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---
base_model: dmis-lab/biobert-v1.1
tags:
- generated_from_trainer
model-index:
- name: BioNLP13CG_bioBERT_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_bioBERT_NER
This model is a fine-tuned version of [dmis-lab/biobert-v1.1](https://huggingface.co/dmis-lab/biobert-v1.1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1928
- Seqeval classification report: precision recall f1-score support
Amino_acid 0.89 0.88 0.88 576
Anatomical_system 0.96 0.82 0.89 317
Cancer 0.92 0.91 0.91 1649
Cell 0.00 0.00 0.00 25
Cellular_component 0.00 0.00 0.00 12
Developing_anatomical_structure 0.75 0.85 0.80 438
Gene_or_gene_product 0.87 0.18 0.29 74
Immaterial_anatomical_entity 0.84 0.84 0.84 4142
Multi-tissue_structure 0.85 0.84 0.84 451
Organ 0.51 0.23 0.31 80
Organism 0.52 0.66 0.58 182
Organism_subdivision 0.81 0.80 0.81 314
Organism_substance 0.73 0.66 0.69 96
Pathological_formation 0.75 0.68 0.71 262
Simple_chemical 0.55 0.44 0.49 112
Tissue 0.82 0.91 0.87 300
micro avg 0.84 0.82 0.83 9030
macro avg 0.67 0.60 0.62 9030
weighted avg 0.84 0.82 0.83 9030
## 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 | 0.2929 | precision recall f1-score support
Amino_acid 0.68 0.81 0.73 576
Anatomical_system 0.93 0.74 0.82 317
Cancer 0.89 0.89 0.89 1649
Cell 0.00 0.00 0.00 25
Cellular_component 0.00 0.00 0.00 12
Developing_anatomical_structure 0.56 0.79 0.65 438
Gene_or_gene_product 0.00 0.00 0.00 74
Immaterial_anatomical_entity 0.79 0.76 0.77 4142
Multi-tissue_structure 0.84 0.75 0.79 451
Organ 0.00 0.00 0.00 80
Organism 0.62 0.08 0.15 182
Organism_subdivision 0.64 0.78 0.70 314
Organism_substance 0.00 0.00 0.00 96
Pathological_formation 0.63 0.44 0.52 262
Simple_chemical 0.79 0.13 0.23 112
Tissue 0.82 0.45 0.58 300
micro avg 0.78 0.72 0.75 9030
macro avg 0.51 0.41 0.43 9030
weighted avg 0.76 0.72 0.73 9030
|
| No log | 2.0 | 191 | 0.2053 | precision recall f1-score support
Amino_acid 0.87 0.87 0.87 576
Anatomical_system 0.98 0.80 0.88 317
Cancer 0.89 0.92 0.91 1649
Cell 0.00 0.00 0.00 25
Cellular_component 0.00 0.00 0.00 12
Developing_anatomical_structure 0.74 0.84 0.79 438
Gene_or_gene_product 1.00 0.05 0.10 74
Immaterial_anatomical_entity 0.83 0.83 0.83 4142
Multi-tissue_structure 0.85 0.82 0.83 451
Organ 0.48 0.15 0.23 80
Organism 0.49 0.66 0.56 182
Organism_subdivision 0.79 0.80 0.80 314
Organism_substance 0.75 0.58 0.65 96
Pathological_formation 0.76 0.66 0.71 262
Simple_chemical 0.48 0.42 0.45 112
Tissue 0.80 0.90 0.85 300
micro avg 0.82 0.82 0.82 9030
macro avg 0.67 0.58 0.59 9030
weighted avg 0.82 0.82 0.81 9030
|
| No log | 2.98 | 285 | 0.1928 | precision recall f1-score support
Amino_acid 0.89 0.88 0.88 576
Anatomical_system 0.96 0.82 0.89 317
Cancer 0.92 0.91 0.91 1649
Cell 0.00 0.00 0.00 25
Cellular_component 0.00 0.00 0.00 12
Developing_anatomical_structure 0.75 0.85 0.80 438
Gene_or_gene_product 0.87 0.18 0.29 74
Immaterial_anatomical_entity 0.84 0.84 0.84 4142
Multi-tissue_structure 0.85 0.84 0.84 451
Organ 0.51 0.23 0.31 80
Organism 0.52 0.66 0.58 182
Organism_subdivision 0.81 0.80 0.81 314
Organism_substance 0.73 0.66 0.69 96
Pathological_formation 0.75 0.68 0.71 262
Simple_chemical 0.55 0.44 0.49 112
Tissue 0.82 0.91 0.87 300
micro avg 0.84 0.82 0.83 9030
macro avg 0.67 0.60 0.62 9030
weighted avg 0.84 0.82 0.83 9030
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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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