Update README.md

README.md

@@ -11,31 +11,46 @@ This model is a Long Short-Term Memory (LSTM) model trained with GloVe embedding
 This model can be used for cybercrime classification tasks. 
 
 Accuracy: 0.9803
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 Precision: 0.9804
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 Recall: 0.9803
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 F1 Score: 0.9803
 
 See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
   df_org['label'] = df_org['label'].replace('unknown', 'not cybercrime')  # Replace 'unknown' with 'not cybercrime'
 <ipython-input-6-8f9ee34c78b4>:37: DeprecationWarning: DataFrameGroupBy.apply operated on the grouping columns. This behavior is deprecated, and in a future version of pandas the grouping columns will be excluded from the operation. Either pass `include_groups=False` to exclude the groupings or explicitly select the grouping columns after groupby to silence this warning.
   df_balanced = df_org.groupby('label', group_keys=False).apply(lambda x: x.sample(max_samples, replace=True))
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 Epoch 1/10
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 158/158 [==============================] - 65s 316ms/step - loss: 1.4255 - accuracy: 0.5900 - val_loss: 0.9644 - val_accuracy: 0.8066
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 Epoch 2/10
 158/158 [==============================] - 73s 461ms/step - loss: 0.6081 - accuracy: 0.8742 - val_loss: 0.3353 - val_accuracy: 0.9132
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 Epoch 3/10
 158/158 [==============================] - 50s 316ms/step - loss: 0.2752 - accuracy: 0.9344 - val_loss: 0.1922 - val_accuracy: 0.9534
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 Epoch 4/10
 158/158 [==============================] - 59s 376ms/step - loss: 0.1848 - accuracy: 0.9563 - val_loss: 0.1487 - val_accuracy: 0.9664
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 Epoch 5/10
 158/158 [==============================] - 66s 419ms/step - loss: 0.1423 - accuracy: 0.9676 - val_loss: 0.1272 - val_accuracy: 0.9714
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 Epoch 6/10
 158/158 [==============================] - 64s 408ms/step - loss: 0.1176 - accuracy: 0.9722 - val_loss: 0.1133 - val_accuracy: 0.9745
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 Epoch 7/10
 158/158 [==============================] - 67s 422ms/step - loss: 0.0971 - accuracy: 0.9789 - val_loss: 0.1042 - val_accuracy: 0.9749
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 Epoch 8/10
 158/158 [==============================] - 76s 479ms/step - loss: 0.0814 - accuracy: 0.9818 - val_loss: 0.0910 - val_accuracy: 0.9794
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 Epoch 9/10
 158/158 [==============================] - 51s 324ms/step - loss: 0.0727 - accuracy: 0.9859 - val_loss: 0.0862 - val_accuracy: 0.9799
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 Epoch 10/10
 158/158 [==============================] - 41s 260ms/step - loss: 0.0638 - accuracy: 0.9864 - val_loss: 0.0791 - val_accuracy: 0.9803
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