--- 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-opt25 results: [] --- # ailab-bio/PROTAC-Splitter-EncoderDecoder-lr_cosine-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: 0.3124 - 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