Training update: 83,138/239,461 rows (34.72%) | +1899 new @ 2025-10-25 21:27:23

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 **34.30%** of planned data.
+- Status: **Early version** — trained on **34.72%** 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 (34.30%) 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 (34.72%) 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**: 239,449
-- **Rows processed (cumulative)**: 82,142 (34.30%)
-- **Training date**: 2025-10-25 20:40:15
+- **Total database rows**: 239,461
+- **Rows processed (cumulative)**: 83,138 (34.72%)
+- **Training date**: 2025-10-25 21:27:23
 
 ### Post-Training Metrics
 - **Final training loss**: 

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training_metadata.json

@@ -1,11 +1,11 @@
 {
-  "trained_at": 1761424815.4469857,
-  "trained_at_readable": "2025-10-25 20:40:15",
-  "samples_this_session": 5004,
-  "new_rows_this_session": 996,
-  "trained_rows_total": 82142,
-  "total_db_rows": 239449,
-  "percentage": 34.30459095673818,
+  "trained_at": 1761427643.019707,
+  "trained_at_readable": "2025-10-25 21:27:23",
+  "samples_this_session": 5001,
+  "new_rows_this_session": 1899,
+  "trained_rows_total": 83138,
+  "total_db_rows": 239461,
+  "percentage": 34.71880598510822,
   "final_loss": 0,
   "epochs": 3,
   "learning_rate": 5e-05,