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bert-ner-conll2003
claudiaspseabra-ua/bert-ner-conll2003
bert-ner-conll2003 is a machine learning model from claudiaspseabra-ua. Use it for the machine learning task on the model card, and read the license before you ship it in a product. 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
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Apr 24, 2026
- Updated
- May 1, 2026
- SHA
- c2156685
Base models
Datasets
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-ner-conll2003
This model is a fine-tuned version of bert-base-cased on the conll2003 dataset. It achieves the following results on the evaluation set:
- Loss: 0.7393
- Precision: 0.9421
- Recall: 0.9490
- F1: 0.9455
- Accuracy: 0.9907
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 2.673 | 1.0 | 878 | 0.7181 | 0.9255 | 0.9336 | 0.9296 | 0.9886 |
| 0.4519 | 2.0 | 1756 | 0.7564 | 0.9396 | 0.9427 | 0.9411 | 0.9899 |
| 0.2646 | 3.0 | 2634 | 0.7393 | 0.9421 | 0.9490 | 0.9455 | 0.9907 |
Framework versions
- Transformers 4.36.0
- Pytorch 2.10.0+cu128
- Datasets 2.16.0
- Tokenizers 0.15.2
- Type
- bert
- License
- apache-2.0
- Created
- Apr 24, 2026
- Updated
- May 1, 2026