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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
f2e857c
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1 Parent(s): 9e0aef9

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: 0.0502
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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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- | 0.3392 | 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
 
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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: 0.0437
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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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+ | 0.3234 | 1.0 | 25 | 0.0950 | 0.0 | 1.0 |
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+ | 0.1031 | 2.0 | 50 | 0.0598 | 0.0 | 1.0 |
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+ | 0.0729 | 3.0 | 75 | 0.0493 | 0.0 | 1.0 |
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+ | 0.0557 | 4.0 | 100 | 0.0450 | 0.0 | 1.0 |
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+ | 0.0527 | 5.0 | 125 | 0.0437 | 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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  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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+ 2025-08-28T13:04:19,codecarbon,bcb16cd7-bb6d-410c-b997-8b2ce64b5319,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,42.758858100976795,0.0005566582427749225,1.3018547910244732e-05,42.5,265.0106673145598,94.34468507766725,0.0005045715434743519,0.0036637176531897353,0.0011199720420895331,0.005288261238753621,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": 0.05024593695998192,
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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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  {
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+ "eval_loss": 0.043746404349803925,
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  "eval_f1_macro": 0.0,
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  "eval_exact_match": 1.0,
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+ "eval_runtime": 0.29,
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+ "eval_samples_per_second": 306.863,
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+ "eval_steps_per_second": 10.344,
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  "epoch": 5.0
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  }
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