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bert-base-uncased-ner-conll2003
andi611/bert-base-uncased-ner-conll2003
bert-base-uncased-ner-conll2003 is a token classification model from andi611. 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
- Mar 2, 2022
- Updated
- Jul 7, 2021
- SHA
- efdf72fb
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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-base-uncased-ner
This model is a fine-tuned version of bert-base-uncased on the conll2003 dataset. It achieves the following results on the evaluation set:
- Loss: 2.1258
- Precision: 0.0269
- Recall: 0.1379
- F1: 0.0451
- Accuracy: 0.1988
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: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 4 | 2.1296 | 0.0270 | 0.1389 | 0.0452 | 0.1942 |
| No log | 2.0 | 8 | 2.1258 | 0.0269 | 0.1379 | 0.0451 | 0.1988 |
Framework versions
- Transformers 4.8.2
- Pytorch 1.8.1+cu111
- Datasets 1.8.0
- Tokenizers 0.10.3
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Mar 2, 2022
- Updated
- Jul 7, 2021