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test-biobert-finetuned-ner-ncbi
cp-gustavo/test-biobert-finetuned-ner-ncbi
test-biobert-finetuned-ner-ncbi is a token classification model from cp-gustavo. Use it when you need labels on individual words, such as names. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Token Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Apr 9, 2025
- Updated
- Apr 15, 2025
- SHA
- 25603ce8
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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-biobert-finetuned-ner-ncbi
This model is a fine-tuned version of dmis-lab/biobert-v1.1 on the medmentions dataset. It achieves the following results on the evaluation set:
- Loss: 0.5280
- Precision: 0.5594
- Recall: 0.5994
- F1: 0.5787
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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
|---|---|---|---|---|---|---|
| 0.8861 | 1.0 | 330 | 0.5909 | 0.5327 | 0.5038 | 0.5178 |
| 0.5305 | 2.0 | 660 | 0.5367 | 0.5508 | 0.5786 | 0.5644 |
| 0.4558 | 3.0 | 990 | 0.5280 | 0.5594 | 0.5994 | 0.5787 |
Framework versions
- Transformers 4.51.1
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- Created
- Apr 9, 2025
- Updated
- Apr 15, 2025