ailab-bio/PROTAC-Splitter-EncoderDecoder-lr_reduce-rand-smiles-train-0.5

1---2base_model: seyonec/ChemBERTa-zinc-base-v13library_name: transformers4license: mit5tags:6- PROTAC7- cheminformatics8- generated_from_trainer9model-index:10- name: ailab-bio/PROTAC-Splitter-EncoderDecoder-lr_reduce-rand-smiles-train-0.511  results: []12---13 14<!-- This model card has been generated automatically according to the information the Trainer had access to. You15should probably proofread and complete it, then remove this comment. -->16 17# ailab-bio/PROTAC-Splitter-EncoderDecoder-lr_reduce-rand-smiles-train-0.518 19This 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.20It achieves the following results on the evaluation set:21- Loss: 0.375122- Reassembly: 0.597023- E3 Graph Edit Distance Norm: inf24- Linker Graph Edit Distance Norm: inf25- All Ligands Equal: 0.589926- Poi Heavy Atoms Difference Norm: 0.041927- Poi Graph Edit Distance Norm: inf28- Linker Heavy Atoms Difference: 0.288329- Linker Equal: 0.847230- Poi Has Attachment Point(s): 0.951031- E3 Tanimoto Similarity: 0.032- Reassembly Nostereo: 0.632933- E3 Graph Edit Distance: inf34- Linker Has Attachment Point(s): 0.997735- E3 Heavy Atoms Difference Norm: 0.003736- Linker Valid: 0.997737- Poi Equal: 0.789038- Linker Graph Edit Distance: 23016997167138810478786188190104988023843767118069314732687360.000039- E3 Equal: 0.824040- Num Fragments: 3.000341- E3 Heavy Atoms Difference: 0.273742- Poi Graph Edit Distance: inf43- Has Three Substructures: 0.999644- Heavy Atoms Difference: 4.768545- Linker Tanimoto Similarity: 0.046- Poi Heavy Atoms Difference: 1.395047- E3 Valid: 0.994448- Poi Tanimoto Similarity: 0.049- Valid: 0.945050- Heavy Atoms Difference Norm: 0.063451- Tanimoto Similarity: 0.052- E3 Has Attachment Point(s): 0.994453- Has All Attachment Points: 0.993854- Poi Valid: 0.951055- Linker Heavy Atoms Difference Norm: 0.006756 57## Model description58 59More information needed60 61## Intended uses & limitations62 63More information needed64 65## Training and evaluation data66 67More information needed68 69## Training procedure70 71### Training hyperparameters72 73The following hyperparameters were used during training:74- learning_rate: 5e-0575- train_batch_size: 12876- eval_batch_size: 6477- seed: 4278- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-0879- lr_scheduler_type: reduce_lr_on_plateau80- lr_scheduler_warmup_steps: 40081- training_steps: 10000082- mixed_precision_training: Native AMP83 84### Training results85 86| Training Loss | Epoch   | Step   | Validation Loss | Reassembly | E3 Graph Edit Distance Norm | Linker Graph Edit Distance Norm | All Ligands Equal | Poi Heavy Atoms Difference Norm | Poi Graph Edit Distance Norm | Linker Heavy Atoms Difference | Linker Equal | Poi Has Attachment Point(s) | E3 Tanimoto Similarity | Reassembly Nostereo | E3 Graph Edit Distance | Linker Has Attachment Point(s) | E3 Heavy Atoms Difference Norm | Linker Valid | Poi Equal | Linker Graph Edit Distance                                          | E3 Equal | Num Fragments | E3 Heavy Atoms Difference | Poi Graph Edit Distance | Has Three Substructures | Heavy Atoms Difference | Linker Tanimoto Similarity | Poi Heavy Atoms Difference | E3 Valid | Poi Tanimoto Similarity | Valid  | Heavy Atoms Difference Norm | Tanimoto Similarity | E3 Has Attachment Point(s) | Has All Attachment Points | Poi Valid | Linker Heavy Atoms Difference Norm |87|:-------------:|:-------:|:------:|:---------------:|:----------:|:---------------------------:|:-------------------------------:|:-----------------:|:-------------------------------:|:----------------------------:|:-----------------------------:|:------------:|:---------------------------:|:----------------------:|:-------------------:|:----------------------:|:------------------------------:|:------------------------------:|:------------:|:---------:|:-------------------------------------------------------------------:|:--------:|:-------------:|:-------------------------:|:-----------------------:|:-----------------------:|:----------------------:|:--------------------------:|:--------------------------:|:--------:|:-----------------------:|:------:|:---------------------------:|:-------------------:|:--------------------------:|:-------------------------:|:---------:|:----------------------------------:|88| 0.0006        | 15.7822 | 80000  | 0.3655          | 0.5977     | inf                         | inf                             | 0.5904            | 0.0477                          | inf                          | 0.1988                        | 0.8371       | 0.9528                      | 0.0                    | 0.6278              | inf                    | 0.9952                         | 0.0221                         | 0.9952       | 0.7851    | inf                                                                 | 0.8250   | 2.9996        | 0.7440                    | inf                     | 0.9994                  | 5.9070                 | 0.0                        | 1.4796                     | 0.9796   | 0.0                     | 0.9315 | 0.0782                      | 0.0                 | 0.9796                     | 0.9879                    | 0.9528    | -0.0014                            |89| 0.0006        | 19.7278 | 100000 | 0.3751          | 0.5970     | inf                         | inf                             | 0.5899            | 0.0419                          | inf                          | 0.2883                        | 0.8472       | 0.9510                      | 0.0                    | 0.6329              | inf                    | 0.9977                         | 0.0037                         | 0.9977       | 0.7890    | 23016997167138810478786188190104988023843767118069314732687360.0000 | 0.8240   | 3.0003        | 0.2737                    | inf                     | 0.9996                  | 4.7685                 | 0.0                        | 1.3950                     | 0.9944   | 0.0                     | 0.9450 | 0.0634                      | 0.0                 | 0.9944                     | 0.9938                    | 0.9510    | 0.0067                             |90 91 92### Framework versions93 94- Transformers 4.44.295- Pytorch 2.4.1+cu12196- Datasets 3.0.097- Tokenizers 0.19.198