Update README.md

README.md

@@ -6,28 +6,51 @@ pipeline_tag: text-classification
 datasets:
 - 19kmunz/iot-23-preprocessed-minimumcolumns
 ---
+## introduction
 This is an undergraduate course project in computer security.
 
 The task is to fine tune the large model to achieve malicious network flow data detection.
 
-dataset:
-19kmunz/iot-23-preprocessed-minimumcolumns
+## base model
+bert-base-uncased
 
-example prompt:
+## dataset:
+19kmunz/iot-23-preprocessed-minimumcolumns
 
+## example prompt:
+```markdown
 134 icmp OTH 2 96 0
 37215 tcp S0 2 80 0
 52869 tcp S0 2 80 0
 8080 tcp S0 2 80 0
 80 tcp S0 2 80 0
-
+```
 The above are "malicious", which is "label_1".
-
+```markdown
 67 udp S0 11 3608 0
 0 icmp OTH 9 844 0
 136 icmp OTH 3 216 0
 0 icmp OTH 8 648 0
 134 icmp OTH 2 96 0
-
+```
 The above are "Benign", which is "label_0".
 
+## accuracy
+```markdown
+	Training Loss	Valid. Loss	Valid. Accur.
+epoch					
+1	0.288545	0.190351	0.929988
+2	0.147658	0.154426	0.943510
+3	0.108059	0.173112	0.943510
+4	0.092468	0.161035	0.947416
+```
+
+## MCC score： 0.816
+
+The "Total MCC" refers to the Matthews Correlation Coefficient (MCC), typically used to assess the quality of predictions in binary classification problems. 
+
+The MCC value ranges from -1 to 1, where 1 signifies perfect predictions, 0 indicates predictions similar to random chance, and -1 denotes completely opposite predictions.
+
+A model with an MCC value of 0.816 can be considered quite good. This value being close to 1 implies that the model has a high predictive capability and can classify samples with considerable accuracy. A higher MCC value closer to 1 indicates stronger predictive ability in the model.
+
+In summary, an MCC value of 0.816 indicates that the model demonstrates a high level of accuracy and predictive capability in binary classification tasks.