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pharmacoNER
aimarsg/pharmacoNER
pharmacoNER is a token classification model from aimarsg. 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
- roberta
- Access
- Public
- Created
- Feb 8, 2023
- Updated
- Feb 8, 2023
- SHA
- b4d8503e
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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. -->
pharmacoNER
This model is a fine-tuned version of PlanTL-GOB-ES/bsc-bio-ehr-es on the pharmaconer dataset. It achieves the following results on the evaluation set:
- Loss: 0.0251
- Precision: 0.9058
- Recall: 0.9026
- F1: 0.9042
- Accuracy: 0.9948
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 |
|---|---|---|---|---|---|---|---|
| 0.0272 | 1.0 | 1017 | 0.0288 | 0.8047 | 0.8503 | 0.8269 | 0.9914 |
| 0.0114 | 2.0 | 2034 | 0.0240 | 0.8950 | 0.8998 | 0.8974 | 0.9945 |
| 0.006 | 3.0 | 3051 | 0.0251 | 0.9058 | 0.9026 | 0.9042 | 0.9948 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
- Task
- Token Classification
- Library
- transformers
- Type
- roberta
- License
- apache-2.0
- Created
- Feb 8, 2023
- Updated
- Feb 8, 2023