prot_bert_classification_finetuned_no_finetune – AI Model by nepp1d0 | AlphaNeural AI

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prot_bert_classification_finetuned_no_finetune

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text-classification

generated_from_trainer

autotrain_compatible

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prot_bert_classification_finetuned_no_finetune

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

Loss: 0.6212
Accuracy: 0.6473
F1: 0.6623
Precision: 0.6201
Recall: 0.7107

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
0.6494	1.0	3332	0.6479	0.6439	0.6679	0.6116	0.7357
0.5357	2.0	6664	0.6440	0.6148	0.6459	0.5845	0.7218
0.4661	3.0	9996	0.6265	0.6283	0.6414	0.6047	0.6829
0.506	4.0	13328	0.6192	0.6439	0.6567	0.6187	0.6996
0.4204	5.0	16660	0.6122	0.6567	0.6752	0.6259	0.7330
0.6071	6.0	19992	0.6212	0.6473	0.6623	0.6201	0.7107

Framework versions

Transformers 4.18.0
Pytorch 1.11.0+cu113
Datasets 2.1.0
Tokenizers 0.12.1