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distilbert-NER-conll2003
joshuaphua/distilbert-NER-conll2003
distilbert-NER-conll2003 is a machine learning model from joshuaphua. Use it for the machine learning task on the model card, and read the license before you ship it in a product. 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
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Aug 14, 2024
- Updated
- Aug 20, 2024
- SHA
- f0345e3e
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. -->
distilbert-NER-conll2003
This model is a fine-tuned version of dslim/distilbert-NER on the conll2003 dataset. It achieves the following results on the evaluation set:
- Loss: nan
- Precision: 0.8732
- Recall: 0.8964
- F1: 0.8847
- Accuracy: 0.9751
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0605 | 1.0 | 3922 | nan | 0.8717 | 0.8877 | 0.8796 | 0.9742 |
| 0.0296 | 2.0 | 7844 | nan | 0.8732 | 0.8964 | 0.8847 | 0.9751 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.2.2
- Datasets 2.20.0
- Tokenizers 0.13.3
- Type
- distilbert
- License
- apache-2.0
- Created
- Aug 14, 2024
- Updated
- Aug 20, 2024