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fine-tuned-bert-large-uncased-swag
amritpuhan/fine-tuned-bert-large-uncased-swag
fine-tuned-bert-large-uncased-swag is a multiple choice model from amritpuhan. 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 6, 2024
- Updated
- Jun 8, 2024
- SHA
- 7da0fb83
Base models
Datasets
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. -->
fine-tuned-bert-large-uncased-swag
This model is a fine-tuned version of bert-large-uncased on the swag dataset. It achieves the following results on the evaluation set:
- Loss: 0.9041
- Accuracy: 0.8505
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: 1.5e-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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6324 | 1.0 | 4597 | 0.4249 | 0.8428 |
| 0.3435 | 2.0 | 9194 | 0.4327 | 0.8456 |
| 0.1759 | 3.0 | 13791 | 0.6816 | 0.8475 |
| 0.0677 | 4.0 | 18388 | 0.9041 | 0.8505 |
Framework versions
- Transformers 4.41.2
- Pytorch 1.11.0
- Datasets 2.19.1
- Tokenizers 0.19.1
- Task
- multiple choice
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Jun 6, 2024
- Updated
- Jun 8, 2024