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cwe-parent-vulnerability-classification-roberta-base

Text Classification
Transformers
PyTorch
Safetensors
roberta
Generated from Trainer
Model card Files
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End of training

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Files changed (4) hide show
  1. README.md +28 -26
  2. emissions.csv +1 -1
  3. metrics.json +6 -6
  4. model.safetensors +1 -1
README.md CHANGED
@@ -4,6 +4,8 @@ license: mit
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  base_model: roberta-base
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  tags:
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  - generated_from_trainer
 
 
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  model-index:
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  - name: cwe-parent-vulnerability-classification-roberta-base
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  results: []
@@ -16,9 +18,9 @@ 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: 0.9139
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- - F1 Macro: 0.0
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- - Exact Match: 0.0
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  ## Model description
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@@ -47,33 +49,33 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | F1 Macro | Exact Match |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|
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- | 1.1458 | 1.0 | 25 | 1.0204 | 0.0 | 0.0 |
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- | 1.4553 | 2.0 | 50 | 0.9139 | 0.0 | 0.0 |
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- | 1.0412 | 3.0 | 75 | 0.9696 | 0.0 | 0.0 |
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- | 1.7656 | 4.0 | 100 | 1.0281 | 0.0 | 0.0 |
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- | 1.3778 | 5.0 | 125 | 1.0019 | 0.0 | 0.0 |
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- | 1.7337 | 6.0 | 150 | 0.9519 | 0.0 | 0.0 |
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- | 0.9857 | 7.0 | 175 | 0.9220 | 0.0 | 0.0 |
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- | 1.3225 | 8.0 | 200 | 1.0009 | 0.0 | 0.0 |
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- | 0.917 | 9.0 | 225 | 0.9627 | 0.0 | 0.0 |
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- | 1.0001 | 10.0 | 250 | 0.9457 | 0.0 | 0.0 |
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- | 1.1714 | 11.0 | 275 | 0.9520 | 0.0 | 0.0 |
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- | 0.6841 | 12.0 | 300 | 0.9900 | 0.0 | 0.0 |
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- | 1.0138 | 13.0 | 325 | 0.9969 | 0.0 | 0.0 |
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- | 0.9479 | 14.0 | 350 | 0.9998 | 0.0 | 0.0 |
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- | 0.6735 | 15.0 | 375 | 0.9824 | 0.0 | 0.0 |
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- | 0.7927 | 16.0 | 400 | 0.9319 | 0.0 | 0.0 |
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- | 0.7996 | 17.0 | 425 | 0.9437 | 0.0 | 0.0 |
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- | 0.7804 | 18.0 | 450 | 0.9582 | 0.0 | 0.0 |
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- | 0.7048 | 19.0 | 475 | 0.9473 | 0.0 | 0.0 |
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- | 0.5819 | 20.0 | 500 | 0.9483 | 0.0 | 0.0 |
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  ### Framework versions
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- - Transformers 4.55.0
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  - Pytorch 2.7.1+cu126
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  - Datasets 4.0.0
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  - Tokenizers 0.21.2
 
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  base_model: roberta-base
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  tags:
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  - generated_from_trainer
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+ metrics:
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+ - accuracy
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  model-index:
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  - name: cwe-parent-vulnerability-classification-roberta-base
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  results: []
 
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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: 0.6890
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+ - Accuracy: 0.8427
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+ - F1 Macro: 0.3821
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
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+ | 2.8193 | 1.0 | 25 | 2.1550 | 0.4270 | 0.0460 |
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+ | 1.9743 | 2.0 | 50 | 1.9856 | 0.4270 | 0.0460 |
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+ | 1.7803 | 3.0 | 75 | 1.9237 | 0.4270 | 0.0460 |
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+ | 1.5493 | 4.0 | 100 | 1.4930 | 0.6292 | 0.1120 |
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+ | 1.2607 | 5.0 | 125 | 1.3301 | 0.6742 | 0.1229 |
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+ | 1.1316 | 6.0 | 150 | 1.2706 | 0.6742 | 0.1229 |
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+ | 1.0911 | 7.0 | 175 | 1.1787 | 0.6742 | 0.1229 |
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+ | 0.9869 | 8.0 | 200 | 1.0819 | 0.7416 | 0.2359 |
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+ | 0.8985 | 9.0 | 225 | 1.0360 | 0.7640 | 0.2587 |
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+ | 0.7404 | 10.0 | 250 | 0.9223 | 0.7753 | 0.2498 |
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+ | 0.8315 | 11.0 | 275 | 0.8992 | 0.7753 | 0.2441 |
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+ | 0.6514 | 12.0 | 300 | 0.8443 | 0.7753 | 0.2395 |
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+ | 0.6427 | 13.0 | 325 | 0.8207 | 0.7753 | 0.2395 |
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+ | 0.5719 | 14.0 | 350 | 0.7653 | 0.8090 | 0.2887 |
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+ | 0.5153 | 15.0 | 375 | 0.7396 | 0.8202 | 0.3028 |
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+ | 0.4863 | 16.0 | 400 | 0.7580 | 0.8202 | 0.3376 |
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+ | 0.4833 | 17.0 | 425 | 0.7177 | 0.8315 | 0.3806 |
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+ | 0.4948 | 18.0 | 450 | 0.6983 | 0.8427 | 0.3821 |
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+ | 0.4546 | 19.0 | 475 | 0.6890 | 0.8427 | 0.3821 |
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+ | 0.4445 | 20.0 | 500 | 0.6911 | 0.8427 | 0.3821 |
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  ### Framework versions
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+ - Transformers 4.55.4
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  - Pytorch 2.7.1+cu126
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  - Datasets 4.0.0
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  - Tokenizers 0.21.2
emissions.csv CHANGED
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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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- 2025-08-28T15:26:15,codecarbon,06fc693e-38ce-4d5d-a96c-77e37117eab8,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,163.80096963886172,0.002178447438859299,1.3299356186121522e-05,42.5,334.8005306981818,94.34468507766725,0.0019328194311220108,0.014472036299842728,0.004290425981121169,0.020695281712085907,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
 
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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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+ 2025-08-28T16:05:20,codecarbon,e2a8bcaf-0f58-4bb5-a248-bf70c0976bdd,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,182.2731417969335,0.003007971348785084,1.6502548423377697e-05,42.5,225.04609279119165,94.34468507766725,0.0021501255845857996,0.021653612322872107,0.004772032769656413,0.028575770677114313,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
@@ -1,9 +1,9 @@
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  {
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- "eval_loss": 0.913872480392456,
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- "eval_f1_macro": 0.0,
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- "eval_exact_match": 0.0,
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- "eval_runtime": 0.2852,
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- "eval_samples_per_second": 312.098,
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- "eval_steps_per_second": 10.52,
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  "epoch": 20.0
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  }
 
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  {
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+ "eval_loss": 0.6889647245407104,
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+ "eval_accuracy": 0.8426966292134831,
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+ "eval_f1_macro": 0.3820724249295678,
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+ "eval_runtime": 0.3068,
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+ "eval_samples_per_second": 290.118,
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+ "eval_steps_per_second": 9.779,
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  "epoch": 20.0
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  }
model.safetensors CHANGED
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