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bert-finetuned-ner_offres
bileldh/bert-finetuned-ner_offres
bert-finetuned-ner_offres is a token classification model from bileldh. 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
- Jan 6, 2023
- Updated
- Jan 7, 2023
- SHA
- 4b99bdeb
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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-finetuned-ner_offres
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: 0.3309
- Precision: 0.2123
- Recall: 0.1950
- F1: 0.2033
- Accuracy: 0.9178
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 | 100 | 0.3799 | 0.1043 | 0.0755 | 0.0876 | 0.9133 |
| No log | 2.0 | 200 | 0.3364 | 0.1608 | 0.1447 | 0.1523 | 0.9177 |
| No log | 3.0 | 300 | 0.3309 | 0.2123 | 0.1950 | 0.2033 | 0.9178 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Jan 6, 2023
- Updated
- Jan 7, 2023