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bert-base-uncased-finetuned-swag
Gefeizi/bert-base-uncased-finetuned-swag
bert-base-uncased-finetuned-swag is a multiple choice model from Gefeizi. 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
- Jun 11, 2025
- Updated
- Jun 12, 2025
- SHA
- c13a3394
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-finetuned-swag
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6457
- Accuracy: 0.8094
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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- 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 |
|---|---|---|---|---|
| 0.7548 | 1.0 | 1150 | 0.5624 | 0.7903 |
| 0.411 | 2.0 | 2300 | 0.5371 | 0.8054 |
| 0.193 | 3.0 | 3450 | 0.6457 | 0.8094 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
- Task
- multiple choice
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Jun 11, 2025
- Updated
- Jun 12, 2025