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bert-base-uncased-mrpc-best
emirergin16/bert-base-uncased-mrpc-best
bert-base-uncased-mrpc-best is a text classification model from emirergin16. 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
- Dec 2, 2025
- Updated
- Dec 3, 2025
- SHA
- c9f14358
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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-mrpc-best
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: 0.4901
- Accuracy: 0.7791
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: 2.09520379133665e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5926 | 1.0 | 115 | 0.5116 | 0.7745 |
| 0.4346 | 2.0 | 230 | 0.4532 | 0.8088 |
| 0.2851 | 3.0 | 345 | 0.4334 | 0.8284 |
| 0.183 | 4.0 | 460 | 0.5309 | 0.8211 |
| 0.1111 | 5.0 | 575 | 0.5890 | 0.8235 |
Framework versions
- Transformers 4.57.2
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Dec 2, 2025
- Updated
- Dec 3, 2025