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bert-finetuned-ncbi
Umesh/bert-finetuned-ncbi
bert-finetuned-ncbi is a token classification model from Umesh. 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
- Jan 24, 2023
- Updated
- Jan 24, 2023
- SHA
- c81e11a0
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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. -->
bert-finetuned-ncbi
This model is a fine-tuned version of bert-base-cased on the ncbi_disease dataset. It achieves the following results on the evaluation set:
- Loss: 0.0679
- Precision: 0.7807
- Recall: 0.8640
- F1: 0.8203
- Accuracy: 0.9831
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1146 | 1.0 | 680 | 0.0686 | 0.7450 | 0.8056 | 0.7741 | 0.9805 |
| 0.0458 | 2.0 | 1360 | 0.0612 | 0.7646 | 0.8628 | 0.8107 | 0.9815 |
| 0.0161 | 3.0 | 2040 | 0.0679 | 0.7807 | 0.8640 | 0.8203 | 0.9831 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Jan 24, 2023
- Updated
- Jan 24, 2023