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bert-base-uncased-finetuned-swag
NightMachinery/bert-base-uncased-finetuned-swag
bert-base-uncased-finetuned-swag is a machine learning model from NightMachinery. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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Public
Updated Nov 10, 2023
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At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Nov 10, 2023
- Updated
- Nov 10, 2023
- SHA
- b7770b6b
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. -->
bert-base-uncased-finetuned-swag
This model is a fine-tuned version of bert-base-uncased on the swag dataset. It achieves the following results on the evaluation set:
- Loss: 0.7187
- Accuracy: 0.7223
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.9645 | 1.0 | 2299 | 0.7779 | 0.6998 |
| 0.8942 | 2.0 | 4598 | 0.7322 | 0.7184 |
| 0.8907 | 3.0 | 6897 | 0.7187 | 0.7223 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0
- Datasets 2.12.0
- Tokenizers 0.13.3
- License
- apache-2.0
- Created
- Nov 10, 2023
- Updated
- Nov 10, 2023