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bert-finetuned-ner-cti
thangvip/bert-finetuned-ner-cti
bert-finetuned-ner-cti is a token classification model from thangvip. Use it when you need labels on individual words, such as names. 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
- Token Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Nov 22, 2023
- Updated
- Nov 22, 2023
- SHA
- 90465627
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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-finetuned-ner-cti
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0676
- Precision: 0.9665
- Recall: 0.9794
- F1: 0.9729
- Accuracy: 0.9824
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 |
|---|---|---|---|---|---|---|---|
| 0.104 | 1.0 | 1725 | 0.0842 | 0.9532 | 0.9693 | 0.9612 | 0.9758 |
| 0.0603 | 2.0 | 3450 | 0.0694 | 0.9654 | 0.9760 | 0.9707 | 0.9808 |
| 0.0374 | 3.0 | 5175 | 0.0676 | 0.9665 | 0.9794 | 0.9729 | 0.9824 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Nov 22, 2023
- Updated
- Nov 22, 2023