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bert-base-uncased-Federal-Regulations
Salm00n/bert-base-uncased-Federal-Regulations
bert-base-uncased-Federal-Regulations is a text classification model from Salm00n. 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
- distilbert
- Access
- Public
- Created
- Dec 4, 2024
- Updated
- Dec 10, 2024
- SHA
- 71b441b6
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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. -->
bert-base-uncased-Federal-Regulations
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6193
- Accuracy: 0.7332
- Precision: 0.7510
- Recall: 0.7332
- F1: 0.7394
- Roc Auc: 0.7821
- Confusion Matrix: [[2590, 795], [498, 963]]
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: 4e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Roc Auc | Confusion Matrix |
|---|---|---|---|---|---|---|---|---|---|
| 0.5846 | 1.0 | 600 | 0.6114 | 0.6620 | 0.7393 | 0.6620 | 0.6759 | 0.7668 | [[2092, 1293], [345, 1116]] |
| 0.5123 | 2.0 | 1200 | 0.5976 | 0.7210 | 0.7535 | 0.7210 | 0.7301 | 0.7848 | [[2465, 920], [432, 1029]] |
| 0.4449 | 3.0 | 1800 | 0.6193 | 0.7332 | 0.7510 | 0.7332 | 0.7394 | 0.7821 | [[2590, 795], [498, 963]] |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Dec 4, 2024
- Updated
- Dec 10, 2024