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bert-finetuned-ncbi
ducmai-4203/bert-finetuned-ncbi
bert-finetuned-ncbi is a token classification model from ducmai-4203. 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
- Mar 18, 2025
- Updated
- Mar 18, 2025
- SHA
- 6373ed21
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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. -->
bert-finetuned-ncbi
This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1494
- Precision: 0.5351
- Recall: 0.6380
- F1: 0.5820
- Accuracy: 0.9437
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: 8
- eval_batch_size: 8
- 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1187 | 1.0 | 1359 | 0.1293 | 0.4997 | 0.5570 | 0.5268 | 0.9413 |
| 0.0781 | 2.0 | 2718 | 0.1360 | 0.5572 | 0.6824 | 0.6135 | 0.9447 |
| 0.0673 | 3.0 | 4077 | 0.1494 | 0.5351 | 0.6380 | 0.5820 | 0.9437 |
Framework versions
- Transformers 4.48.1
- Pytorch 2.6.0+cu118
- Datasets 2.21.0
- Tokenizers 0.21.0
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Mar 18, 2025
- Updated
- Mar 18, 2025