ailab-bio/PROTAC-Splitter-EncoderDecoder-lr_reduce-opt25-rand-smiles
083
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ailab-bio/PROTAC-Splitter-EncoderDecoder-lr_reduce-opt25-rand-smiles
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: 0.3251
- All Ligands Equal: 0.5455
- E3 Tanimoto Similarity: 0.0
- E3 Graph Edit Distance Norm: inf
- E3 Heavy Atoms Difference Norm: 0.0123
- Linker Tanimoto Similarity: 0.0
- Tanimoto Similarity: 0.0
- E3 Valid: 0.9866
- Linker Heavy Atoms Difference Norm: -0.0013
- Num Fragments: 2.9997
- Heavy Atoms Difference: 5.7446
- E3 Has Attachment Point(s): 0.9866
- E3 Equal: 0.8076
- Reassembly: 0.5548
- Poi Has Attachment Point(s): 0.9458
- Poi Graph Edit Distance Norm: inf
- Linker Graph Edit Distance: inf
- Poi Heavy Atoms Difference Norm: 0.0510
- Linker Has Attachment Point(s): 0.9952
- Poi Equal: 0.7632
- E3 Heavy Atoms Difference: 0.4690
- Has All Attachment Points: 0.9866
- Linker Graph Edit Distance Norm: inf
- Has Three Substructures: 0.9990
- Linker Equal: 0.7856
- Poi Valid: 0.9458
- Valid: 0.9308
- Poi Tanimoto Similarity: 0.0
- Reassembly Nostereo: 0.5789
- Linker Valid: 0.9952
- Heavy Atoms Difference Norm: 0.0744
- Linker Heavy Atoms Difference: 0.2002
- Poi Heavy Atoms Difference: 1.7548
- Poi Graph Edit Distance: inf
- E3 Graph Edit Distance: inf
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: 800
- training_steps: 10000
- mixedprecisiontraining: Native AMP
Training results
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
