codechrl commited on
Commit
1363b56
·
verified ·
1 Parent(s): d112d51

Training update: 136,215/240,622 rows (56.61%) | +16 new @ 2025-10-30 01:17:38

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 **56.56%** 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 (56.56%) 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**: 240,616
79
- - **Rows processed (cumulative)**: 136,082 (56.56%)
80
- - **Training date**: 2025-10-30 00:27:40
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 **56.61%** 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 (56.61%) 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**: 240,622
79
+ - **Rows processed (cumulative)**: 136,215 (56.61%)
80
+ - **Training date**: 2025-10-30 01:17:38
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 sha256:86759d836afc553992619bd8543d7a3da57f0118922e72d9cb7b836fee340945
3
  size 17671560
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:94f420af7ee05fa039b577cfd8a15852134c698ee268366c2f14fc9c850a5e75
3
  size 17671560
training_args.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:182c64a0757579059f32ac513ba3cc832bc33e1cf0c2e3fe529ba5806693dcd3
3
  size 5905
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7f09ecb28d4cd45610908a5f4f4e57c951cc055cf60b094ad640b784fdaae8cf
3
  size 5905
training_metadata.json CHANGED
@@ -1,11 +1,11 @@
1
  {
2
- "trained_at": 1761784060.9851012,
3
- "trained_at_readable": "2025-10-30 00:27:40",
4
- "samples_this_session": 1995,
5
- "new_rows_this_session": 133,
6
- "trained_rows_total": 136082,
7
- "total_db_rows": 240616,
8
- "percentage": 56.55567377065531,
9
  "final_loss": 0,
10
  "epochs": 3,
11
  "learning_rate": 5e-05,
 
1
  {
2
+ "trained_at": 1761787058.2839193,
3
+ "trained_at_readable": "2025-10-30 01:17:38",
4
+ "samples_this_session": 2089,
5
+ "new_rows_this_session": 16,
6
+ "trained_rows_total": 136215,
7
+ "total_db_rows": 240622,
8
+ "percentage": 56.609536950071075,
9
  "final_loss": 0,
10
  "epochs": 3,
11
  "learning_rate": 5e-05,