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BERT-finetuned-case-hold
samuelsavine/BERT-finetuned-case-hold
BERT-finetuned-case-hold is a multiple choice model from samuelsavine. Use it for the multiple choice task on the model card, and read the license before you ship it in a product. 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
- multiple choice
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Apr 29, 2025
- Updated
- Apr 29, 2025
- SHA
- 7243d83a
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-finetuned-case-hold
This model is a fine-tuned version of google-bert/bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7475
- Accuracy: 0.7367
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7716 | 1.0 | 1407 | 0.6712 | 0.7321 |
| 0.6004 | 2.0 | 2814 | 0.6744 | 0.7364 |
| 0.485 | 3.0 | 4221 | 0.7475 | 0.7367 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu118
- Datasets 3.2.0
- Tokenizers 0.21.0
- Task
- multiple choice
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Apr 29, 2025
- Updated
- Apr 29, 2025