judithrosell/JNLPBA_ClinicalBERT_NER
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JNLPBAClinicalBERTNER
This model is a fine-tuned version of medicalai/ClinicalBERT on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1723
- Seqeval classification report: precision recall f1-score support
DNA 0.72 0.81 0.77 1351 RNA 0.71 0.86 0.78 723 cellline 0.84 0.74 0.78 582 celltype 0.72 0.75 0.73 5623 protein 0.85 0.85 0.85 3501
micro avg 0.76 0.79 0.78 11780 macro avg 0.77 0.80 0.78 11780 weighted avg 0.76 0.79 0.78 11780
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
- trainbatchsize: 16
- evalbatchsize: 16
- seed: 42
- gradientaccumulationsteps: 2
- totaltrainbatch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lrschedulertype: linear
- num_epochs: 3
Training results
DNA 0.72 0.77 0.75 1351 RNA 0.70 0.84 0.77 723 cellline 0.85 0.70 0.77 582 celltype 0.71 0.68 0.69 5623 protein 0.85 0.80 0.83 3501
micro avg 0.76 0.74 0.75 11780 macro avg 0.77 0.76 0.76 11780 weighted avg 0.76 0.74 0.75 11780 | | 0.1841 | 2.0 | 1164 | 0.1762 | precision recall f1-score support
DNA 0.73 0.78 0.76 1351 RNA 0.70 0.87 0.78 723 cellline 0.86 0.71 0.78 582 celltype 0.71 0.73 0.72 5623 protein 0.86 0.83 0.84 3501
micro avg 0.76 0.77 0.77 11780 macro avg 0.77 0.78 0.78 11780 weighted avg 0.77 0.77 0.77 11780 | | 0.1582 | 3.0 | 1746 | 0.1723 | precision recall f1-score support
DNA 0.72 0.81 0.77 1351 RNA 0.71 0.86 0.78 723 cellline 0.84 0.74 0.78 582 celltype 0.72 0.75 0.73 5623 protein 0.85 0.85 0.85 3501
micro avg 0.76 0.79 0.78 11780 macro avg 0.77 0.80 0.78 11780 weighted avg 0.76 0.79 0.78 11780 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
