codechrl commited on
Commit
82762fd
·
verified ·
1 Parent(s): 7f9923d

Training update: 161,015/163,680 rows (98.37%) | +5 new @ 2025-11-10 21:10:39

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 **98.29%** 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 (98.29%) 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
 
@@ -75,9 +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**: 163,676
79
- - **Rows processed (cumulative)**: 160,878 (98.29%)
80
- - **Training date**: 2025-11-10 20:41:47
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 **98.37%** 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 (98.37%) 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**: 163,680
79
+ - **Rows processed (cumulative)**: 161,015 (98.37%)
80
+ - **Training date**: 2025-11-10 21:10:39
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:fc53a41b8ffaac73d7a7372b4fc3830d2780051351a803e627bec6fa40272e48
3
  size 17671560
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:687372dcf6a079aba9764ec1fece2f17be1ece16fb5ff5ac250a770b9acc1beb
3
  size 17671560
training_args.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:4f07001d52fd525326de08681b362776df1a6db4c6447e762884a938acafdd42
3
  size 5905
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:02f3298ec4505a57a8ddc88a7d5cfadee800a56984099d3633eea9fca28b8368
3
  size 5905
training_metadata.json CHANGED
@@ -1,11 +1,11 @@
1
  {
2
- "trained_at": 1762807307.1878793,
3
- "trained_at_readable": "2025-11-10 20:41:47",
4
- "samples_this_session": 1001,
5
- "new_rows_this_session": 137,
6
- "trained_rows_total": 160878,
7
- "total_db_rows": 163676,
8
- "percentage": 98.2905251838999,
9
  "final_loss": 0,
10
  "epochs": 3,
11
  "learning_rate": 5e-05,
 
1
  {
2
+ "trained_at": 1762809039.6314473,
3
+ "trained_at_readable": "2025-11-10 21:10:39",
4
+ "samples_this_session": 1703,
5
+ "new_rows_this_session": 5,
6
+ "trained_rows_total": 161015,
7
+ "total_db_rows": 163680,
8
+ "percentage": 98.37182306940372,
9
  "final_loss": 0,
10
  "epochs": 3,
11
  "learning_rate": 5e-05,