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bert-finetuned-ner
jesusnieto/bert-finetuned-ner
bert-finetuned-ner is a machine learning model from jesusnieto. 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
- Nov 4, 2025
- Updated
- Nov 4, 2025
- SHA
- 41797372
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-finetuned-ner
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: 0.0629
- Precision: 0.9344
- Recall: 0.9487
- F1: 0.9415
- Accuracy: 0.9856
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: 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 |
|---|---|---|---|---|---|---|---|
| 0.0783 | 1.0 | 1756 | 0.0677 | 0.9046 | 0.9303 | 0.9173 | 0.9818 |
| 0.0354 | 2.0 | 3512 | 0.0729 | 0.9302 | 0.9424 | 0.9363 | 0.9844 |
| 0.0243 | 3.0 | 5268 | 0.0629 | 0.9344 | 0.9487 | 0.9415 | 0.9856 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.6.0+cpu
- Datasets 3.6.0
- Tokenizers 0.15.2
- Type
- bert
- License
- apache-2.0
- Created
- Nov 4, 2025
- Updated
- Nov 4, 2025