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bert-finetuned-ner
Serah3/bert-finetuned-ner
bert-finetuned-ner is a token classification model from Serah3. 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
- distilbert
- Access
- Public
- Created
- Jan 12, 2023
- Updated
- Jan 12, 2023
- SHA
- c6c8c3d9
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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 distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0161
- Precision: 0.7061
- Recall: 0.7454
- F1: 0.7252
- Accuracy: 0.9954
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 | 31 | 0.0293 | 0.5270 | 0.1806 | 0.2690 | 0.9899 |
| No log | 2.0 | 62 | 0.0177 | 0.7110 | 0.7176 | 0.7143 | 0.9953 |
| No log | 3.0 | 93 | 0.0161 | 0.7061 | 0.7454 | 0.7252 | 0.9954 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.12.1
- Datasets 2.8.0
- Tokenizers 0.13.2
- Task
- Token Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Jan 12, 2023
- Updated
- Jan 12, 2023