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---
license: mit
base_model: microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext
tags:
- generated_from_trainer
model-index:
- name: BioNLP13CG_PubMedBERT_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_PubMedBERT_NER
This model is a fine-tuned version of [microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2066
- Seqeval classification report: precision recall f1-score support
Amino_acid 0.78 0.81 0.79 301
Anatomical_system 0.00 0.00 0.00 3
Cancer 0.00 0.00 0.00 37
Cell 0.79 0.85 0.82 446
Cellular_component 0.00 0.00 0.00 19
Developing_anatomical_structure 0.55 0.78 0.65 399
Gene_or_gene_product 0.68 0.41 0.51 128
Immaterial_anatomical_entity 0.00 0.00 0.00 45
Multi-tissue_structure 0.25 0.02 0.04 98
Organ 0.00 0.00 0.00 19
Organism 0.90 0.93 0.92 1108
Organism_subdivision 0.71 0.12 0.21 120
Organism_substance 0.62 0.59 0.60 128
Pathological_formation 0.00 0.00 0.00 41
Simple_chemical 0.87 0.86 0.86 4397
Tissue 0.90 0.93 0.91 1790
micro avg 0.84 0.83 0.84 9079
macro avg 0.44 0.39 0.39 9079
weighted avg 0.83 0.83 0.82 9079
## 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 | 0.3390 | precision recall f1-score support
Amino_acid 0.81 0.10 0.18 301
Anatomical_system 0.00 0.00 0.00 3
Cancer 0.00 0.00 0.00 37
Cell 0.82 0.76 0.79 446
Cellular_component 0.00 0.00 0.00 19
Developing_anatomical_structure 0.90 0.07 0.13 399
Gene_or_gene_product 0.00 0.00 0.00 128
Immaterial_anatomical_entity 0.00 0.00 0.00 45
Multi-tissue_structure 0.00 0.00 0.00 98
Organ 0.00 0.00 0.00 19
Organism 0.64 0.86 0.73 1108
Organism_subdivision 0.00 0.00 0.00 120
Organism_substance 0.00 0.00 0.00 128
Pathological_formation 0.00 0.00 0.00 41
Simple_chemical 0.83 0.79 0.81 4397
Tissue 0.74 0.91 0.82 1790
micro avg 0.77 0.71 0.74 9079
macro avg 0.30 0.22 0.22 9079
weighted avg 0.73 0.71 0.69 9079
|
| No log | 2.0 | 191 | 0.2209 | precision recall f1-score support
Amino_acid 0.76 0.75 0.76 301
Anatomical_system 0.00 0.00 0.00 3
Cancer 0.00 0.00 0.00 37
Cell 0.78 0.87 0.82 446
Cellular_component 0.00 0.00 0.00 19
Developing_anatomical_structure 0.52 0.75 0.61 399
Gene_or_gene_product 0.65 0.24 0.35 128
Immaterial_anatomical_entity 0.00 0.00 0.00 45
Multi-tissue_structure 0.00 0.00 0.00 98
Organ 0.00 0.00 0.00 19
Organism 0.89 0.92 0.91 1108
Organism_subdivision 0.50 0.05 0.09 120
Organism_substance 0.61 0.52 0.56 128
Pathological_formation 0.00 0.00 0.00 41
Simple_chemical 0.86 0.86 0.86 4397
Tissue 0.87 0.93 0.90 1790
micro avg 0.83 0.82 0.83 9079
macro avg 0.40 0.37 0.37 9079
weighted avg 0.81 0.82 0.81 9079
|
| No log | 2.98 | 285 | 0.2066 | precision recall f1-score support
Amino_acid 0.78 0.81 0.79 301
Anatomical_system 0.00 0.00 0.00 3
Cancer 0.00 0.00 0.00 37
Cell 0.79 0.85 0.82 446
Cellular_component 0.00 0.00 0.00 19
Developing_anatomical_structure 0.55 0.78 0.65 399
Gene_or_gene_product 0.68 0.41 0.51 128
Immaterial_anatomical_entity 0.00 0.00 0.00 45
Multi-tissue_structure 0.25 0.02 0.04 98
Organ 0.00 0.00 0.00 19
Organism 0.90 0.93 0.92 1108
Organism_subdivision 0.71 0.12 0.21 120
Organism_substance 0.62 0.59 0.60 128
Pathological_formation 0.00 0.00 0.00 41
Simple_chemical 0.87 0.86 0.86 4397
Tissue 0.90 0.93 0.91 1790
micro avg 0.84 0.83 0.84 9079
macro avg 0.44 0.39 0.39 9079
weighted avg 0.83 0.83 0.82 9079
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### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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