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cwe-parent-vulnerability-classification-roberta-base

Text Classification
Transformers
PyTorch
Safetensors
roberta
Generated from Trainer
classification
nlp
vulnerability
CWE
text-embeddings-inference
Model card Files
xet
Community
elselse commited on
Commit
3884963
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verified ·
1 Parent(s): 99d6043

End of training

Browse files
Files changed (4) hide show
  1. README.md +6 -6
  2. emissions.csv +1 -1
  3. metrics.json +4 -4
  4. pytorch_model.bin +1 -1
README.md CHANGED
@@ -16,7 +16,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0499
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  - F1 Macro: 0.0
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  - Exact Match: 1.0
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@@ -49,11 +49,11 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | F1 Macro | Exact Match |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|
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- | 0.3266 | 1.0 | 25 | 0.1003 | 0.0 | 1.0 |
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- | 0.1076 | 2.0 | 50 | 0.0669 | 0.0 | 1.0 |
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- | 0.0777 | 3.0 | 75 | 0.0563 | 0.0 | 1.0 |
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- | 0.0609 | 4.0 | 100 | 0.0515 | 0.0 | 1.0 |
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- | 0.0579 | 5.0 | 125 | 0.0499 | 0.0 | 1.0 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0502
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  - F1 Macro: 0.0
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  - Exact Match: 1.0
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  | Training Loss | Epoch | Step | Validation Loss | F1 Macro | Exact Match |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|
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+ | 0.3392 | 1.0 | 25 | 0.1059 | 0.0 | 1.0 |
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+ | 0.1101 | 2.0 | 50 | 0.0681 | 0.0 | 1.0 |
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+ | 0.0792 | 3.0 | 75 | 0.0568 | 0.0 | 1.0 |
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+ | 0.0616 | 4.0 | 100 | 0.0518 | 0.0 | 1.0 |
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+ | 0.0584 | 5.0 | 125 | 0.0502 | 0.0 | 1.0 |
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  ### Framework versions
emissions.csv CHANGED
@@ -1,2 +1,2 @@
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  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
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+ 2025-08-28T12:57:53,codecarbon,223caa76-c5c3-4dff-8e93-cb756d423b49,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,39.7907460401766,0.0005288261800781823,1.3290180072126018e-05,42.5,287.0547175752856,94.34468507766725,0.0004695883299613747,0.003511875865065406,0.0010423920515003216,0.005023856246527102,Luxembourg,LUX,luxembourg,,,Linux-6.8.0-71-generic-x86_64-with-glibc2.39,3.12.3,2.8.4,64,AMD EPYC 9124 16-Core Processor,2,2 x NVIDIA L40S,6.1294,49.6113,251.5858268737793,machine,N,1.0
metrics.json CHANGED
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  {
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- "eval_loss": 0.04985176399350166,
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  "eval_f1_macro": 0.0,
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  "eval_exact_match": 1.0,
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- "eval_runtime": 0.2657,
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- "eval_samples_per_second": 335.027,
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- "eval_steps_per_second": 11.293,
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  "epoch": 5.0
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  }
 
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  {
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+ "eval_loss": 0.05024593695998192,
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  "eval_f1_macro": 0.0,
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  "eval_exact_match": 1.0,
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+ "eval_runtime": 0.2641,
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+ "eval_samples_per_second": 337.056,
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+ "eval_steps_per_second": 11.361,
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  "epoch": 5.0
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  }
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