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PROTAC-Splitter-EncoderDecoder-lr_cosine_restarts-opt25
ailab-bio/PROTAC-Splitter-EncoderDecoder-lr_cosine_restarts-opt25
PROTAC-Splitter-EncoderDecoder-lr_cosine_restarts-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
- 9dbbe38e
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_restarts-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: 0.3086
- Poi Heavy Atoms Difference: 2.1208
- E3 Valid: 0.9896
- Poi Valid: 0.9272
- Poi Has Attachment Point(s): 0.9272
- All Ligands Equal: 0.5462
- Valid: 0.9157
- Reassembly: 0.5544
- Poi Tanimoto Similarity: 0.0
- Linker Tanimoto Similarity: 0.0
- Poi Graph Edit Distance: inf
- Linker Heavy Atoms Difference: 0.3144
- Linker Graph Edit Distance Norm: inf
- E3 Graph Edit Distance Norm: inf
- Num Fragments: 2.9998
- E3 Heavy Atoms Difference Norm: 0.0131
- Linker Valid: 0.9961
- E3 Heavy Atoms Difference: 0.5553
- E3 Tanimoto Similarity: 0.0
- Poi Heavy Atoms Difference Norm: 0.0719
- Reassembly Nostereo: 0.5796
- Linker Equal: 0.7666
- Linker Has Attachment Point(s): 0.9961
- Has All Attachment Points: 0.9836
- Poi Equal: 0.7680
- E3 Graph Edit Distance: inf
- Tanimoto Similarity: 0.0
- E3 Has Attachment Point(s): 0.9896
- Poi Graph Edit Distance Norm: inf
- E3 Equal: 0.8045
- Heavy Atoms Difference Norm: 0.0939
- Has Three Substructures: 0.9991
- Linker Graph Edit Distance: inf
- Heavy Atoms Difference: 7.0102
- Linker Heavy Atoms Difference Norm: 0.0033
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_with_restarts
- lr_scheduler_warmup_steps: 100
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Poi Heavy Atoms Difference | E3 Valid | Poi Valid | Poi Has Attachment Point(s) | All Ligands Equal | Valid | Reassembly | Poi Tanimoto Similarity | Linker Tanimoto Similarity | Poi Graph Edit Distance | Linker Heavy Atoms Difference | Linker Graph Edit Distance Norm | E3 Graph Edit Distance Norm | Num Fragments | E3 Heavy Atoms Difference Norm | Linker Valid | E3 Heavy Atoms Difference | E3 Tanimoto Similarity | Poi Heavy Atoms Difference Norm | Reassembly Nostereo | Linker Equal | Linker Has Attachment Point(s) | Has All Attachment Points | Poi Equal | E3 Graph Edit Distance | Tanimoto Similarity | E3 Has Attachment Point(s) | Poi Graph Edit Distance Norm | E3 Equal | Heavy Atoms Difference Norm | Has Three Substructures | Linker Graph Edit Distance | Heavy Atoms Difference | Linker Heavy Atoms Difference Norm |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.0156 | 0.4932 | 5000 | 0.2891 | 2.3129 | 0.9916 | 0.9252 | 0.9252 | 0.4596 | 0.9169 | 0.4665 | 0.0 | 0.0 | inf | 0.3805 | inf | inf | 3.0006 | 0.0061 | 0.9965 | 0.3913 | 0.0 | 0.0739 | 0.4911 | 0.6623 | 0.9965 | 0.9863 | 0.7265 | inf | 0.0 | 0.9916 | inf | 0.7815 | 0.0918 | 0.9988 | 35410764872521246890440289523238443113605795566260484204134400.0000 | 7.0030 | 0.0005 |
| 0.0077 | 0.7398 | 7500 | 0.3073 | 2.5750 | 0.9857 | 0.9161 | 0.9161 | 0.4898 | 0.8987 | 0.4975 | 0.0 | 0.0 | inf | 0.4483 | inf | inf | 3.0002 | 0.0088 | 0.9943 | 0.4845 | 0.0 | 0.0832 | 0.5220 | 0.7095 | 0.9943 | 0.9812 | 0.7363 | inf | 0.0 | 0.9857 | inf | 0.7908 | 0.1093 | 0.9995 | 56657223796033995024704463237181508981769272906016774726615040.0000 | 8.2839 | 0.0090 |
| 0.0046 | 0.9864 | 10000 | 0.3086 | 2.1208 | 0.9896 | 0.9272 | 0.9272 | 0.5462 | 0.9157 | 0.5544 | 0.0 | 0.0 | inf | 0.3144 | inf | inf | 2.9998 | 0.0131 | 0.9961 | 0.5553 | 0.0 | 0.0719 | 0.5796 | 0.7666 | 0.9961 | 0.9836 | 0.7680 | inf | 0.0 | 0.9896 | inf | 0.8045 | 0.0939 | 0.9991 | inf | 7.0102 | 0.0033 |
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