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bert-news-classifier
Mint1501/bert-news-classifier
bert-news-classifier is a text classification model from Mint1501. 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 30, 2025
- Updated
- Mar 30, 2025
- SHA
- 7d3c3792
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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-news-classifier
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: 0.5859
- Accuracy: 0.8471
- Precision: 0.8492
- Recall: 0.8471
- F1-score: 0.8463
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1-score |
|---|---|---|---|---|---|---|---|
| 1.8874 | 1.0 | 788 | 1.1642 | 0.5871 | 0.6028 | 0.5871 | 0.5692 |
| 0.8034 | 2.0 | 1576 | 0.6257 | 0.8214 | 0.8249 | 0.8214 | 0.8195 |
| 0.5749 | 3.0 | 2364 | 0.5859 | 0.8471 | 0.8492 | 0.8471 | 0.8463 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cpu
- Datasets 3.3.2
- Tokenizers 0.21.0
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Mar 30, 2025
- Updated
- Mar 30, 2025