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---
base_model: medicalai/ClinicalBERT
tags:
- generated_from_trainer
model-index:
- name: BioNLP13CG_ClinicalBERT_NER
results: []
---
<!-- 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. -->
# BioNLP13CG_ClinicalBERT_NER
This model is a fine-tuned version of [medicalai/ClinicalBERT](https://huggingface.co/medicalai/ClinicalBERT) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3339
- Seqeval classification report: precision recall f1-score support
Amino_acid 0.81 0.59 0.68 297
Anatomical_system 0.70 0.78 0.74 297
Cancer 0.74 0.73 0.73 3490
Cell 0.72 0.87 0.79 1360
Cellular_component 0.00 0.00 0.00 99
Developing_anatomical_structure 0.00 0.00 0.00 11
Gene_or_gene_product 0.67 0.25 0.37 174
Immaterial_anatomical_entity 0.52 0.76 0.62 432
Multi-tissue_structure 0.83 0.59 0.69 317
Organ 0.00 0.00 0.00 49
Organism 0.71 0.48 0.57 464
Organism_subdivision 0.70 0.72 0.71 678
Organism_substance 0.00 0.00 0.00 128
Pathological_formation 0.62 0.05 0.09 108
Simple_chemical 0.00 0.00 0.00 56
Tissue 0.80 0.85 0.82 1566
micro avg 0.73 0.71 0.72 9526
macro avg 0.49 0.42 0.43 9526
weighted avg 0.71 0.71 0.70 9526
## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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 | Seqeval classification report |
|:-------------:|:-----:|:----:|:---------------:|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
| No log | 0.99 | 95 | 0.4681 | precision recall f1-score support
Amino_acid 1.00 0.02 0.04 297
Anatomical_system 0.44 0.68 0.54 297
Cancer 0.68 0.63 0.65 3490
Cell 0.59 0.85 0.70 1360
Cellular_component 0.00 0.00 0.00 99
Developing_anatomical_structure 0.00 0.00 0.00 11
Gene_or_gene_product 0.00 0.00 0.00 174
Immaterial_anatomical_entity 0.40 0.60 0.48 432
Multi-tissue_structure 0.86 0.06 0.11 317
Organ 0.00 0.00 0.00 49
Organism 0.88 0.02 0.03 464
Organism_subdivision 0.62 0.54 0.58 678
Organism_substance 0.00 0.00 0.00 128
Pathological_formation 0.00 0.00 0.00 108
Simple_chemical 0.00 0.00 0.00 56
Tissue 0.70 0.84 0.76 1566
micro avg 0.63 0.58 0.60 9526
macro avg 0.39 0.27 0.24 9526
weighted avg 0.63 0.58 0.55 9526
|
| No log | 2.0 | 191 | 0.3526 | precision recall f1-score support
Amino_acid 0.81 0.52 0.63 297
Anatomical_system 0.66 0.77 0.71 297
Cancer 0.74 0.73 0.73 3490
Cell 0.71 0.87 0.78 1360
Cellular_component 0.00 0.00 0.00 99
Developing_anatomical_structure 0.00 0.00 0.00 11
Gene_or_gene_product 0.76 0.20 0.32 174
Immaterial_anatomical_entity 0.46 0.76 0.57 432
Multi-tissue_structure 0.83 0.57 0.68 317
Organ 0.00 0.00 0.00 49
Organism 0.68 0.44 0.54 464
Organism_subdivision 0.71 0.67 0.69 678
Organism_substance 0.00 0.00 0.00 128
Pathological_formation 1.00 0.01 0.02 108
Simple_chemical 0.00 0.00 0.00 56
Tissue 0.78 0.85 0.81 1566
micro avg 0.72 0.70 0.71 9526
macro avg 0.51 0.40 0.41 9526
weighted avg 0.70 0.70 0.68 9526
|
| No log | 2.98 | 285 | 0.3339 | precision recall f1-score support
Amino_acid 0.81 0.59 0.68 297
Anatomical_system 0.70 0.78 0.74 297
Cancer 0.74 0.73 0.73 3490
Cell 0.72 0.87 0.79 1360
Cellular_component 0.00 0.00 0.00 99
Developing_anatomical_structure 0.00 0.00 0.00 11
Gene_or_gene_product 0.67 0.25 0.37 174
Immaterial_anatomical_entity 0.52 0.76 0.62 432
Multi-tissue_structure 0.83 0.59 0.69 317
Organ 0.00 0.00 0.00 49
Organism 0.71 0.48 0.57 464
Organism_subdivision 0.70 0.72 0.71 678
Organism_substance 0.00 0.00 0.00 128
Pathological_formation 0.62 0.05 0.09 108
Simple_chemical 0.00 0.00 0.00 56
Tissue 0.80 0.85 0.82 1566
micro avg 0.73 0.71 0.72 9526
macro avg 0.49 0.42 0.43 9526
weighted avg 0.71 0.71 0.70 9526
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### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
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