ailab-bio/PROTAC-Splitter-EncoderDecoder-lr_reduce-rand-smiles-train-0.5
019
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ailab-bio/PROTAC-Splitter-EncoderDecoder-lr_reduce-rand-smiles-train-0.5
This model is a fine-tuned version of seyonec/ChemBERTa-zinc-base-v1 on the ailab-bio/PROTAC-Splitter-Dataset dataset. It achieves the following results on the evaluation set:
- Loss: 0.3751
- Reassembly: 0.5970
- E3 Graph Edit Distance Norm: inf
- Linker Graph Edit Distance Norm: inf
- All Ligands Equal: 0.5899
- Poi Heavy Atoms Difference Norm: 0.0419
- Poi Graph Edit Distance Norm: inf
- Linker Heavy Atoms Difference: 0.2883
- Linker Equal: 0.8472
- Poi Has Attachment Point(s): 0.9510
- E3 Tanimoto Similarity: 0.0
- Reassembly Nostereo: 0.6329
- E3 Graph Edit Distance: inf
- Linker Has Attachment Point(s): 0.9977
- E3 Heavy Atoms Difference Norm: 0.0037
- Linker Valid: 0.9977
- Poi Equal: 0.7890
- Linker Graph Edit Distance: 23016997167138810478786188190104988023843767118069314732687360.0000
- E3 Equal: 0.8240
- Num Fragments: 3.0003
- E3 Heavy Atoms Difference: 0.2737
- Poi Graph Edit Distance: inf
- Has Three Substructures: 0.9996
- Heavy Atoms Difference: 4.7685
- Linker Tanimoto Similarity: 0.0
- Poi Heavy Atoms Difference: 1.3950
- E3 Valid: 0.9944
- Poi Tanimoto Similarity: 0.0
- Valid: 0.9450
- Heavy Atoms Difference Norm: 0.0634
- Tanimoto Similarity: 0.0
- E3 Has Attachment Point(s): 0.9944
- Has All Attachment Points: 0.9938
- Poi Valid: 0.9510
- Linker Heavy Atoms Difference Norm: 0.0067
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
- trainbatchsize: 128
- evalbatchsize: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lrschedulertype: reducelron_plateau
- lrschedulerwarmup_steps: 400
- training_steps: 100000
- mixedprecisiontraining: Native AMP
Training results
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
