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SourceData_RolesMulti_v1_0_0_PubMedBERT_large
EMBO/SourceData_RolesMulti_v1_0_0_PubMedBERT_large
SourceData_RolesMulti_v1_0_0_PubMedBERT_large is a token classification model from EMBO. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Token Classification
- Library
- transformers
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- Sep 16, 2025
- Updated
- Sep 16, 2025
- SHA
- 07d004dd
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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. -->
SourceData_RolesMulti_v1_0_0_PubMedBERT_large
This model is a fine-tuned version of microsoft/BiomedNLP-BiomedBERT-large-uncased-abstract on the source_data dataset. It achieves the following results on the evaluation set:
- Loss: 0.0068
- Accuracy Score: 0.9981
- Precision: 0.9613
- Recall: 0.9695
- F1: 0.9654
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: 16
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Use adafactor and the args are: No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 1.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy Score | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.0046 | 0.9994 | 863 | 0.0068 | 0.9981 | 0.9613 | 0.9695 | 0.9654 |
Framework versions
- Transformers 4.46.3
- Pytorch 1.13.1+cu117
- Datasets 3.1.0
- Tokenizers 0.20.3
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- License
- mit
- Created
- Sep 16, 2025
- Updated
- Sep 16, 2025