protBERTbfd_AAV2_regressor – AI Model by avuhong | AlphaNeural AI

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avuhong/
protBERTbfd_AAV2_regressor

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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protBERTbfd_AAV2_regressor

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

Loss: 0.0327
Mse: 0.0327
Rmse: 0.1808
Mae: 0.0618
R2: 0.8691
Smape: 101.2324

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: 64
eval_batch_size: 64
seed: 42
gradient_accumulation_steps: 64
total_train_batch_size: 4096
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 200
num_epochs: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Mse	Rmse	Mae	R2	Smape
No log	1.0	58	0.0985	0.0985	0.3138	0.1707	0.6057	102.5806
No log	2.0	116	0.0689	0.0689	0.2625	0.1432	0.7242	112.9846
No log	3.0	174	0.0400	0.0400	0.1999	0.0859	0.8399	102.6132
No log	4.0	232	0.0402	0.0402	0.2005	0.0745	0.8389	103.3228
No log	5.0	290	0.0337	0.0337	0.1836	0.0665	0.8650	101.0925
No log	6.0	348	0.0327	0.0327	0.1808	0.0618	0.8691	101.2324

Framework versions

Transformers 4.21.0
Pytorch 1.12.0+cu113
Datasets 2.4.0
Tokenizers 0.12.1