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Balanced-KFold-ft-bert-base-uncased-for-binary-search
TrunkG0d/Balanced-KFold-ft-bert-base-uncased-for-binary-search
Balanced-KFold-ft-bert-base-uncased-for-binary-search is a text classification model from TrunkG0d. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Nov 9, 2024
- Updated
- Nov 9, 2024
- SHA
- a1532e0c
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Base models
Model card
From the Hugging Face model README
<!-- 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. -->
Balanced-KFold-ft-bert-base-uncased-for-binary-search
This model is a fine-tuned version of bert-base-uncased on the network_vulnerability_dataset.csv dataset. It achieves the following results on the evaluation set:
- Loss: 0.4549
- Accuracy: 0.7989
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.4663 | 1.0 | 109 | 0.4549 | 0.7989 |
| 0.4814 | 2.0 | 218 | 0.4474 | 0.7989 |
| 0.4625 | 3.0 | 327 | 0.4467 | 0.7989 |
| 0.523 | 4.0 | 436 | 0.4532 | 0.7989 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.2
- Tokenizers 0.20.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Nov 9, 2024
- Updated
- Nov 9, 2024