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---
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: []
---

<!-- 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-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