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bert-finetuned-ner
CarlosHRdJ/bert-finetuned-ner
bert-finetuned-ner is a token classification model from CarlosHRdJ. 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 25, 2024
- Updated
- Mar 26, 2024
- SHA
- 794e1ea5
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Base models
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 an unknown dataset. It achieves the following results on the evaluation set:
- Loss: nan
- Precision: 0.6085
- Recall: 0.7622
- F1: 0.6768
- Accuracy: 0.9635
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 |
|---|---|---|---|---|---|---|---|
| 0.2588 | 1.0 | 979 | nan | 0.5327 | 0.7221 | 0.6131 | 0.9543 |
| 0.0521 | 2.0 | 1958 | nan | 0.6024 | 0.7655 | 0.6743 | 0.9599 |
| 0.028 | 3.0 | 2937 | nan | 0.6085 | 0.7622 | 0.6768 | 0.9635 |
Framework versions
- Transformers 4.39.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Mar 25, 2024
- Updated
- Mar 26, 2024