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BlueBERT_BC5CDR_NER_new
judithrosell/BlueBERT_BC5CDR_NER_new
BlueBERT_BC5CDR_NER_new is a token classification model from judithrosell. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as cc0-1.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Token Classification
- Library
- transformers
- License
- cc0-1.0
- Model type
- bert
- Access
- Public
- Created
- Jan 2, 2024
- Updated
- Jan 2, 2024
- SHA
- 39b72133
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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. -->
BlueBERT_BC5CDR_NER_new
This model is a fine-tuned version of bionlp/bluebert_pubmed_mimic_uncased_L-12_H-768_A-12 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0950
- Precision: 0.9736
- Recall: 0.9710
- F1: 0.9723
- Accuracy: 0.9704
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: 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 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 286 | 0.1058 | 0.9683 | 0.9648 | 0.9665 | 0.9644 |
| 0.1425 | 2.0 | 572 | 0.0898 | 0.9726 | 0.9706 | 0.9716 | 0.9701 |
| 0.1425 | 3.0 | 858 | 0.0950 | 0.9736 | 0.9710 | 0.9723 | 0.9704 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- License
- cc0-1.0
- Created
- Jan 2, 2024
- Updated
- Jan 2, 2024