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

Text Classification
Transformers
PyTorch
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
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End of training

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  1. README.md +60 -59
  2. config.json +606 -606
  3. emissions.csv +1 -1
  4. metrics.json +6 -6
  5. model.safetensors +1 -1
  6. training_args.bin +1 -1
README.md CHANGED
@@ -1,37 +1,38 @@
1
  ---
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  library_name: transformers
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- license: cc-by-4.0
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  base_model: roberta-base
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  tags:
6
  - generated_from_trainer
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- - text-classification
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- - classification
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- - nlp
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- - vulnerability
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- - CWE
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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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- datasets:
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- - CIRCL/vulnerability-cwe-patch
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  ---
20
 
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
23
 
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- # CWE guessing
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26
- This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the
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- [CIRCL/vulnerability-cwe-patch](https://huggingface.co/datasets/CIRCL/vulnerability-cwe-patch) dataset.
 
 
 
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- The goal is to predict CWE categories from Git commit messages and vulnerability descriptions. Predicted child CWEs are mapped to their parent CWEs if applicable.
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- It achieves the following results on the evaluation set:
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- - Loss: 1.7510
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- - Accuracy: 0.5455
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- - F1 Macro: 0.3776
 
 
 
 
 
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  ## Training procedure
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@@ -50,51 +51,51 @@ 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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- | 3.226 | 1.0 | 125 | 3.1362 | 0.0382 | 0.0035 |
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- | 3.0244 | 2.0 | 250 | 2.9390 | 0.2155 | 0.1215 |
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- | 2.589 | 3.0 | 375 | 2.3469 | 0.4141 | 0.2521 |
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- | 2.1614 | 4.0 | 500 | 2.0701 | 0.4355 | 0.2551 |
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- | 1.8396 | 5.0 | 625 | 1.9336 | 0.4467 | 0.2748 |
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- | 1.5698 | 6.0 | 750 | 1.9086 | 0.4905 | 0.2938 |
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- | 1.4142 | 7.0 | 875 | 1.7933 | 0.5174 | 0.3416 |
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- | 1.2292 | 8.0 | 1000 | 1.7510 | 0.5455 | 0.3776 |
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- | 1.1182 | 9.0 | 1125 | 1.7681 | 0.5713 | 0.3803 |
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- | 0.9924 | 10.0 | 1250 | 1.8151 | 0.6083 | 0.4059 |
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- | 0.9307 | 11.0 | 1375 | 1.8391 | 0.6218 | 0.4379 |
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- | 0.7875 | 12.0 | 1500 | 1.8065 | 0.6038 | 0.4048 |
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- | 0.6308 | 13.0 | 1625 | 1.9221 | 0.6409 | 0.4210 |
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- | 0.7327 | 14.0 | 1750 | 1.9986 | 0.6465 | 0.4775 |
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- | 0.5175 | 15.0 | 1875 | 2.0520 | 0.6644 | 0.4316 |
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- | 0.5302 | 16.0 | 2000 | 2.0989 | 0.6712 | 0.4528 |
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- | 0.38 | 17.0 | 2125 | 2.0826 | 0.6734 | 0.4669 |
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- | 0.3768 | 18.0 | 2250 | 2.1953 | 0.6611 | 0.4544 |
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- | 0.3653 | 19.0 | 2375 | 2.2217 | 0.6880 | 0.5000 |
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- | 0.3349 | 20.0 | 2500 | 2.1911 | 0.6880 | 0.4951 |
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- | 0.2563 | 21.0 | 2625 | 2.2999 | 0.6813 | 0.4771 |
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- | 0.2513 | 22.0 | 2750 | 2.4158 | 0.7037 | 0.4640 |
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- | 0.2154 | 23.0 | 2875 | 2.4323 | 0.7138 | 0.4689 |
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- | 0.1889 | 24.0 | 3000 | 2.4296 | 0.7037 | 0.4733 |
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- | 0.2042 | 25.0 | 3125 | 2.5223 | 0.7071 | 0.4411 |
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- | 0.1774 | 26.0 | 3250 | 2.5476 | 0.7037 | 0.5083 |
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- | 0.156 | 27.0 | 3375 | 2.5737 | 0.7205 | 0.5236 |
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- | 0.1406 | 28.0 | 3500 | 2.6518 | 0.7048 | 0.5220 |
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- | 0.144 | 29.0 | 3625 | 2.6388 | 0.7015 | 0.4789 |
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- | 0.1119 | 30.0 | 3750 | 2.7159 | 0.7228 | 0.5003 |
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- | 0.1187 | 31.0 | 3875 | 2.7170 | 0.7071 | 0.4973 |
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- | 0.1095 | 32.0 | 4000 | 2.7796 | 0.7160 | 0.4707 |
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- | 0.1082 | 33.0 | 4125 | 2.7926 | 0.7239 | 0.5038 |
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- | 0.0976 | 34.0 | 4250 | 2.8240 | 0.7149 | 0.4515 |
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- | 0.0885 | 35.0 | 4375 | 2.8532 | 0.7149 | 0.4466 |
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- | 0.0872 | 36.0 | 4500 | 2.8697 | 0.7183 | 0.4700 |
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- | 0.0795 | 37.0 | 4625 | 2.8467 | 0.7138 | 0.4994 |
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- | 0.0878 | 38.0 | 4750 | 2.8566 | 0.7104 | 0.4673 |
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- | 0.0886 | 39.0 | 4875 | 2.8951 | 0.7127 | 0.4667 |
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- | 0.086 | 40.0 | 5000 | 2.8841 | 0.7127 | 0.4683 |
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  ### Framework versions
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- - Transformers 4.57.3
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- - Pytorch 2.9.1+cu128
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- - Datasets 4.4.2
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  - Tokenizers 0.22.2
 
