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FoodEntityRecognition-BioBERT-frozen-layers-v4
fdastak/FoodEntityRecognition-BioBERT-frozen-layers-v4
FoodEntityRecognition-BioBERT-frozen-layers-v4 is a token classification model from fdastak. 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
- Jul 15, 2026
- Updated
- Jul 16, 2026
- SHA
- 5285a6cf
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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. -->
FoodEntityRecognition-BioBERT-frozen-layers-v4
This model is a fine-tuned version of dmis-lab/biobert-v1.1 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0042
- Precision: 0.8063
- Recall: 0.8747
- F1: 0.8391
- Accuracy: 0.9869
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0488 | 1.0 | 117 | 0.0085 | 0.6630 | 0.7643 | 0.7101 | 0.9731 |
| 0.0086 | 2.0 | 234 | 0.0058 | 0.7090 | 0.8174 | 0.7594 | 0.9785 |
| 0.0066 | 3.0 | 351 | 0.0047 | 0.7847 | 0.8280 | 0.8058 | 0.9843 |
| 0.0056 | 4.0 | 468 | 0.0046 | 0.8139 | 0.8450 | 0.8292 | 0.9853 |
| 0.0049 | 5.0 | 585 | 0.0051 | 0.725 | 0.8620 | 0.7876 | 0.9809 |
| 0.0043 | 6.0 | 702 | 0.0041 | 0.8225 | 0.8854 | 0.8528 | 0.9876 |
| 0.0038 | 7.0 | 819 | 0.0042 | 0.7961 | 0.8620 | 0.8277 | 0.9861 |
| 0.0035 | 8.0 | 936 | 0.0042 | 0.8063 | 0.8747 | 0.8391 | 0.9869 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.8.0+cpu
- Datasets 4.0.0
- Tokenizers 0.22.1
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- Created
- Jul 15, 2026
- Updated
- Jul 16, 2026