Training update: 164,792/337,148 rows (48.88%) | +1000 new @ 2026-03-27 07:48:21

README.md

@@ -25,7 +25,7 @@ pipeline_tag: fill-mask
 - Model type: fine-tuned lightweight BERT variant  
 - Languages: English & Indonesia
 - Finetuned from: `boltuix/bert-micro`
-- Status: **Early version** — trained on **49.06%** of planned data.
+- Status: **Early version** — trained on **48.88%** of planned data.
 
 **Model sources**  
 - Base model: [boltuix/bert-micro](https://huggingface.co/boltuix/bert-micro)
@@ -51,7 +51,7 @@ You can use this model to classify cybersecurity-related text — for example, w
 - Early classification of SIEM alert & events.
 
 ## 3. Bias, Risks, and Limitations 
-Because the model is based on a small subset (49.06%) of planned data, performance is preliminary and may degrade on unseen or specialized domains (industrial control, IoT logs, foreign language).
+Because the model is based on a small subset (48.88%) of planned data, performance is preliminary and may degrade on unseen or specialized domains (industrial control, IoT logs, foreign language).
 - Inherits any biases present in the base model (`boltuix/bert-micro`) and in the fine-tuning data — e.g., over-representation of certain threat types, vendor or tooling-specific vocabulary.
 - **Should not be used as sole authority for incident decisions; only as an aid to human analysts.**
 
@@ -75,9 +75,9 @@ Since cybersecurity data often contains lengthy alert descriptions and execution
 - **LR scheduler**: Linear with warmup
 
 ### Training Data
-- **Total database rows**: 335,877
-- **Rows processed (cumulative)**: 164,788 (49.06%)
-- **Training date**: 2026-03-17 17:32:38
+- **Total database rows**: 337,148
+- **Rows processed (cumulative)**: 164,792 (48.88%)
+- **Training date**: 2026-03-27 07:48:21
 
 ### Post-Training Metrics
 - **Final training loss**: 

config.json

@@ -22,7 +22,7 @@
   "pad_token_id": 0,
   "position_embedding_type": "absolute",
   "tie_word_embeddings": true,
-  "transformers_version": "5.3.0",
+  "transformers_version": "5.4.0",
   "type_vocab_size": 2,
   "use_cache": false,
   "vocab_size": 30522

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:a5f3f1256b3277d5a7c851b1e7bab3c3a6568906b5368627a07081a0b90857df
+oid sha256:6909820cf3da69d442f30dbdbf9ef7ba11aa34b8a96e8a0c31230876a17bfdcf
 size 17671552

training_metadata.json

@@ -1,11 +1,11 @@
 {
-  "trained_at": 1773768758.5562274,
-  "trained_at_readable": "2026-03-17 17:32:38",
-  "samples_this_session": 1241,
-  "new_rows_this_session": 4,
-  "trained_rows_total": 164788,
-  "total_db_rows": 335877,
-  "percentage": 49.06200781833826,
+  "trained_at": 1774597701.2824352,
+  "trained_at_readable": "2026-03-27 07:48:21",
+  "samples_this_session": 1000,
+  "new_rows_this_session": 1000,
+  "trained_rows_total": 164792,
+  "total_db_rows": 337148,
+  "percentage": 48.87823745061516,
   "final_loss": 0,
   "epochs": 3,
   "learning_rate": 5e-05,