Training update: 165,761/348,722 rows (47.53%) | +7 new @ 2026-04-06 03:08:30

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 **49.33%** of planned data.
+- Status: **Early version** — trained on **47.53%** 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 (49.33%) 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 (47.53%) 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**: 335,995
-- **Rows processed (cumulative)**: 165,758 (49.33%)
-- **Training date**: 2026-03-31 17:28:43
+- **Total database rows**: 348,722
+- **Rows processed (cumulative)**: 165,761 (47.53%)
+- **Training date**: 2026-04-06 03:08:30
 
 ### 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": "5.4.0",
+  "transformers_version": "5.5.0",
   "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:b4082ca26b11f86de3062a5435db09de5c919d22990a80c70c3fdeb5459025e0
+oid sha256:12917da4dfc3f5c4ad90d2fe93c0cdd57e1e4c1df7f3d01b8c94b8952db28272
 size 17671552

training_metadata.json

@@ -1,11 +1,11 @@
 {
-  "trained_at": 1774978123.6197236,
-  "trained_at_readable": "2026-03-31 17:28:43",
-  "samples_this_session": 872,
-  "new_rows_this_session": 3,
-  "trained_rows_total": 165758,
-  "total_db_rows": 335995,
-  "percentage": 49.33347222428905,
+  "trained_at": 1775444910.9934316,
+  "trained_at_readable": "2026-04-06 03:08:30",
+  "samples_this_session": 1135,
+  "new_rows_this_session": 7,
+  "trained_rows_total": 165761,
+  "total_db_rows": 348722,
+  "percentage": 47.533852180246726,
   "final_loss": 0,
   "epochs": 3,
   "learning_rate": 5e-05,