codechrl commited on
Commit
db590d2
·
verified ·
1 Parent(s): 8a527d4

Training update: 153,489/241,654 rows (63.52%) | +32 new @ 2025-11-05 10:12:41

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 **63.46%** 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 (63.46%) 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**: 241,650
79
- - **Rows processed (cumulative)**: 153,349 (63.46%)
80
- - **Training date**: 2025-11-05 09:06:06
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 **63.52%** 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 (63.52%) 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**: 241,654
79
+ - **Rows processed (cumulative)**: 153,489 (63.52%)
80
+ - **Training date**: 2025-11-05 10:12:41
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 sha256:30088c3d61b1d32ccf6833222ebb8ec0a140616c5f9045424a0192a96971333b
3
  size 17671560
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ed2747eb84180d09f3581f715ffbdce69c8f9927d1b91b160eb1ccc115c487ed
3
  size 17671560
training_args.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:8ee550335387df9a993f0c3dec9e07093345b5686ef9c4ad0b9bd0af2bbc7c68
3
  size 5905
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:47046ef7cb7c029456c1fd7f5488a7a5ab5a44c08934090eeb0dff9b049db956
3
  size 5905
training_metadata.json CHANGED
@@ -1,11 +1,11 @@
1
  {
2
- "trained_at": 1762333566.4803362,
3
- "trained_at_readable": "2025-11-05 09:06:06",
4
- "samples_this_session": 1633,
5
- "new_rows_this_session": 142,
6
- "trained_rows_total": 153349,
7
- "total_db_rows": 241650,
8
- "percentage": 63.4591351127664,
9
  "final_loss": 0,
10
  "epochs": 3,
11
  "learning_rate": 5e-05,
 
1
  {
2
+ "trained_at": 1762337561.5791628,
3
+ "trained_at_readable": "2025-11-05 10:12:41",
4
+ "samples_this_session": 1401,
5
+ "new_rows_this_session": 32,
6
+ "trained_rows_total": 153489,
7
+ "total_db_rows": 241654,
8
+ "percentage": 63.516018770639015,
9
  "final_loss": 0,
10
  "epochs": 3,
11
  "learning_rate": 5e-05,