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bert-agnews
taherimoalem/bert-agnews
bert-agnews is a text classification model from taherimoalem. 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
- Feb 4, 2026
- Updated
- Mar 12, 2026
- SHA
- 7b0af2d5
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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-agnews
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: 0.2343
- Accuracy: 0.946
- F1 Macro: 0.9456
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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- 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
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
|---|---|---|---|---|---|
| 0.2213 | 1.0 | 3594 | 0.1723 | 0.939 | 0.9386 |
| 0.1288 | 2.0 | 7188 | 0.1712 | 0.9456 | 0.9453 |
| 0.0836 | 3.0 | 10782 | 0.1990 | 0.9478 | 0.9473 |
| 0.0539 | 4.0 | 14376 | 0.2343 | 0.946 | 0.9456 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.5.1+cu121
- Datasets 4.5.0
- Tokenizers 0.22.2
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Feb 4, 2026
- Updated
- Mar 12, 2026