Upload BertForSequenceClassification

README.md

@@ -1,26 +1,26 @@
 ---
+language:
+- ar
 license: apache-2.0
-base_model: google-bert/bert-base-multilingual-uncased
 tags:
 - generated_from_trainer
-model-index:
-- name: Arabic-Book-Review-Sentiment-Assessment
-  results: []
+base_model: google-bert/bert-base-multilingual-uncased
 datasets:
 - labr
-language:
-- ar
 widget:
-- text: "كتاب يستحق القراءة"
-  example_title: "مثال 1"
-- text: "ما عجبني بنوب"
-  example_title: "مثال 2"
-- text: "لم يعجبني أبدا"
-  example_title: "مثال 3"
-- text: "أنصح وبشدة قراءة الكتاب خصوصا لمن لديه اهتمام في العلوم الاجتماعية"
-  example_title: "مثال 4"
-- text: "ماشي حالو بعطيه 4 من 10"
-  example_title: "مثال 5"
+- text: كتاب يستحق القراءة
+  example_title: مثال 1
+- text: ما عجبني بنوب
+  example_title: مثال 2
+- text: لم يعجبني أبدا
+  example_title: مثال 3
+- text: أنصح وبشدة قراءة الكتاب خصوصا لمن لديه اهتمام في العلوم الاجتماعية
+  example_title: مثال 4
+- text: ماشي حالو بعطيه 4 من 10
+  example_title: مثال 5
+model-index:
+- name: Arabic-Book-Review-Sentiment-Assessment
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You

config.json

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "google-bert/bert-base-multilingual-uncased",
+  "_name_or_path": "Arabic-Book-Review-Sentiment-Assessment",
   "architectures": [
     "BertForSequenceClassification"
   ],
@@ -10,20 +10,20 @@
   "hidden_dropout_prob": 0.1,
   "hidden_size": 768,
   "id2label": {
-    "0": "LABEL_0",
-    "1": "LABEL_1",
-    "2": "LABEL_2",
-    "3": "LABEL_3",
-    "4": "LABEL_4"
+    "0": "Poor",
+    "1": "Fair",
+    "2": "Good",
+    "3": "Very Good",
+    "4": "Excellent"
   },
   "initializer_range": 0.02,
   "intermediate_size": 3072,
   "label2id": {
-    "LABEL_0": 0,
-    "LABEL_1": 1,
-    "LABEL_2": 2,
-    "LABEL_3": 3,
-    "LABEL_4": 4
+    "Excellent": 4,
+    "Fair": 1,
+    "Good": 2,
+    "Poor": 0,
+    "Very Good": 3
   },
   "layer_norm_eps": 1e-12,
   "max_position_embeddings": 512,
@@ -39,7 +39,7 @@
   "position_embedding_type": "absolute",
   "problem_type": "single_label_classification",
   "torch_dtype": "float32",
-  "transformers_version": "4.39.1",
+  "transformers_version": "4.39.2",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 105879