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bert-base-uncased-sst2-qnli
AKHILESHANIL25/bert-base-uncased-sst2-qnli
bert-base-uncased-sst2-qnli is a text classification model from AKHILESHANIL25. 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
- Jul 1, 2025
- Updated
- Jul 1, 2025
- SHA
- 8a9e76e1
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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-sst2-qnli
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: 0.4663
- Accuracy: 0.8788
- Precision: 0.8779
- Recall: 0.8756
- F1: 0.8767
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: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.4939 | 1.0 | 3438 | 0.4533 | 0.8325 | 0.8266 | 0.8350 | 0.8308 |
| 0.3678 | 2.0 | 6876 | 0.3815 | 0.8475 | 0.8254 | 0.8756 | 0.8498 |
| 0.2783 | 3.0 | 10314 | 0.4029 | 0.855 | 0.8424 | 0.8680 | 0.855 |
| 0.2132 | 4.0 | 13752 | 0.4663 | 0.8788 | 0.8779 | 0.8756 | 0.8767 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Jul 1, 2025
- Updated
- Jul 1, 2025