--- 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-rand-smiles results: [] --- # ailab-bio/PROTAC-Splitter-EncoderDecoder-lr_cosine_restarts-opt25-rand-smiles 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: 0.3093 - Linker Heavy Atoms Difference: 0.3372 - Has Three Substructures: 0.9991 - Poi Valid: 0.9534 - Linker Graph Edit Distance Norm: inf - Reassembly: 0.5402 - Valid: 0.9458 - Poi Heavy Atoms Difference: 1.3755 - E3 Has Attachment Point(s): 0.9922 - Poi Heavy Atoms Difference Norm: 0.0422 - Heavy Atoms Difference: 4.5184 - Has All Attachment Points: 0.9900 - Poi Tanimoto Similarity: 0.0 - Heavy Atoms Difference Norm: 0.0596 - E3 Heavy Atoms Difference: 0.2046 - All Ligands Equal: 0.5318 - E3 Heavy Atoms Difference Norm: -0.0014 - Linker Heavy Atoms Difference Norm: 0.0044 - Tanimoto Similarity: 0.0 - E3 Graph Edit Distance Norm: inf - Poi Equal: 0.7580 - Poi Has Attachment Point(s): 0.9534 - Poi Graph Edit Distance Norm: inf - Num Fragments: 2.9998 - Linker Graph Edit Distance: inf - Linker Valid: 0.9980 - Linker Tanimoto Similarity: 0.0 - Poi Graph Edit Distance: inf - E3 Equal: 0.8017 - Linker Has Attachment Point(s): 0.9980 - Linker Equal: 0.7645 - E3 Tanimoto Similarity: 0.0 - Reassembly Nostereo: 0.5728 - E3 Valid: 0.9922 - 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 - 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 | Linker Heavy Atoms Difference | Has Three Substructures | Poi Valid | Linker Graph Edit Distance Norm | Reassembly | Valid | Poi Heavy Atoms Difference | E3 Has Attachment Point(s) | Poi Heavy Atoms Difference Norm | Heavy Atoms Difference | Has All Attachment Points | Poi Tanimoto Similarity | Heavy Atoms Difference Norm | E3 Heavy Atoms Difference | All Ligands Equal | E3 Heavy Atoms Difference Norm | Linker Heavy Atoms Difference Norm | Tanimoto Similarity | E3 Graph Edit Distance Norm | Poi Equal | Poi Has Attachment Point(s) | Poi Graph Edit Distance Norm | Num Fragments | Linker Graph Edit Distance | Linker Valid | Linker Tanimoto Similarity | Poi Graph Edit Distance | E3 Equal | Linker Has Attachment Point(s) | Linker Equal | E3 Tanimoto Similarity | Reassembly Nostereo | E3 Valid | E3 Graph Edit Distance | |:-------------:|:------:|:-----:|:---------------:|:-----------------------------:|:-----------------------:|:---------:|:-------------------------------:|:----------:|:------:|:--------------------------:|:--------------------------:|:-------------------------------:|:----------------------:|:-------------------------:|:-----------------------:|:---------------------------:|:-------------------------:|:-----------------:|:------------------------------:|:----------------------------------:|:-------------------:|:---------------------------:|:---------:|:---------------------------:|:----------------------------:|:-------------:|:-------------------------------------------------------------------:|:------------:|:--------------------------:|:-----------------------:|:--------:|:------------------------------:|:------------:|:----------------------:|:-------------------:|:--------:|:----------------------:| | 0.0212 | 0.4932 | 5000 | 0.2852 | 0.5099 | 0.9994 | 0.9528 | inf | 0.4464 | 0.9500 | 1.4706 | 0.9979 | 0.0414 | 4.6065 | 0.9903 | 0.0 | 0.0591 | 0.1237 | 0.4396 | -0.0043 | 0.0050 | 0.0 | inf | 0.7208 | 0.9528 | inf | 3.0001 | 24787535410764872823308202666266910179524056896382338942894080.0000 | 0.9975 | 0.0 | inf | 0.7734 | 0.9975 | 0.6416 | 0.0 | 0.4783 | 0.9979 | inf | | 0.011 | 0.7398 | 7500 | 0.3022 | 0.3255 | 0.9990 | 0.9389 | 0.0511 | 0.4896 | 0.9294 | 2.2561 | 0.9905 | 0.0673 | 6.6114 | 0.9858 | 0.0 | 0.0846 | 0.5439 | 0.4827 | 0.0117 | -0.0008 | 0.0 | inf | 0.7332 | 0.9389 | inf | 3.0001 | 27443342776203963485595838968590031296472552664861602492710912.0000 | 0.9973 | 0.0 | inf | 0.7827 | 0.9973 | 0.7075 | 0.0 | 0.5176 | 0.9905 | inf | | 0.007 | 0.9864 | 10000 | 0.3093 | 0.3372 | 0.9991 | 0.9534 | inf | 0.5402 | 0.9458 | 1.3755 | 0.9922 | 0.0422 | 4.5184 | 0.9900 | 0.0 | 0.0596 | 0.2046 | 0.5318 | -0.0014 | 0.0044 | 0.0 | inf | 0.7580 | 0.9534 | inf | 2.9998 | inf | 0.9980 | 0.0 | inf | 0.8017 | 0.9980 | 0.7645 | 0.0 | 0.5728 | 0.9922 | inf | ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.1+cu121 - Datasets 3.0.0 - Tokenizers 0.19.1