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

README.md

@@ -0,0 +1,101 @@
+---
+library_name: transformers
+license: mit
+base_model: roberta-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: cwe-parent-vulnerability-classification-roberta-base-roberta-base
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# cwe-parent-vulnerability-classification-roberta-base-roberta-base
+
+This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.8770
+- Accuracy: 0.3704
+- F1 Macro: 0.2104
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 1e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 40
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
+| 3.2548        | 1.0   | 22   | 3.2008          | 0.0247   | 0.0032   |
+| 3.2101        | 2.0   | 44   | 3.1368          | 0.2469   | 0.0390   |
+| 3.1235        | 3.0   | 66   | 3.1592          | 0.3086   | 0.0470   |
+| 3.1517        | 4.0   | 88   | 3.1942          | 0.0741   | 0.0306   |
+| 3.1203        | 5.0   | 110  | 3.1893          | 0.0741   | 0.0236   |
+| 3.052         | 6.0   | 132  | 3.2068          | 0.1111   | 0.0506   |
+| 2.9901        | 7.0   | 154  | 3.2085          | 0.0864   | 0.0450   |
+| 2.9408        | 8.0   | 176  | 3.1076          | 0.1605   | 0.0837   |
+| 2.9616        | 9.0   | 198  | 3.1395          | 0.2840   | 0.1093   |
+| 2.6981        | 10.0  | 220  | 3.0276          | 0.1235   | 0.0822   |
+| 2.5881        | 11.0  | 242  | 2.9858          | 0.3086   | 0.1426   |
+| 2.4502        | 12.0  | 264  | 3.0535          | 0.2963   | 0.1760   |
+| 2.3384        | 13.0  | 286  | 2.9500          | 0.2840   | 0.1541   |
+| 2.3099        | 14.0  | 308  | 2.9306          | 0.2593   | 0.1812   |
+| 2.1734        | 15.0  | 330  | 2.9583          | 0.3086   | 0.1412   |
+| 2.0758        | 16.0  | 352  | 2.9464          | 0.2840   | 0.1504   |
+| 1.9912        | 17.0  | 374  | 2.9119          | 0.3210   | 0.1949   |
+| 1.8726        | 18.0  | 396  | 2.9168          | 0.3210   | 0.1794   |
+| 1.8145        | 19.0  | 418  | 2.9360          | 0.2963   | 0.1724   |
+| 1.6758        | 20.0  | 440  | 2.9125          | 0.3333   | 0.1914   |
+| 1.5863        | 21.0  | 462  | 2.9420          | 0.3457   | 0.2171   |
+| 1.5365        | 22.0  | 484  | 2.9001          | 0.3580   | 0.2316   |
+| 1.4698        | 23.0  | 506  | 2.8783          | 0.3457   | 0.2107   |
+| 1.4471        | 24.0  | 528  | 2.9298          | 0.3580   | 0.2286   |
+| 1.3445        | 25.0  | 550  | 2.8971          | 0.3580   | 0.2178   |
+| 1.3723        | 26.0  | 572  | 2.8770          | 0.3704   | 0.2104   |
+| 1.1981        | 27.0  | 594  | 2.9112          | 0.3704   | 0.2195   |
+| 1.279         | 28.0  | 616  | 2.9038          | 0.3580   | 0.2278   |
+| 1.1505        | 29.0  | 638  | 2.9192          | 0.3704   | 0.2269   |
+| 1.1089        | 30.0  | 660  | 2.9398          | 0.3704   | 0.2228   |
+| 1.0631        | 31.0  | 682  | 2.9589          | 0.3704   | 0.2292   |
+| 1.0373        | 32.0  | 704  | 2.9136          | 0.3704   | 0.2106   |
+| 0.9814        | 33.0  | 726  | 2.9551          | 0.3457   | 0.2155   |
+| 1.0372        | 34.0  | 748  | 2.9457          | 0.3704   | 0.2094   |
+| 0.9644        | 35.0  | 770  | 2.9645          | 0.3827   | 0.2269   |
+| 1.0171        | 36.0  | 792  | 2.9565          | 0.3704   | 0.2317   |
+| 0.9021        | 37.0  | 814  | 2.9583          | 0.3951   | 0.2400   |
+| 0.9202        | 38.0  | 836  | 2.9742          | 0.4074   | 0.2458   |
+| 0.9314        | 39.0  | 858  | 2.9691          | 0.3951   | 0.2349   |
+| 0.9293        | 40.0  | 880  | 2.9746          | 0.3951   | 0.2349   |
+
+
+### Framework versions
+
+- Transformers 4.56.1
+- Pytorch 2.8.0+cu128
+- Datasets 4.0.0
+- Tokenizers 0.22.0

config.json

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   "layer_norm_eps": 1e-05,
   "max_position_embeddings": 514,

emissions.csv

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+2025-10-15T12:36:16,codecarbon,2e463b2d-fb6f-42cd-9687-32c8f179a8f1,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,354.22733898554,0.005596118459999381,1.5798098690027484e-05,42.5,219.5918093228074,94.34468507766725,0.004177519621494381,0.039712911214735414,0.009272774278571993,0.05316320511480179,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

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+{
+    "eval_loss": 2.877013683319092,
+    "eval_accuracy": 0.37037037037037035,
+    "eval_f1_macro": 0.2103685138772858,
+    "eval_runtime": 0.2673,
+    "eval_samples_per_second": 303.013,
+    "eval_steps_per_second": 11.223,
+    "epoch": 40.0
+}

model.safetensors

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