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my_ner_model
zhang-zx25/my_ner_model
my_ner_model is a machine learning model from zhang-zx25. 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
- Jul 22, 2026
- Updated
- Jul 22, 2026
- SHA
- b760b454
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. -->
my_ner_model
This model is a fine-tuned version of distilbert/distilbert-base-uncased on the ncbi_disease dataset. It achieves the following results on the evaluation set:
- Loss: 0.0566
- Precision: 0.7843
- Recall: 0.8361
- F1: 0.8093
- Accuracy: 0.9852
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 340 | 0.0601 | 0.7268 | 0.7776 | 0.7514 | 0.9809 |
| 0.0888 | 2.0 | 680 | 0.0548 | 0.7695 | 0.8272 | 0.7973 | 0.9843 |
| 0.0275 | 3.0 | 1020 | 0.0566 | 0.7843 | 0.8361 | 0.8093 | 0.9852 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.7.1+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2
- Type
- distilbert
- License
- apache-2.0
- Created
- Jul 22, 2026
- Updated
- Jul 22, 2026