bert-finetuned-mutation-recognition-3 – AI Model by Salvatore | AlphaNeural AI

You can deploy this model and start earning money today!

Salvatore/
bert-finetuned-mutation-recognition-3

like

0

token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

Views

No views yet

bert-finetuned-mutation-recognition-3

This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0727
Dnamutation F1: 0.6484
Proteinmutation F1: 0.8571
Snp F1: 1.0
Precision: 0.7966
Recall: 0.7625
F1: 0.7792
Accuracy: 0.9872

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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Dnamutation F1	Proteinmutation F1	Snp F1	Precision	Recall	F1	Accuracy
No log	1.0	324	0.0323	0.5996	0.7886	1.0	0.6583	0.7982	0.7215	0.9901
0.0788	2.0	648	0.0314	0.6765	0.8783	1.0	0.7453	0.8571	0.7973	0.9907
0.0788	3.0	972	0.0306	0.6391	0.8679	1.0	0.7341	0.8232	0.7761	0.9903
0.0273	4.0	1296	0.0424	0.6360	0.8714	1.0	0.7792	0.775	0.7771	0.9885
0.0178	5.0	1620	0.0462	0.5885	0.8683	1.0	0.7576	0.7589	0.7583	0.9869
0.0178	6.0	1944	0.0531	0.6176	0.8701	1.0	0.7734	0.7679	0.7706	0.9873
0.0165	7.0	2268	0.0573	0.6597	0.8658	1.0	0.8022	0.775	0.7884	0.9881
0.0144	8.0	2592	0.0636	0.6596	0.8454	1.0	0.7919	0.7679	0.7797	0.9871
0.0144	9.0	2916	0.0710	0.6568	0.8748	1.0	0.8159	0.7679	0.7912	0.9872
0.0108	10.0	3240	0.0727	0.6484	0.8571	1.0	0.7966	0.7625	0.7792	0.9872

Framework versions

Transformers 4.17.0
Pytorch 1.10.2
Datasets 2.0.0
Tokenizers 0.12.1