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avuhong/
protBERTbfd_AAV2_classification

Name: protBERTbfd_AAV2_classification
Rating: 2.5 (8 reviews)

generated_from_trainer

autotrain_compatible

endpoints_compatible

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protBERTbfd_AAV2_classification

This model is a fine-tuned version of Rostlab/prot_bert_bfd on AAV2 dataset with ~230k sequences (Bryant et al 2020).

The WT sequence (aa561-588): D E E E I R T T N P V A T E Q Y G S V S T N L Q R G N R Maximum length: 50

It achieves the following results on the evaluation set. Note:this is result of the last epoch, I think the pushed model is loaded with best checkpoint - best val_loss, I'm not so sure though :/

Loss: 0.1341
Accuracy: 0.9615
F1: 0.9627
Precision: 0.9637
Recall: 0.9618
Auroc: 0.9615

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: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 64
total_train_batch_size: 2048
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 200
num_epochs: 8
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall	Auroc
No log	1.0	116	0.2582	0.9064	0.9157	0.8564	0.9839	0.9038
No log	2.0	232	0.1447	0.9424	0.9432	0.9618	0.9252	0.9430
No log	3.0	348	0.1182	0.9542	0.9556	0.9573	0.9539	0.9542
No log	4.0	464	0.1129	0.9585	0.9602	0.9520	0.9685	0.9581
0.2162	5.0	580	0.1278	0.9553	0.9558	0.9776	0.9351	0.9561
0.2162	6.0	696	0.1139	0.9587	0.9607	0.9465	0.9752	0.9581
0.2162	7.0	812	0.1127	0.9620	0.9633	0.9614	0.9652	0.9619
0.2162	8.0	928	0.1341	0.9615	0.9627	0.9637	0.9618	0.9615

Framework versions

Transformers 4.18.0
Pytorch 1.11.0+cu113
Datasets 2.1.0
Tokenizers 0.12.1

avuhong/protBERTbfd_AAV2_classification

protBERTbfd_AAV2_classification

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

avuhong/
protBERTbfd_AAV2_classification