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news_classification_file
kozy9/news_classification_file
news_classification_file is a text classification model from kozy9. 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
- distilbert
- Access
- Public
- Created
- Dec 3, 2025
- Updated
- Dec 15, 2025
- SHA
- 247175ae
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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. -->
news_classification_file
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4052
- Accuracy: 0.89
- F1: 0.8902
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: 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 | F1 |
|---|---|---|---|---|---|
| 0.812 | 1.0 | 32 | 0.4014 | 0.875 | 0.8756 |
| 0.299 | 2.0 | 64 | 0.3691 | 0.89 | 0.8903 |
| 0.1833 | 3.0 | 96 | 0.3947 | 0.88 | 0.8808 |
| 0.137 | 4.0 | 128 | 0.4067 | 0.89 | 0.8904 |
| 0.1069 | 5.0 | 160 | 0.4052 | 0.89 | 0.8902 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Dec 3, 2025
- Updated
- Dec 15, 2025