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b3r-test-half-epochs
cp-gustavo/b3r-test-half-epochs
b3r-test-half-epochs 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
- Sep 27, 2025
- Updated
- Sep 27, 2025
- SHA
- dd9de483
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Base models
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. -->
b3r-test-half-epochs
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: 0.5004
- Precision: 0.5859
- Recall: 0.6383
- F1: 0.6110
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: 0.00012839450868399685
- 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
- lr_scheduler_warmup_ratio: 0.1685473261668876
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
|---|---|---|---|---|---|---|
| 0.9512 | 1.0 | 330 | 0.5404 | 0.5490 | 0.5409 | 0.5449 |
| 0.4371 | 2.0 | 660 | 0.4880 | 0.5556 | 0.6303 | 0.5906 |
| 0.2961 | 3.0 | 990 | 0.5004 | 0.5859 | 0.6383 | 0.6110 |
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
- Sep 27, 2025
- Updated
- Sep 27, 2025