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bert-finetuned-ner
Xzt/bert-finetuned-ner
bert-finetuned-ner is a token classification model from Xzt. 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.
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
- May 4, 2022
- Updated
- May 18, 2022
- SHA
- a1dbb31c
Try a prompt
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
Xzt/bert-finetuned-ner
This model is a fine-tuned version of hfl/chinese-bert-wwm-ext on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.0622
- Epoch: 0
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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 7039, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32
Training results
| Train Loss | Epoch |
|---|---|
| 0.0622 | 0 |
Framework versions
- Transformers 4.18.0
- TensorFlow 2.6.0
- Datasets 1.18.0
- Tokenizers 0.12.1
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- May 4, 2022
- Updated
- May 18, 2022