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bert-finetuned-for-ner
sunny2309/bert-finetuned-for-ner
bert-finetuned-for-ner is a token classification model from sunny2309. 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
- Dec 4, 2023
- Updated
- Dec 4, 2023
- SHA
- 7f0202e4
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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-for-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: 0.1653
- Precision: 0.7733
- Recall: 0.7915
- F1: 0.7823
- Accuracy: 0.9493
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 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 125 | 0.2616 | 0.6787 | 0.7156 | 0.6966 | 0.9261 |
| No log | 2.0 | 250 | 0.1916 | 0.7397 | 0.7650 | 0.7522 | 0.9411 |
| No log | 3.0 | 375 | 0.1653 | 0.7733 | 0.7915 | 0.7823 | 0.9493 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.0.1+cu117
- Datasets 2.15.0
- Tokenizers 0.15.0
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Dec 4, 2023
- Updated
- Dec 4, 2023