End of training

README.md

@@ -9,8 +9,6 @@ metrics:
 model-index:
 - name: vulnerability-severity-classification-roberta-base
   results: []
-datasets:
-- CIRCL/vulnerability-scores
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -18,15 +16,14 @@ should probably proofread and complete it, then remove this comment. -->
 
 # vulnerability-severity-classification-roberta-base
 
-This model is a fine-tuned version of [RoBERTa-base](https://huggingface.co/FacebookAI/roberta-base) on the dataset [CIRCL/vulnerability-scores](https://huggingface.co/datasets/CIRCL/vulnerability-scores).
-
+This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.6501
-- Accuracy: 0.7607
+- Loss: 0.5372
+- Accuracy: 0.8138
 
 ## Model description
 
-It is a classification model and is aimed to assist in classifying vulnerabilities by severity based on their descriptions.
+More information needed
 
 ## Intended uses & limitations
 
@@ -51,13 +48,13 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
-|:-------------:|:-----:|:-----:|:---------------:|:--------:|
-| 0.5993        | 1.0   | 14930 | 0.6907          | 0.7245   |
-| 0.5952        | 2.0   | 29860 | 0.6572          | 0.7416   |
-| 0.6602        | 3.0   | 44790 | 0.6146          | 0.7513   |
-| 0.4305        | 4.0   | 59720 | 0.6159          | 0.7615   |
-| 0.3855        | 5.0   | 74650 | 0.6501          | 0.7607   |
+| Training Loss | Epoch | Step   | Validation Loss | Accuracy |
+|:-------------:|:-----:|:------:|:---------------:|:--------:|
+| 0.7239        | 1.0   | 24058  | 0.6421          | 0.7359   |
+| 0.6718        | 2.0   | 48116  | 0.5911          | 0.7598   |
+| 0.5085        | 3.0   | 72174  | 0.5567          | 0.7878   |
+| 0.4282        | 4.0   | 96232  | 0.5377          | 0.8059   |
+| 0.3508        | 5.0   | 120290 | 0.5372          | 0.8138   |
 
 
 ### Framework versions
@@ -65,4 +62,4 @@ The following hyperparameters were used during training:
 - Transformers 4.49.0
 - Pytorch 2.6.0+cu124
 - Datasets 3.3.2
-- Tokenizers 0.21.0
+- Tokenizers 0.21.0

emissions.csv

@@ -1,2 +1,2 @@
 timestamp,project_name,run_id,experiment_id,duration,emissions,emissions_rate,cpu_power,gpu_power,ram_power,cpu_energy,gpu_energy,ram_energy,energy_consumed,country_name,country_iso_code,region,cloud_provider,cloud_region,os,python_version,codecarbon_version,cpu_count,cpu_model,gpu_count,gpu_model,longitude,latitude,ram_total_size,tracking_mode,on_cloud,pue
-2025-02-27T10:50:20,codecarbon,cd8cf35a-bafe-44d1-933e-6b563a348d0c,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,12287.956344367936,0.21961461757741388,1.7872346826661057e-05,42.5,183.40103182049944,94.34470081329346,0.14497745433383238,1.6195452042462648,0.32181933791832995,2.0863419964984264,Luxembourg,LUX,luxembourg,,,Linux-6.8.0-48-generic-x86_64-with-glibc2.39,3.12.3,2.8.3,64,AMD EPYC 9124 16-Core Processor,2,2 x NVIDIA L40S,6.1294,49.6113,251.58586883544922,machine,N,1.0
+2025-03-07T18:34:32,codecarbon,0d870122-7bf3-4a74-9532-05a1c879af32,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,21096.269472956657,0.369204716185761,1.7500948054301502e-05,42.5,181.08759584722017,94.34470081329346,0.24886044327972778,2.706183070500259,0.5524065511598465,3.507450064939827,Luxembourg,LUX,luxembourg,,,Linux-6.8.0-48-generic-x86_64-with-glibc2.39,3.12.3,2.8.3,64,AMD EPYC 9124 16-Core Processor,2,2 x NVIDIA L40S,6.1294,49.6113,251.58586883544922,machine,N,1.0