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WL_DISEASE_NER_v1
roscazo/WL_DISEASE_NER_v1
WL_DISEASE_NER_v1 is a token classification model from roscazo. 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
- Jan 27, 2023
- Updated
- Jan 27, 2023
- SHA
- 9499aafc
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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. -->
WL_DISEASE_NER_v1
This model is a fine-tuned version of PlanTL-GOB-ES/bsc-bio-ehr-es on the wl-disease dataset. It achieves the following results on the evaluation set:
- Loss: 0.1489
- Diso Precision: 0.7908
- Diso Recall: 0.8397
- Diso F1: 0.8145
- Diso Number: 1765
- Overall Precision: 0.7908
- Overall Recall: 0.8397
- Overall F1: 0.8145
- Overall Accuracy: 0.9631
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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Diso Precision | Diso Recall | Diso F1 | Diso Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.1199 | 1.0 | 1714 | 0.1187 | 0.7739 | 0.7972 | 0.7854 | 1765 | 0.7739 | 0.7972 | 0.7854 | 0.9610 |
| 0.0916 | 2.0 | 3428 | 0.1237 | 0.7748 | 0.8266 | 0.7999 | 1765 | 0.7748 | 0.8266 | 0.7999 | 0.9620 |
| 0.0625 | 3.0 | 5142 | 0.1343 | 0.7900 | 0.8289 | 0.8090 | 1765 | 0.7900 | 0.8289 | 0.8090 | 0.9630 |
| 0.0485 | 4.0 | 6856 | 0.1489 | 0.7908 | 0.8397 | 0.8145 | 1765 | 0.7908 | 0.8397 | 0.8145 | 0.9631 |
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
- Jan 27, 2023
- Updated
- Jan 27, 2023