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bert-base-uncased-finetuned-sql-classification-no_context
PatWang/bert-base-uncased-finetuned-sql-classification-no_context
bert-base-uncased-finetuned-sql-classification-no_context is a text classification model from PatWang. 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
- bert
- Access
- Public
- Created
- Mar 10, 2024
- Updated
- Mar 10, 2024
- SHA
- 0aa6c07d
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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-finetuned-sql-classification-no_context
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4198
- Accuracy: 0.8791
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.4969 | 1.0 | 1290 | 0.4608 | 0.8124 |
| 0.4308 | 2.0 | 2580 | 0.3739 | 0.8547 |
| 0.4018 | 3.0 | 3870 | 0.4356 | 0.8550 |
| 0.3308 | 4.0 | 5160 | 0.3754 | 0.8686 |
| 0.3403 | 5.0 | 6450 | 0.4198 | 0.8791 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Mar 10, 2024
- Updated
- Mar 10, 2024