End of training

README.md

@@ -9,8 +9,6 @@ metrics:
 model-index:
 - name: vulnerability-severity-classification-chinese-macbert-base
   results: []
-datasets:
-- CIRCL/Vulnerability-CNVD
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -18,13 +16,22 @@ should probably proofread and complete it, then remove this comment. -->
 
 # vulnerability-severity-classification-chinese-macbert-base
 
-This model is a fine-tuned version of [hfl/chinese-macbert-base](https://huggingface.co/hfl/chinese-macbert-base) on the dataset [CIRCL/Vulnerability-CNVD](https://huggingface.co/datasets/CIRCL/Vulnerability-CNVD).
+This model is a fine-tuned version of [hfl/chinese-macbert-base](https://huggingface.co/hfl/chinese-macbert-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5994
+- Accuracy: 0.7900
 
-You can read [this page](https://www.vulnerability-lookup.org/user-manual/ai/) for more information.
+## Model description
 
-It achieves the following results on the evaluation set:
-- Loss: 0.6177
-- Accuracy: 0.7801
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
 
 ## Training procedure
 
@@ -43,11 +50,11 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step  | Validation Loss | Accuracy |
 |:-------------:|:-----:|:-----:|:---------------:|:--------:|
-| 0.6391        | 1.0   | 3388  | 0.5728          | 0.7547   |
-| 0.6062        | 2.0   | 6776  | 0.5545          | 0.7704   |
-| 0.5545        | 3.0   | 10164 | 0.5357          | 0.7819   |
-| 0.3597        | 4.0   | 13552 | 0.5709          | 0.7820   |
-| 0.327         | 5.0   | 16940 | 0.6177          | 0.7801   |
+| 0.65          | 1.0   | 3388  | 0.5772          | 0.7561   |
+| 0.582         | 2.0   | 6776  | 0.5656          | 0.7620   |
+| 0.5284        | 3.0   | 10164 | 0.5274          | 0.7881   |
+| 0.3406        | 4.0   | 13552 | 0.5555          | 0.7869   |
+| 0.3224        | 5.0   | 16940 | 0.5994          | 0.7900   |
 
 
 ### Framework versions
@@ -55,4 +62,4 @@ The following hyperparameters were used during training:
 - Transformers 4.51.3
 - Pytorch 2.7.1+cu126
 - Datasets 3.6.0
-- Tokenizers 0.21.1
+- Tokenizers 0.21.1

emissions.csv

@@ -1,2 +1,2 @@
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-2025-06-30T11:52:22,codecarbon,0e289da9-d45c-4fea-a0b8-1775cda9cf46,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,5728.429068184923,0.10835683297338093,1.8915627946793143e-05,42.5,454.91915669717054,94.34468364715576,0.06758234387103264,0.8117899213758335,0.15001919208743872,1.0293914573343048,Luxembourg,LUX,luxembourg,,,Linux-6.8.0-60-generic-x86_64-with-glibc2.39,3.12.3,2.8.4,64,AMD EPYC 9124 16-Core Processor,2,2 x NVIDIA L40S,6.1294,49.6113,251.58582305908203,machine,N,1.0
+2025-07-03T08:48:19,codecarbon,6b6ee9a5-bd5e-4b19-a09c-85d1371fcaf6,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,5843.158349264413,0.11051319342331094,1.8913263481422386e-05,42.5,416.29527770671575,94.34468364715576,0.06893670656428569,0.8279147587201692,0.15302544705236684,1.0498769123368223,Luxembourg,LUX,luxembourg,,,Linux-6.8.0-60-generic-x86_64-with-glibc2.39,3.12.3,2.8.4,64,AMD EPYC 9124 16-Core Processor,2,2 x NVIDIA L40S,6.1294,49.6113,251.58582305908203,machine,N,1.0

model.safetensors

@@ -1,3 +1,3 @@
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+oid sha256:15e82635a3ad2169c9f0892412f05e344bbfe290f4375fb58e5c85549144e722
 size 409103316