This model is a fine-tuned version of michiyasunaga/BioLinkBERT-large on the source_data dataset. It achieves the following results on the evaluation set:

Loss: 0.1324
Accuracy Score: 0.9585
Precision: 0.8224
Recall: 0.8583
F1: 0.8400

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: 5e-05
train_batch_size: 16
eval_batch_size: 64
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Use adafactor and the args are: No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 2.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy Score	Precision	Recall	F1
0.1047	0.9994	863	0.1295	0.9563	0.8179	0.8437	0.8306
0.0747	1.9988	1726	0.1324	0.9585	0.8224	0.8583	0.8400

Framework versions

Transformers 4.46.3
Pytorch 1.13.1+cu117
Datasets 3.1.0
Tokenizers 0.20.3

EMBO/SourceData_NER_v1_0_0_BioLinkBERT_large

SourceData_NER_v1_0_0_BioLinkBERT_large

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

EMBO/
SourceData_NER_v1_0_0_BioLinkBERT_large