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BioLinkBERT-base – AI Model by zonghaoyang | AlphaNeural AI
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zonghaoyang
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BioLinkBERT-base
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transformers
pytorch
tensorboard
bert
text-classification
generated_from_trainer
apache-2.0
autotrain_compatible
endpoints_compatible
us
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BioLinkBERT-base
This model is a fine-tuned version of
michiyasunaga/BioLinkBERT-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.3937
Accuracy: 0.9025
F1: 0.6107
Precision: 0.6765
Recall: 0.5565
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
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
Accuracy
F1
Precision
Recall
0.2363
1.0
1626
0.2699
0.9057
0.5991
0.7205
0.5127
0.1832
2.0
3252
0.3328
0.9038
0.6233
0.675
0.5789
0.1324
3.0
4878
0.3937
0.9025
0.6107
0.6765
0.5565
Framework versions
Transformers 4.29.2
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3
