update README

README.md

@@ -4,33 +4,34 @@ tags:
 metrics:
 - accuracy
 model-index:
-- name: test-mlm-bert-base-uncased-pcap-3M-mixed
+- name: NetFID-PCAP-IP-Header
   results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
 
-# test-mlm-bert-base-uncased-pcap-3M-mixed
+# NetFID-PCAP-IP-Header
 
-This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
+This model is a train-from-scratch version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on a mixed-source PCAP dataset.
 It achieves the following results on the evaluation set:
 - Loss: 0.8973
 - Accuracy: 0.7592
 
 ## Model description
-
-More information needed
+Pretrained model with [bert-base-uncased](https://huggingface.co/bert-base-uncased) (110M parameters) as the base architecture.
 
 ## Intended uses & limitations
+This model is mainly used to get embeddings for PCAP IPv4 header data, which can be further used for ML-based tasks e.g., classification, clustering, etc.
 
-More information needed
+## How to use
+The usage is almost the same as regular BERT models, except that the input data is PCAP traces.
 
 ## Training and evaluation data
-
-More information needed
+TBD.
 
 ## Training procedure
+TBD.
 
 ### Training hyperparameters