End of training

README.md

@@ -25,16 +25,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.761528608027327
+      value: 0.7959714100064977
     - name: Recall
       type: recall
-      value: 0.7616912235746316
+      value: 0.7847533632286996
     - name: F1
       type: f1
-      value: 0.7616099071207431
+      value: 0.7903225806451614
     - name: Accuracy
       type: accuracy
-      value: 0.9554657562878841
+      value: 0.959060823521215
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -44,11 +44,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [distilbert/distilbert-base-multilingual-cased](https://huggingface.co/distilbert/distilbert-base-multilingual-cased) on the lener_br dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1792
-- Precision: 0.7615
-- Recall: 0.7617
-- F1: 0.7616
-- Accuracy: 0.9555
+- Loss: 0.1904
+- Precision: 0.7960
+- Recall: 0.7848
+- F1: 0.7903
+- Accuracy: 0.9591
 
 ## Model description
 
@@ -73,18 +73,22 @@ 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: 100
+- num_epochs: 10
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.0   | 490  | 0.2100          | 0.7139    | 0.6624 | 0.6872 | 0.9394   |
-| 0.2608        | 2.0   | 980  | 0.1962          | 0.7059    | 0.7508 | 0.7276 | 0.9443   |
-| 0.0681        | 3.0   | 1470 | 0.1858          | 0.7225    | 0.7649 | 0.7431 | 0.9486   |
-| 0.0382        | 4.0   | 1960 | 0.1792          | 0.7615    | 0.7617 | 0.7616 | 0.9555   |
-| 0.0248        | 5.0   | 2450 | 0.2068          | 0.7715    | 0.8149 | 0.7926 | 0.9560   |
-| 0.0173        | 6.0   | 2940 | 0.2029          | 0.7112    | 0.8031 | 0.7544 | 0.9529   |
+| No log        | 1.0   | 490  | 0.2124          | 0.6794    | 0.6842 | 0.6818 | 0.9363   |
+| 0.2601        | 2.0   | 980  | 0.1744          | 0.701     | 0.7485 | 0.7239 | 0.9486   |
+| 0.0688        | 3.0   | 1470 | 0.1653          | 0.7344    | 0.7598 | 0.7469 | 0.9522   |
+| 0.0375        | 4.0   | 1960 | 0.1868          | 0.7764    | 0.7429 | 0.7593 | 0.9546   |
+| 0.0229        | 5.0   | 2450 | 0.1844          | 0.7748    | 0.7854 | 0.7801 | 0.9560   |
+| 0.0162        | 6.0   | 2940 | 0.2072          | 0.6896    | 0.7929 | 0.7377 | 0.9462   |
+| 0.0123        | 7.0   | 3430 | 0.1941          | 0.7612    | 0.7704 | 0.7658 | 0.9548   |
+| 0.0078        | 8.0   | 3920 | 0.1900          | 0.7701    | 0.7909 | 0.7804 | 0.9581   |
+| 0.0068        | 9.0   | 4410 | 0.1884          | 0.8000    | 0.7822 | 0.7910 | 0.9593   |
+| 0.0045        | 10.0  | 4900 | 0.1904          | 0.7960    | 0.7848 | 0.7903 | 0.9591   |
 
 
 ### Framework versions

model.safetensors

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