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cwe-parent-vulnerability-classification-roberta-base

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roberta
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classification
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vulnerability
CWE
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CIRCL/cwe-parent-vulnerability-classification-roberta-base

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Files changed (5) hide show
  1. README.md +43 -43
  2. config.json +52 -52
  3. emissions.csv +1 -1
  4. metrics.json +6 -6
  5. model.safetensors +1 -1
README.md CHANGED
@@ -18,9 +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: 1.2702
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- - Accuracy: 0.8391
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- - F1 Macro: 0.5749
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  ## Model description
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@@ -51,46 +51,46 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
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- | 3.2401 | 1.0 | 25 | 3.1530 | 0.0230 | 0.0174 |
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- | 3.152 | 2.0 | 50 | 2.9711 | 0.1609 | 0.0578 |
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- | 3.0578 | 3.0 | 75 | 2.9801 | 0.2874 | 0.0558 |
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- | 3.0517 | 4.0 | 100 | 2.9785 | 0.2874 | 0.0563 |
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- | 2.9601 | 5.0 | 125 | 2.9911 | 0.0345 | 0.0119 |
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- | 3.05 | 6.0 | 150 | 3.0056 | 0.1264 | 0.0535 |
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- | 2.9557 | 7.0 | 175 | 2.9701 | 0.2299 | 0.1007 |
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- | 2.848 | 8.0 | 200 | 2.9056 | 0.5402 | 0.2504 |
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- | 2.7726 | 9.0 | 225 | 2.8495 | 0.3678 | 0.2690 |
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- | 2.7038 | 10.0 | 250 | 2.8059 | 0.5517 | 0.3253 |
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- | 2.5916 | 11.0 | 275 | 2.6539 | 0.6092 | 0.3668 |
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- | 2.3383 | 12.0 | 300 | 2.6676 | 0.5862 | 0.3023 |
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- | 2.2088 | 13.0 | 325 | 2.4652 | 0.6322 | 0.3471 |
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- | 2.0892 | 14.0 | 350 | 2.3637 | 0.6552 | 0.3423 |
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- | 1.9416 | 15.0 | 375 | 2.2169 | 0.6437 | 0.3671 |
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- | 1.7143 | 16.0 | 400 | 2.1235 | 0.6782 | 0.3641 |
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- | 1.6272 | 17.0 | 425 | 2.0935 | 0.6897 | 0.3928 |
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- | 1.5298 | 18.0 | 450 | 1.9714 | 0.6782 | 0.3864 |
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- | 1.4403 | 19.0 | 475 | 1.8721 | 0.7011 | 0.4369 |
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- | 1.2856 | 20.0 | 500 | 1.9068 | 0.6782 | 0.3349 |
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- | 1.2127 | 21.0 | 525 | 1.7450 | 0.7241 | 0.4121 |
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- | 1.1393 | 22.0 | 550 | 1.7261 | 0.7471 | 0.4584 |
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- | 1.0283 | 23.0 | 575 | 1.6108 | 0.7241 | 0.4489 |
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- | 0.9733 | 24.0 | 600 | 1.6081 | 0.7586 | 0.4284 |
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- | 0.9161 | 25.0 | 625 | 1.5531 | 0.7701 | 0.4667 |
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- | 0.8368 | 26.0 | 650 | 1.5585 | 0.7586 | 0.4239 |
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- | 0.8555 | 27.0 | 675 | 1.4921 | 0.7701 | 0.4354 |
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- | 0.7642 | 28.0 | 700 | 1.4521 | 0.8046 | 0.4944 |
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- | 0.6875 | 29.0 | 725 | 1.3804 | 0.8276 | 0.5610 |
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- | 0.7027 | 30.0 | 750 | 1.3856 | 0.8046 | 0.5304 |
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- | 0.6434 | 31.0 | 775 | 1.3554 | 0.8391 | 0.5749 |
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- | 0.6695 | 32.0 | 800 | 1.3494 | 0.8276 | 0.5198 |
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- | 0.6012 | 33.0 | 825 | 1.3325 | 0.8391 | 0.5749 |
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- | 0.6109 | 34.0 | 850 | 1.3240 | 0.8391 | 0.5749 |
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- | 0.6068 | 35.0 | 875 | 1.2947 | 0.8391 | 0.5749 |
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- | 0.5564 | 36.0 | 900 | 1.2942 | 0.8391 | 0.5749 |
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- | 0.5492 | 37.0 | 925 | 1.2761 | 0.8391 | 0.5749 |
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- | 0.5494 | 38.0 | 950 | 1.2749 | 0.8391 | 0.5749 |
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- | 0.5339 | 39.0 | 975 | 1.2702 | 0.8391 | 0.5749 |
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- | 0.4882 | 40.0 | 1000 | 1.2728 | 0.8391 | 0.5749 |
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  ### Framework versions
 
