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bert-finetuned-ner
benshafat/bert-finetuned-ner
bert-finetuned-ner is a machine learning model from benshafat. 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
- Sep 9, 2024
- Updated
- Sep 9, 2024
- SHA
- 9667d502
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: 0.0634
- Precision: 0.9378
- Recall: 0.9509
- F1: 0.9443
- Accuracy: 0.9862
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 |
|---|---|---|---|---|---|---|---|
| 0.0792 | 1.0 | 1756 | 0.0841 | 0.9079 | 0.9325 | 0.9200 | 0.9790 |
| 0.0394 | 2.0 | 3512 | 0.0571 | 0.9292 | 0.9478 | 0.9384 | 0.9861 |
| 0.0252 | 3.0 | 5268 | 0.0634 | 0.9378 | 0.9509 | 0.9443 | 0.9862 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.15.2
- Type
- bert
- License
- apache-2.0
- Created
- Sep 9, 2024
- Updated
- Sep 9, 2024