bert-finetuned-mutation-recognition-1 – AI Model by Salvatore | AlphaNeural AI

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Salvatore/
bert-finetuned-mutation-recognition-1

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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bert-finetuned-mutation-recognition-1

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: 0.0380
Proteinmutation F1: 0.8631
Dnamutation F1: 0.7522
Snp F1: 1.0
Precision: 0.8061
Recall: 0.8386
F1: 0.8221
Accuracy: 0.9942

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	Proteinmutation F1	Dnamutation F1	Snp F1	Precision	Recall	F1	Accuracy
No log	1.0	259	0.0273	0.8072	0.5762	0.975	0.6685	0.7580	0.7104	0.9924
0.0597	2.0	518	0.0260	0.8148	0.6864	0.9873	0.7363	0.8004	0.7670	0.9936
0.0597	3.0	777	0.0338	0.8252	0.7221	1.0	0.7857	0.7941	0.7899	0.9935
0.0046	4.0	1036	0.0299	0.8707	0.7214	0.9873	0.7773	0.8450	0.8098	0.9941
0.0046	5.0	1295	0.0353	0.9035	0.7364	0.9873	0.8130	0.8493	0.8307	0.9941
0.0014	6.0	1554	0.0361	0.8941	0.7391	0.9873	0.8093	0.8471	0.8278	0.9941
0.0014	7.0	1813	0.0367	0.8957	0.7249	1.0	0.8090	0.8365	0.8225	0.9940
0.0004	8.0	2072	0.0381	0.8714	0.7578	1.0	0.8266	0.8301	0.8284	0.9940
0.0004	9.0	2331	0.0380	0.8732	0.7550	1.0	0.8148	0.8408	0.8276	0.9942
0.0002	10.0	2590	0.0380	0.8631	0.7522	1.0	0.8061	0.8386	0.8221	0.9942

Framework versions

Transformers 4.17.0
Pytorch 1.10.2
Datasets 2.0.0
Tokenizers 0.12.1