--- base_model: seyonec/ChemBERTa-zinc-base-v1 library_name: transformers license: mit tags: - PROTAC - cheminformatics - generated_from_trainer model-index: - name: ailab-bio/PROTAC-Splitter-EncoderDecoder-lr_cosine_restarts-opt25 results: [] --- # ailab-bio/PROTAC-Splitter-EncoderDecoder-lr_cosine_restarts-opt25 This model is a fine-tuned version of [seyonec/ChemBERTa-zinc-base-v1](https://huggingface.co/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