codechrl commited on
Commit
e3a40de
·
verified ·
1 Parent(s): 9b83f06

Training update: 152,918/241,599 rows (63.29%) | +39 new @ 2025-11-05 00:36:14

Browse files
Files changed (4) hide show
  1. README.md +5 -5
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
  4. training_metadata.json +7 -7
README.md CHANGED
@@ -25,7 +25,7 @@ pipeline_tag: fill-mask
25
  - Model type: fine-tuned lightweight BERT variant
26
  - Languages: English & Indonesia
27
  - Finetuned from: `boltuix/bert-micro`
28
- - Status: **Early version** — trained on **63.30%** of planned data.
29
 
30
  **Model sources**
31
  - 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
51
  - Early classification of SIEM alert & events.
52
 
53
  ## 3. Bias, Risks, and Limitations
54
- Because the model is based on a small subset (63.30%) of planned data, performance is preliminary and may degrade on unseen or specialized domains (industrial control, IoT logs, foreign language).
55
  - 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.
56
  - **Should not be used as sole authority for incident decisions; only as an aid to human analysts.**
57
 
@@ -75,9 +75,9 @@ Since cybersecurity data often contains lengthy alert descriptions and execution
75
  - **LR scheduler**: Linear with warmup
76
 
77
  ### Training Data
78
- - **Total database rows**: 241,587
79
- - **Rows processed (cumulative)**: 152,913 (63.30%)
80
- - **Training date**: 2025-11-04 16:06:09
81
 
82
  ### Post-Training Metrics
83
  - **Final training loss**:
 
25
  - Model type: fine-tuned lightweight BERT variant
26
  - Languages: English & Indonesia
27
  - Finetuned from: `boltuix/bert-micro`
28
+ - Status: **Early version** — trained on **63.29%** of planned data.
29
 
30
  **Model sources**
31
  - Base model: [boltuix/bert-micro](https://huggingface.co/boltuix/bert-micro)
 
51
  - Early classification of SIEM alert & events.
52
 
53
  ## 3. Bias, Risks, and Limitations
54
+ Because the model is based on a small subset (63.29%) of planned data, performance is preliminary and may degrade on unseen or specialized domains (industrial control, IoT logs, foreign language).
55
  - 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.
56
  - **Should not be used as sole authority for incident decisions; only as an aid to human analysts.**
57
 
 
75
  - **LR scheduler**: Linear with warmup
76
 
77
  ### Training Data
78
+ - **Total database rows**: 241,599
79
+ - **Rows processed (cumulative)**: 152,918 (63.29%)
80
+ - **Training date**: 2025-11-05 00:36:14
81
 
82
  ### Post-Training Metrics
83
  - **Final training loss**:
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:18f862d2f06075a6aaea7830b434058581d6e5441647c30ede91bedfc2ea0bc7
3
  size 17671560
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9fa7d88bb1cdb8de5e5a0e311567253bdbec9cc86395cfe052d77188bcdd6522
3
  size 17671560
training_args.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:49259279f0ab097db4c5ee7a02b88887b05a6c68eaa1459477c335ecdbe74fdc
3
  size 5905
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e96f7a72370df14348f903746c44d70182d5356b6d5be9711318d6b4401b8ad1
3
  size 5905
training_metadata.json CHANGED
@@ -1,11 +1,11 @@
1
  {
2
- "trained_at": 1762272369.8742146,
3
- "trained_at_readable": "2025-11-04 16:06:09",
4
- "samples_this_session": 1294,
5
- "new_rows_this_session": 5,
6
- "trained_rows_total": 152913,
7
- "total_db_rows": 241587,
8
- "percentage": 63.295210421090545,
9
  "final_loss": 0,
10
  "epochs": 3,
11
  "learning_rate": 5e-05,
 
1
  {
2
+ "trained_at": 1762302974.7156608,
3
+ "trained_at_readable": "2025-11-05 00:36:14",
4
+ "samples_this_session": 1504,
5
+ "new_rows_this_session": 39,
6
+ "trained_rows_total": 152918,
7
+ "total_db_rows": 241599,
8
+ "percentage": 63.294136151225786,
9
  "final_loss": 0,
10
  "epochs": 3,
11
  "learning_rate": 5e-05,