Update README.md

README.md

@@ -1,9 +1,14 @@
-classifier_2 = BERTForClassification(bert_model=model, num_classes=6)
+#Overview 
+Model : "bert-base-uncased"
+DataSet: dair-ai/emotion
 
-classifier_2.load_weights('/content/drive/MyDrive/FineTunning2/model2.1/model')
+Training:
+After first epoch, accuracy: 0.6497
+After third epoch, accuracy: 0.9360
 
-example_input = "Your work is very very bad"
+Test:
+accuracy: 0.9265
 
-encoded_example = tokenizer.encode(example_input, padding=True, truncation=True, return_tensors="tf")
+Sentiments:
+sadness (0), joy (1), love (2), anger (3), fear (4), surprise (5)
 
-p = classifier_2(encoded_example)