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bert-biobert
Ironwolf1212/bert-biobert
bert-biobert is a token classification model from Ironwolf1212. Use it when you need labels on individual words, such as names. It is set up for transformers. 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
- Task
- Token Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Nov 20, 2024
- Updated
- Nov 21, 2024
- SHA
- b0836c15
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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. -->
bert-biobert
This model is a fine-tuned version of distilbert-base-uncased on the biobert_json dataset. It achieves the following results on the evaluation set:
- Loss: 0.1159
- Precision: 0.9239
- Recall: 0.9548
- F1: 0.9391
- Accuracy: 0.9698
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use 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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.5326 | 1.0 | 612 | 0.1450 | 0.9196 | 0.9350 | 0.9272 | 0.9642 |
| 0.175 | 2.0 | 1224 | 0.1159 | 0.9239 | 0.9548 | 0.9391 | 0.9698 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Nov 20, 2024
- Updated
- Nov 21, 2024