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19
  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
20
  It achieves the following results on the evaluation set:
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+ - Loss: 1.5419
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+ - Accuracy: 0.8068
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+ - F1 Macro: 0.3782
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
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+ | 3.2546 | 1.0 | 25 | 3.1526 | 0.0682 | 0.0142 |
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+ | 3.1769 | 2.0 | 50 | 2.9132 | 0.0795 | 0.0185 |
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+ | 3.1105 | 3.0 | 75 | 2.8945 | 0.5 | 0.0752 |
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+ | 3.0319 | 4.0 | 100 | 2.7792 | 0.0114 | 0.0027 |
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+ | 3.0703 | 5.0 | 125 | 2.8108 | 0.0455 | 0.0130 |
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+ | 2.9543 | 6.0 | 150 | 2.8282 | 0.0682 | 0.0235 |
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+ | 2.9445 | 7.0 | 175 | 2.7967 | 0.125 | 0.0743 |
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+ | 2.8502 | 8.0 | 200 | 2.7834 | 0.1818 | 0.0913 |
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+ | 2.7131 | 9.0 | 225 | 2.6824 | 0.4205 | 0.1350 |
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+ | 2.6082 | 10.0 | 250 | 2.6462 | 0.5227 | 0.1447 |
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+ | 2.6341 | 11.0 | 275 | 2.6106 | 0.4545 | 0.1765 |
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+ | 2.3253 | 12.0 | 300 | 2.5876 | 0.5455 | 0.1611 |
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+ | 2.2511 | 13.0 | 325 | 2.6247 | 0.4773 | 0.1580 |
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+ | 2.2056 | 14.0 | 350 | 2.5191 | 0.6136 | 0.1808 |
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+ | 2.0981 | 15.0 | 375 | 2.3928 | 0.625 | 0.2183 |
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+ | 1.8694 | 16.0 | 400 | 2.3963 | 0.6818 | 0.2353 |
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+ | 1.7945 | 17.0 | 425 | 2.2359 | 0.6818 | 0.2290 |
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+ | 1.7152 | 18.0 | 450 | 2.2076 | 0.7159 | 0.2540 |
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+ | 1.6186 | 19.0 | 475 | 2.1035 | 0.7045 | 0.2388 |
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+ | 1.4477 | 20.0 | 500 | 2.0271 | 0.6932 | 0.2464 |
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+ | 1.4064 | 21.0 | 525 | 1.9818 | 0.7159 | 0.2478 |
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+ | 1.2211 | 22.0 | 550 | 1.8832 | 0.7159 | 0.2517 |
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+ | 1.2831 | 23.0 | 575 | 1.8892 | 0.7273 | 0.2712 |
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+ | 1.1426 | 24.0 | 600 | 1.7992 | 0.7273 | 0.2644 |
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+ | 1.054 | 25.0 | 625 | 1.8517 | 0.7386 | 0.2726 |
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+ | 1.0345 | 26.0 | 650 | 1.7283 | 0.7273 | 0.2644 |
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+ | 0.9516 | 27.0 | 675 | 1.7043 | 0.7045 | 0.2630 |
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+ | 0.8861 | 28.0 | 700 | 1.6532 | 0.7386 | 0.2735 |
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+ | 0.8477 | 29.0 | 725 | 1.6508 | 0.7614 | 0.2795 |
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+ | 0.8804 | 30.0 | 750 | 1.6057 | 0.7386 | 0.2612 |
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+ | 0.7854 | 31.0 | 775 | 1.5771 | 0.75 | 0.2902 |
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+ | 0.7311 | 32.0 | 800 | 1.5838 | 0.7614 | 0.2662 |
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+ | 0.7362 | 33.0 | 825 | 1.5649 | 0.7841 | 0.3463 |
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+ | 0.7031 | 34.0 | 850 | 1.5553 | 0.7841 | 0.3361 |
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+ | 0.7589 | 35.0 | 875 | 1.5546 | 0.7955 | 0.3545 |
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+ | 0.6877 | 36.0 | 900 | 1.5557 | 0.7841 | 0.3361 |
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+ | 0.6497 | 37.0 | 925 | 1.5419 | 0.8068 | 0.3782 |
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+ | 0.6565 | 38.0 | 950 | 1.5496 | 0.7955 | 0.3663 |
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+ | 0.6333 | 39.0 | 975 | 1.5531 | 0.7955 | 0.3458 |
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+ | 0.653 | 40.0 | 1000 | 1.5501 | 0.7955 | 0.3458 |
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  ### Framework versions
config.json CHANGED
@@ -10,62 +10,62 @@
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  "hidden_dropout_prob": 0.1,
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  "hidden_size": 768,
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  "id2label": {
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- "0": "LABEL_0",
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  },
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  "layer_norm_eps": 1e-05,
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emissions.csv CHANGED
@@ -1,2 +1,2 @@
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1
  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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metrics.json CHANGED
@@ -1,9 +1,9 @@
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  {
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- "eval_accuracy": 0.8390804597701149,
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- "eval_samples_per_second": 288.082,
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- "eval_steps_per_second": 9.934,
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  "epoch": 40.0
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  }
 
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  "epoch": 40.0
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  }
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