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punjabi-bert-ner
mirfan899/punjabi-bert-ner
punjabi-bert-ner is a token classification model from mirfan899. 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
- Sep 13, 2023
- Updated
- Feb 12, 2025
- SHA
- b5ffb5a0
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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. -->
punjabi-bert-ner
This model is a fine-tuned version of bert-base-multilingual-cased on an punjabi-ner dataset. It achieves the following results on the evaluation set:
- Loss: 0.0773
- Precision: 0.7730
- Recall: 0.7767
- F1: 0.7748
- Accuracy: 0.9794
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 |
|---|---|---|---|---|---|---|---|
| 0.1001 | 1.0 | 1613 | 0.0792 | 0.7619 | 0.6539 | 0.7037 | 0.9752 |
| 0.0645 | 2.0 | 3226 | 0.0742 | 0.7684 | 0.7528 | 0.7605 | 0.9787 |
| 0.0397 | 3.0 | 4839 | 0.0773 | 0.7730 | 0.7767 | 0.7748 | 0.9794 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Sep 13, 2023
- Updated
- Feb 12, 2025