3217        | 0.7166 | 7000 | 0.3131          | 0.9068   | 0.9025    | 0.9034 | 0.9068 |
+| 0.3169        | 0.8190 | 8000 | 0.2952          | 0.9167   | 0.9101    | 0.9125 | 0.9167 |
+| 0.3147        | 0.9214 | 9000 | 0.2924          | 0.9183   | 0.9118    | 0.9144 | 0.9183 |
 
 
 ### Framework versions

test_metrics.json

@@ -0,0 +1,10 @@
+{
+    "test_loss": 0.29217079281806946,
+    "test_accuracy": 0.917,
+    "test_precision": 0.9091510305145407,
+    "test_f1": 0.9120262685701904,
+    "test_recall": 0.917,
+    "test_runtime": 60.0375,
+    "test_samples_per_second": 66.625,
+    "test_steps_per_second": 33.313
+}

val_metrics.json

@@ -0,0 +1,10 @@
+{
+    "test_loss": 0.29238182306289673,
+    "test_accuracy": 0.9183333333333333,
+    "test_precision": 0.9118332286016088,
+    "test_f1": 0.9143940987847119,
+    "test_recall": 0.9183333333333333,
+    "test_runtime": 89.1537,
+    "test_samples_per_second": 67.3,
+    "test_steps_per_second": 33.65
+}