1
  ---
2
  library_name: transformers
3
+ license: mit
4
  base_model: roberta-base
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  tags:
6
  - 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: []
 
 
12
  ---
13
 
14
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
15
  should probably proofread and complete it, then remove this comment. -->
16
 
17
+ # cwe-parent-vulnerability-classification-roberta-base
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19
+ 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: 4.2511
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+ - Accuracy: 0.5683
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+ - F1 Macro: 0.2101
24
 
25
+ ## Model description
26
 
27
+ More information needed
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+
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+ ## Intended uses & limitations
30
+
31
+ More information needed
32
+
33
+ ## Training and evaluation data
34
+
35
+ More information needed
36
 
37
  ## Training procedure
38
 
 
51
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
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+ | 5.6204 | 1.0 | 101 | 5.5246 | 0.0189 | 0.0004 |
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+ | 5.4605 | 2.0 | 202 | 5.4081 | 0.0068 | 0.0005 |
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+ | 5.4306 | 3.0 | 303 | 5.3191 | 0.0447 | 0.0045 |
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+ | 5.3366 | 4.0 | 404 | 5.2692 | 0.0717 | 0.0049 |
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+ | 5.2705 | 5.0 | 505 | 5.2310 | 0.0704 | 0.0096 |
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+ | 5.1530 | 6.0 | 606 | 5.1756 | 0.0934 | 0.0136 |
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+ | 4.9916 | 7.0 | 707 | 5.1084 | 0.2097 | 0.0299 |
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+ | 4.8387 | 8.0 | 808 | 5.0626 | 0.2341 | 0.0419 |
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+ | 4.7198 | 9.0 | 909 | 5.0164 | 0.2503 | 0.0616 |
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+ | 4.6754 | 10.0 | 1010 | 4.9531 | 0.2963 | 0.0674 |
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+ | 4.4443 | 11.0 | 1111 | 4.9144 | 0.3194 | 0.0714 |
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+ | 4.3628 | 12.0 | 1212 | 4.8954 | 0.3315 | 0.0811 |
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+ | 4.2481 | 13.0 | 1313 | 4.8476 | 0.3654 | 0.1104 |
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+ | 4.1578 | 14.0 | 1414 | 4.7984 | 0.3775 | 0.1155 |
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+ | 3.9924 | 15.0 | 1515 | 4.7600 | 0.4181 | 0.1226 |
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+ | 3.9078 | 16.0 | 1616 | 4.7190 | 0.4263 | 0.1215 |
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+ | 3.8065 | 17.0 | 1717 | 4.6783 | 0.4506 | 0.1442 |
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+ | 3.7696 | 18.0 | 1818 | 4.6424 | 0.4696 | 0.1503 |
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+ | 3.7075 | 19.0 | 1919 | 4.6157 | 0.4696 | 0.1438 |
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+ | 3.5318 | 20.0 | 2020 | 4.5766 | 0.4736 | 0.1489 |
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+ | 3.5248 | 21.0 | 2121 | 4.5494 | 0.4831 | 0.1463 |
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+ | 3.5334 | 22.0 | 2222 | 4.5183 | 0.5101 | 0.1718 |
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+ | 3.3713 | 23.0 | 2323 | 4.4923 | 0.5183 | 0.1595 |
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+ | 3.2803 | 24.0 | 2424 | 4.4588 | 0.5223 | 0.1758 |
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+ | 3.2246 | 25.0 | 2525 | 4.4311 | 0.5250 | 0.1932 |
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+ | 3.1723 | 26.0 | 2626 | 4.4115 | 0.5359 | 0.1911 |
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+ | 3.0648 | 27.0 | 2727 | 4.3898 | 0.5359 | 0.1986 |
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+ | 2.9372 | 28.0 | 2828 | 4.3769 | 0.5426 | 0.1994 |
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+ | 3.0113 | 29.0 | 2929 | 4.3596 | 0.5494 | 0.1968 |
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+ | 2.9797 | 30.0 | 3030 | 4.3321 | 0.5413 | 0.1882 |
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+ | 2.9339 | 31.0 | 3131 | 4.3254 | 0.5453 | 0.1944 |
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+ | 2.8733 | 32.0 | 3232 | 4.3052 | 0.5521 | 0.1934 |
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+ | 2.8051 | 33.0 | 3333 | 4.2951 | 0.5629 | 0.2121 |
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+ | 2.8297 | 34.0 | 3434 | 4.2923 | 0.5589 | 0.2049 |
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+ | 2.7814 | 35.0 | 3535 | 4.2770 | 0.5616 | 0.2079 |
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+ | 2.7509 | 36.0 | 3636 | 4.2605 | 0.5670 | 0.2107 |
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+ | 2.7396 | 37.0 | 3737 | 4.2677 | 0.5670 | 0.2128 |
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+ | 2.7384 | 38.0 | 3838 | 4.2520 | 0.5670 | 0.2099 |
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+ | 2.7081 | 39.0 | 3939 | 4.2548 | 0.5670 | 0.2115 |
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+ | 2.7587 | 40.0 | 4040 | 4.2511 | 0.5683 | 0.2101 |
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  ### Framework versions
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+ - Transformers 5.13.0
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+ - Pytorch 2.12.1+cu130
100
+ - Datasets 4.8.5
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  - Tokenizers 0.22.2
config.json CHANGED
@@ -12,617 +12,617 @@
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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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