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cwe-parent-vulnerability-classification-roberta-base

Text Classification
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PyTorch
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
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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: 1.9131
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- - Accuracy: 0.7701
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- - F1 Macro: 0.4179
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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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- | 3.2726 | 1.0 | 25 | 3.1430 | 0.0230 | 0.0041 |
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- | 3.214 | 2.0 | 50 | 2.9861 | 0.0230 | 0.0041 |
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- | 3.1457 | 3.0 | 75 | 2.9949 | 0.0115 | 0.0019 |
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- | 3.0447 | 4.0 | 100 | 3.0090 | 0.1149 | 0.0265 |
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- | 3.0588 | 5.0 | 125 | 2.9652 | 0.0230 | 0.0039 |
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- | 2.9336 | 6.0 | 150 | 2.9089 | 0.4828 | 0.1081 |
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- | 2.9729 | 7.0 | 175 | 2.9005 | 0.1264 | 0.0606 |
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- | 2.812 | 8.0 | 200 | 2.9174 | 0.3563 | 0.1788 |
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- | 2.6587 | 9.0 | 225 | 2.8268 | 0.3563 | 0.1414 |
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- | 2.5464 | 10.0 | 250 | 2.8296 | 0.3103 | 0.1339 |
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- | 2.4379 | 11.0 | 275 | 2.7762 | 0.2989 | 0.1554 |
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- | 2.2741 | 12.0 | 300 | 2.7595 | 0.4598 | 0.1745 |
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- | 2.1793 | 13.0 | 325 | 2.7483 | 0.4943 | 0.1826 |
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- | 2.0085 | 14.0 | 350 | 2.6646 | 0.4713 | 0.2136 |
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- | 1.9313 | 15.0 | 375 | 2.6414 | 0.6092 | 0.2916 |
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- | 1.7534 | 16.0 | 400 | 2.5186 | 0.6552 | 0.3345 |
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- | 1.6187 | 17.0 | 425 | 2.3736 | 0.6552 | 0.3381 |
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- | 1.5568 | 18.0 | 450 | 2.2908 | 0.6667 | 0.3391 |
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- | 1.4627 | 19.0 | 475 | 2.4101 | 0.6437 | 0.3356 |
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- | 1.2964 | 20.0 | 500 | 2.2791 | 0.6782 | 0.3525 |
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- | 1.2236 | 21.0 | 525 | 2.1636 | 0.6667 | 0.3403 |
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- | 1.1237 | 22.0 | 550 | 2.1584 | 0.6897 | 0.3397 |
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- | 1.0589 | 23.0 | 575 | 2.1262 | 0.6782 | 0.3535 |
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- | 0.952 | 24.0 | 600 | 2.1252 | 0.6782 | 0.3504 |
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- | 0.9137 | 25.0 | 625 | 2.0899 | 0.6667 | 0.3656 |
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- | 0.878 | 26.0 | 650 | 1.9915 | 0.7126 | 0.4012 |
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- | 0.8073 | 27.0 | 675 | 1.9856 | 0.7356 | 0.3857 |
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- | 0.7588 | 28.0 | 700 | 1.9613 | 0.7356 | 0.3737 |
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- | 0.7114 | 29.0 | 725 | 1.9789 | 0.7701 | 0.4103 |
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- | 0.6728 | 30.0 | 750 | 1.9131 | 0.7701 | 0.4179 |
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- | 0.6651 | 31.0 | 775 | 2.0236 | 0.7701 | 0.4231 |
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- | 0.5979 | 32.0 | 800 | 2.0366 | 0.7701 | 0.4668 |
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- | 0.5946 | 33.0 | 825 | 2.0026 | 0.7931 | 0.4478 |
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- | 0.5395 | 34.0 | 850 | 2.0010 | 0.8046 | 0.4544 |
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- | 0.5301 | 35.0 | 875 | 1.9332 | 0.8046 | 0.4500 |
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- | 0.5216 | 36.0 | 900 | 1.9965 | 0.8161 | 0.4966 |
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- | 0.497 | 37.0 | 925 | 1.9930 | 0.8161 | 0.4639 |
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- | 0.5149 | 38.0 | 950 | 1.9813 | 0.8161 | 0.4582 |
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- | 0.5022 | 39.0 | 975 | 1.9775 | 0.8046 | 0.4667 |
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- | 0.4892 | 40.0 | 1000 | 1.9643 | 0.8161 | 0.4688 |
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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: 1.2702
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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
 
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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
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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  "max_position_embeddings": 514,
 
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  "hidden_dropout_prob": 0.1,
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emissions.csv CHANGED
@@ -1,2 +1,2 @@
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metrics.json CHANGED
@@ -1,9 +1,9 @@
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  {
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- "eval_accuracy": 0.7701149425287356,
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- "eval_steps_per_second": 11.347,
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  "epoch": 40.0
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  }
 
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  "epoch": 40.0
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