Training 20251208_194407 - 6 classes with metrics

README.md

@@ -19,15 +19,15 @@ model-index:
       type: legal_documents
     metrics:
     - type: accuracy
-      value: 0.924822695035461
+      value: 0.936231884057971
     - type: f1
-      value: 0.9194249427990718
+      value: 0.9353615414017292
     - type: precision
-      value: 0.9170301776376935
+      value: 0.9369069235885541
     - type: recall
-      value: 0.924822695035461
+      value: 0.936231884057971
     - type: f1_macro
-      value: 0.7914249223969743
+      value: 0.8474441104841182
 ---
 
 # Model Card for Model ID
@@ -51,7 +51,7 @@ Este modelo foi treinado para classificar documentos jurídicos brasileiros usan
 
 - **Base Model:** google-bert/bert-base-multilingual-cased
 - **Tipo:** Classificação Multiclasse
-- **Número de Classes:** 7
+- **Número de Classes:** 6
 - **Idioma:** Português (Brasil)
 - **Domínio:** Documentos Jurídicos
 
@@ -59,38 +59,36 @@ Este modelo foi treinado para classificar documentos jurídicos brasileiros usan
 
 0. Alvará
 1. Sentença
-2. Penhora/Arresto/Sequestro
+2. Penhora
 3. Citação
-4. Art.40
-5. Não
-6. teste 123
+4. Art. 40
+5. Não Influencia
 
 ## Métricas de Avaliação
 
 As métricas abaixo foram calculadas no conjunto de validação:
 
-- **Accuracy:** 0.9248
-- **F1-Score (Weighted):** 0.9194
-- **Precision (Weighted):** 0.9170
-- **Recall (Weighted):** 0.9248
-- **F1-Score (Macro):** 0.7914
+- **Accuracy:** 0.9362
+- **F1-Score (Weighted):** 0.9354
+- **Precision (Weighted):** 0.9369
+- **Recall (Weighted):** 0.9362
+- **F1-Score (Macro):** 0.8474
 
 ## Classification Report Completo
 
 ```
               precision    recall  f1-score   support
 
-           0       0.00      0.00      0.00         7
-           1       0.94      1.00      0.97        47
-           2       0.94      0.77      0.85        57
-           3       0.80      0.97      0.88        34
-           4       0.94      0.87      0.90       120
-           5       0.93      0.96      0.94       423
-           6       1.00      1.00      1.00        17
-
-    accuracy                           0.92       705
-   macro avg       0.79      0.80      0.79       705
-weighted avg       0.92      0.92      0.92       705
+           0       0.60      0.38      0.46         8
+           1       0.86      0.98      0.92        45
+           2       1.00      0.85      0.92        54
+           3       0.85      0.95      0.90        41
+           4       0.93      0.95      0.94       121
+           5       0.95      0.95      0.95       421
+
+    accuracy                           0.94       690
+   macro avg       0.87      0.84      0.85       690
+weighted avg       0.94      0.94      0.94       690
 
 ```
 

config.json

@@ -10,24 +10,22 @@
   "hidden_dropout_prob": 0.1,
   "hidden_size": 768,
   "id2label": {
-    "0": "Alvar\u00e1",
-    "1": "Senten\u00e7a",
-    "2": "Penhora/Arresto/Sequestro",
-    "3": "Cita\u00e7\u00e3o",
-    "4": "Art.40",
-    "5": "N\u00e3o",
-    "6": "teste 123"
+    "0": "646bb41b351734d0a39bb557",
+    "1": "652026c3798f7600075f9d40",
+    "2": "646bc57bc7605185f40b4263",
+    "3": "646b78c3dc761bc8c743a0c6",
+    "4": "645d42ebbacbc7baba32624d",
+    "5": "64ac68185fe31ca8ad57a822"
   },
   "initializer_range": 0.02,
   "intermediate_size": 3072,
   "label2id": {
-    "Alvar\u00e1": 0,
-    "Art.40": 4,
-    "Cita\u00e7\u00e3o": 3,
-    "N\u00e3o": 5,
-    "Penhora/Arresto/Sequestro": 2,
-    "Senten\u00e7a": 1,
-    "teste 123": 6
+    "645d42ebbacbc7baba32624d": 4,
+    "646b78c3dc761bc8c743a0c6": 3,
+    "646bb41b351734d0a39bb557": 0,
+    "646bc57bc7605185f40b4263": 2,
+    "64ac68185fe31ca8ad57a822": 5,
+    "652026c3798f7600075f9d40": 1
   },
   "layer_norm_eps": 1e-12,
   "max_position_embeddings": 512,

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:8e7a51405646562397dff1b29b51513a1d2f354d8be5165327e43849dec09a6a
-size 711458836
+oid sha256:ebbc0bde22fe9605d6b416bb40abfd1a9c25bb23293ebd059249447c5a5db0fb
+size 711455760