2026-02-01_CAFA6_classification_Rostlab_prot_bert_v1

This model is a fine-tuned version of Rostlab/prot_bert on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0017

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: 0.0001
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.05
• num_epochs: 10
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
0.0016	1.0	172	0.0016
0.0016	2.0	344	0.0016
0.0016	3.0	516	0.0016
0.0016	4.0	688	0.0017
0.0016	5.0	860	0.0017
0.0016	6.0	1032	0.0017
0.0016	7.0	1204	0.0017
0.0016	8.0	1376	0.0017
0.0016	9.0	1548	0.0017
0.0016	10.0	1720	0.0017

Framework versions

• Transformers 4.57.6
• Pytorch 2.9.0+cu126
• Datasets 4.0.0
• Tokenizers 0.22.2