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bert-finetuned-ner
schubertcarvalho/bert-finetuned-ner
bert-finetuned-ner is a token classification model from schubertcarvalho. 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
- Oct 25, 2023
- Updated
- Jun 9, 2024
- SHA
- 99829917
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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-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: 0.0561
- Precision: 0.9210
- Recall: 0.9443
- F1: 0.9325
- Accuracy: 0.9858
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: 32
- eval_batch_size: 32
- 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 | 439 | 0.0758 | 0.8831 | 0.9192 | 0.9008 | 0.9789 |
| 0.1901 | 2.0 | 878 | 0.0572 | 0.9105 | 0.9399 | 0.9250 | 0.9846 |
| 0.0483 | 3.0 | 1317 | 0.0561 | 0.9210 | 0.9443 | 0.9325 | 0.9858 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0a0+29c30b1
- Datasets 2.14.5
- Tokenizers 0.14.1
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Oct 25, 2023
- Updated
- Jun 9, 2024