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BERT-Finetuned-NER
Mehmood-Deshmukh/BERT-Finetuned-NER
BERT-Finetuned-NER is a machine learning model from Mehmood-Deshmukh. 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
- Aug 6, 2024
- Updated
- Aug 6, 2024
- SHA
- 517e27e9
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. -->
test-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: 0.0625
- Accuracy: 0.9843
- Precision: 0.9538
- Recall: 0.9606
- F1: 0.9572
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: 16
- 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 | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.2406 | 1.0 | 878 | 0.0700 | 0.9792 | 0.9365 | 0.9471 | 0.9417 |
| 0.0485 | 2.0 | 1756 | 0.0663 | 0.9829 | 0.9486 | 0.9566 | 0.9526 |
| 0.026 | 3.0 | 2634 | 0.0625 | 0.9843 | 0.9538 | 0.9606 | 0.9572 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Type
- bert
- License
- apache-2.0
- Created
- Aug 6, 2024
- Updated
- Aug 6, 2024