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bert-tzh-med-ner
kaishih/bert-tzh-med-ner
bert-tzh-med-ner is a machine learning model from kaishih. 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
- bert
- Access
- Public
- Created
- Sep 2, 2024
- Updated
- Sep 2, 2024
- SHA
- c9221553
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. -->
test-ner
This model is a fine-tuned version of bert-base-chinese on an CMeEE-V2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4423
- Precision: 0.5197
- Recall: 0.6287
- F1: 0.5690
- Accuracy: 0.8492
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 |
|---|---|---|---|---|---|---|---|
| 0.6791 | 1.0 | 938 | 0.4600 | 0.5031 | 0.6096 | 0.5513 | 0.8435 |
| 0.3969 | 2.0 | 1876 | 0.4423 | 0.5197 | 0.6287 | 0.5690 | 0.8492 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
- Type
- bert
- License
- apache-2.0
- Languages
- zh
- Created
- Sep 2, 2024
- Updated
- Sep 2, 2024