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PROTAC-Splitter-EncoderDecoder-lr_cosine-opt25
ailab-bio/PROTAC-Splitter-EncoderDecoder-lr_cosine-opt25
PROTAC-Splitter-EncoderDecoder-lr_cosine-opt25 is a machine learning model from ailab-bio. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- mit
- Model type
- encoder-decoder
- Access
- Public
- Created
- Mar 4, 2025
- Updated
- Mar 8, 2025
- SHA
- d0967972
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
ailab-bio/PROTAC-Splitter-EncoderDecoder-lr_cosine-opt25
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: 0.3124
- E3 Graph Edit Distance Norm: inf
- Poi Has Attachment Point(s): 0.9294
- Linker Heavy Atoms Difference: 0.3252
- Reassembly Nostereo: 0.5845
- E3 Valid: 0.9942
- Poi Heavy Atoms Difference Norm: 0.0668
- Linker Graph Edit Distance: inf
- All Ligands Equal: 0.5477
- Has All Attachment Points: 0.9857
- Linker Valid: 0.9951
- E3 Tanimoto Similarity: 0.0
- Heavy Atoms Difference: 6.4929
- Tanimoto Similarity: 0.0
- Reassembly: 0.5549
- E3 Heavy Atoms Difference: 0.3628
- Poi Graph Edit Distance Norm: inf
- Valid: 0.9232
- Linker Tanimoto Similarity: 0.0
- Linker Heavy Atoms Difference Norm: 0.0050
- Poi Valid: 0.9294
- Linker Graph Edit Distance Norm: inf
- Poi Equal: 0.7673
- Linker Equal: 0.7726
- E3 Graph Edit Distance: inf
- Poi Graph Edit Distance: inf
- Has Three Substructures: 0.9983
- Poi Heavy Atoms Difference: 2.0849
- Num Fragments: 3.0008
- Poi Tanimoto Similarity: 0.0
- E3 Heavy Atoms Difference Norm: 0.0044
- E3 Has Attachment Point(s): 0.9942
- E3 Equal: 0.8035
- Linker Has Attachment Point(s): 0.9951
- Heavy Atoms Difference Norm: 0.0854
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: 128
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 699
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | E3 Graph Edit Distance Norm | Poi Has Attachment Point(s) | Linker Heavy Atoms Difference | Reassembly Nostereo | E3 Valid | Poi Heavy Atoms Difference Norm | Linker Graph Edit Distance | All Ligands Equal | Has All Attachment Points | Linker Valid | E3 Tanimoto Similarity | Heavy Atoms Difference | Tanimoto Similarity | Reassembly | E3 Heavy Atoms Difference | Poi Graph Edit Distance Norm | Valid | Linker Tanimoto Similarity | Linker Heavy Atoms Difference Norm | Poi Valid | Linker Graph Edit Distance Norm | Poi Equal | Linker Equal | E3 Graph Edit Distance | Poi Graph Edit Distance | Has Three Substructures | Poi Heavy Atoms Difference | Num Fragments | Poi Tanimoto Similarity | E3 Heavy Atoms Difference Norm | E3 Has Attachment Point(s) | E3 Equal | Linker Has Attachment Point(s) | Heavy Atoms Difference Norm |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.0086 | 0.4932 | 5000 | 0.2931 | inf | 0.9248 | 0.6527 | 0.5238 | 0.9949 | 0.0785 | 46033994334277620957572376380209976047687534236138629465374720.0000 | 0.4899 | 0.9820 | 0.9954 | 0.0 | 7.4350 | 0.0 | 0.4972 | 0.3592 | inf | 0.9182 | 0.0 | 0.0200 | 0.9248 | 0.0544 | 0.7416 | 0.7092 | inf | inf | 0.9988 | 2.4199 | 3.0004 | 0.0 | 0.0041 | 0.9949 | 0.7832 | 0.9954 | 0.0974 |
| 0.004 | 0.7398 | 7500 | 0.3098 | inf | 0.9225 | 0.2498 | 0.5729 | 0.9924 | 0.0709 | 59313031161473097104973641187183678565005524270457129338404864.0000 | 0.5381 | 0.9818 | 0.9941 | 0.0 | 6.9868 | 0.0 | 0.5451 | 0.4005 | inf | 0.9147 | 0.0 | -0.0010 | 0.9225 | inf | 0.7603 | 0.7604 | inf | inf | 0.9978 | 2.2024 | 3.0006 | 0.0 | 0.0081 | 0.9924 | 0.8044 | 0.9941 | 0.0924 |
| 0.003 | 0.9864 | 10000 | 0.3124 | inf | 0.9294 | 0.3252 | 0.5845 | 0.9942 | 0.0668 | inf | 0.5477 | 0.9857 | 0.9951 | 0.0 | 6.4929 | 0.0 | 0.5549 | 0.3628 | inf | 0.9232 | 0.0 | 0.0050 | 0.9294 | inf | 0.7673 | 0.7726 | inf | inf | 0.9983 | 2.0849 | 3.0008 | 0.0 | 0.0044 | 0.9942 | 0.8035 | 0.9951 | 0.0854 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
- Library
- transformers
- Type
- encoder-decoder
- License
- mit
- Created
- Mar 4, 2025
- Updated
- Mar 8, 2025