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prot_bert_bfd-disoRNA – AI Model by debbiesoon | AlphaNeural AI
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prot_bert_bfd-disoRNA
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transformers
pytorch
tensorboard
bert
token-classification
generated_from_trainer
autotrain_compatible
endpoints_compatible
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prot_bert_bfd-disoRNA
This model is a fine-tuned version of
Rostlab/prot_bert_bfd
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0634
Precision: 0.9746
Recall: 0.9872
F1: 0.9809
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: 2e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
0.0627
1.0
61
0.0665
0.9746
0.9872
0.9809
0.0186
2.0
122
0.0644
0.9746
0.9872
0.9809
0.015
3.0
183
0.0634
0.9746
0.9872
0.9809
Framework versions
Transformers 4.21.3
Pytorch 1.12.1+cu113
Datasets 2.4.0
Tokenizers 0.12.1
