prot_bert_classification_finetuned

This model is a fine-tuned version of nepp1d0/prot_bert-finetuned-smiles-bindingDB on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.5675
• Accuracy: 0.7299
• F1: 0.7377
• Precision: 0.6995
• Recall: 0.7803

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: 1e-06
• train_batch_size: 1
• eval_batch_size: 1
• seed: 3
• gradient_accumulation_steps: 4
• total_train_batch_size: 4
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 5
• num_epochs: 6
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.4221	1.0	3332	0.6152	0.6615	0.6711	0.6367	0.7093
0.4133	2.0	6664	0.5840	0.6845	0.6718	0.6805	0.6634
0.4293	3.0	9996	0.5727	0.7116	0.7094	0.6961	0.7232
0.3098	4.0	13328	0.5636	0.7163	0.7220	0.6904	0.7566
0.3881	5.0	16660	0.5629	0.7265	0.7377	0.6918	0.7900
0.4943	6.0	19992	0.5675	0.7299	0.7377	0.6995	0.7803

Framework versions

• Transformers 4.18.0
• Pytorch 1.11.0+cu113
• Datasets 2.1.0
• Tokenizers 0.12.1