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bert-finetuned-ner
Elytum/bert-finetuned-ner
bert-finetuned-ner is a token classification model from Elytum. 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
- Feb 8, 2023
- Updated
- Feb 8, 2023
- SHA
- 9daed2c6
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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 gaunernst/bert-small-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0186
- Precision: 0.9941
- Recall: 0.9952
- F1: 0.9946
- Accuracy: 0.9963
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 |
|---|---|---|---|---|---|---|---|
| 0.0277 | 1.0 | 2500 | 0.0190 | 0.9929 | 0.9939 | 0.9934 | 0.9956 |
| 0.0137 | 2.0 | 5000 | 0.0180 | 0.9935 | 0.9951 | 0.9943 | 0.9960 |
| 0.0095 | 3.0 | 7500 | 0.0186 | 0.9941 | 0.9952 | 0.9946 | 0.9963 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu117
- Datasets 2.9.0
- Tokenizers 0.13.2
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Feb 8, 2023
- Updated
- Feb 8, 2023