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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_reduce-rand-smiles
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_reduce-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: 0.3692
- All Ligands Equal: 0.6035
- E3 Valid: 0.9927
- Linker Has Attachment Point(s): 0.9984
- E3 Graph Edit Distance: inf
- Poi Valid: 0.9629
- Reassembly: 0.6101
- E3 Has Attachment Point(s): 0.9927
- E3 Tanimoto Similarity: 0.0
- Poi Heavy Atoms Difference: 1.0907
- Linker Graph Edit Distance Norm: inf
- Heavy Atoms Difference: 4.2504
- E3 Heavy Atoms Difference Norm: 0.0208
- Has All Attachment Points: 0.9934
- Linker Heavy Atoms Difference: 0.1354
- Poi Equal: 0.7987
- Poi Graph Edit Distance: inf
- Tanimoto Similarity: 0.0
- Num Fragments: 2.9997
- Poi Heavy Atoms Difference Norm: 0.0332
- Poi Graph Edit Distance Norm: inf
- Valid: 0.9550
- Reassembly Nostereo: 0.6440
- Linker Graph Edit Distance: 15934844192634561100698130285457299401122608004817217891860480.0000
- E3 Equal: 0.8303
- Linker Heavy Atoms Difference Norm: -0.0025
- Poi Tanimoto Similarity: 0.0
- Linker Tanimoto Similarity: 0.0
- E3 Graph Edit Distance Norm: inf
- Linker Valid: 0.9984
- E3 Heavy Atoms Difference: 0.6159
- Linker Equal: 0.8640
- Poi Has Attachment Point(s): 0.9629
- Heavy Atoms Difference Norm: 0.0571
- Has Three Substructures: 0.9997
## 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: reduce_lr_on_plateau
- lr_scheduler_warmup_steps: 400
- training_steps: 100000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | All Ligands Equal | E3 Equal | E3 Graph Edit Distance | E3 Graph Edit Distance Norm | E3 Has Attachment Point(s) | E3 Heavy Atoms Difference | E3 Heavy Atoms Difference Norm | E3 Tanimoto Similarity | E3 Valid | Has All Attachment Points | Has Three Substructures | Heavy Atoms Difference | Heavy Atoms Difference Norm | Linker Equal | Linker Graph Edit Distance | Linker Graph Edit Distance Norm | Linker Has Attachment Point(s) | Linker Heavy Atoms Difference | Linker Heavy Atoms Difference Norm | Linker Tanimoto Similarity | Linker Valid | Validation Loss | Num Fragments | Poi Equal | Poi Graph Edit Distance | Poi Graph Edit Distance Norm | Poi Has Attachment Point(s) | Poi Heavy Atoms Difference | Poi Heavy Atoms Difference Norm | Poi Tanimoto Similarity | Poi Valid | Reassembly | Reassembly Nostereo | Tanimoto Similarity | Valid |
|:-------------:|:------:|:------:|:-----------------:|:--------:|:----------------------:|:---------------------------:|:--------------------------:|:-------------------------:|:------------------------------:|:----------------------:|:--------:|:-------------------------:|:-----------------------:|:----------------------:|:---------------------------:|:------------:|:-------------------------------------------------------------------:|:-------------------------------:|:------------------------------:|:-----------------------------:|:----------------------------------:|:--------------------------:|:------------:|:---------------:|:-------------:|:---------:|:--------------------------------------------------------------------:|:----------------------------:|:---------------------------:|:--------------------------:|:-------------------------------:|:-----------------------:|:---------:|:----------:|:-------------------:|:-------------------:|:------:|
| 0.0107 | 0.4932 | 5000 | 0.5011 | 0.7894 | inf | inf | 0.9859 | 0.4474 | 0.0105 | 0.0 | 0.9859 | 0.9880 | 0.9993 | 4.6779 | 0.0617 | 0.7242 | inf | inf | 0.9978 | 0.5834 | 0.0173 | 0.0 | 0.9978 | 0.3008 | 3.0002 | 0.7466 | inf | inf | 0.9624 | 1.1262 | 0.0317 | 0.0 | 0.9624 | 0.5097 | 0.5343 | 0.0 | 0.9481 |
| 0.0058 | 0.7398 | 7500 | 0.5325 | 0.8015 | inf | inf | 0.9835 | 0.6172 | 0.0172 | 0.0 | 0.9835 | 0.9898 | 0.9992 | 4.7889 | 0.0626 | 0.7643 | 59313031161473085686992099539504630098717768674496038276431872.0000 | inf | 0.9941 | 0.2995 | 0.0039 | 0.0 | 0.9941 | 0.3187 | 2.9999 | 0.7586 | inf | inf | 0.9616 | 0.9886 | 0.0264 | 0.0 | 0.9616 | 0.5402 | 0.5643 | 0.0 | 0.9417 |
| 0.0049 | 0.9864 | 10000 | 0.5455 | 0.8076 | inf | inf | 0.9866 | 0.4690 | 0.0123 | 0.0 | 0.9866 | 0.9866 | 0.9990 | 5.7446 | 0.0744 | 0.7856 | inf | inf | 0.9952 | 0.2002 | -0.0013 | 0.0 | 0.9952 | 0.3251 | 2.9997 | 0.7632 | inf | inf | 0.9458 | 1.7548 | 0.0510 | 0.0 | 0.9458 | 0.5548 | 0.5789 | 0.0 | 0.9308 |
| 0.0007 | 6.9047 | 70000 | 0.3657 | 0.5933 | 0.9918 | 0.9974 | inf | 0.9509 | 0.6012 | 0.9918 | 0.0 | 1.4603 | inf | 5.0341 | 0.0084 | 0.9904 | 0.1724 | 0.7852 | inf | 0.0 | 2.9999 | 0.0467 | inf | 0.9408 | 0.6375 | 25672804532577903995569209904347871257364201785538851047997440.0000| 0.8272 | 0.0013 | 0.0 | 0.0 | inf | 0.9974 | 0.4047 | 0.8478 | 0.9509 | 0.0678 | 0.9999 |
| 0.0006 | 7.1513 | 72500 | 0.3683 | 0.5906 | 0.9896 | 0.9978 | inf | 0.9499 | 0.5974 | 0.9896 | 0.0 | 1.4326 | inf | 5.1042 | 0.0098 | 0.9856 | 0.1323 | 0.7870 | inf | 0.0 | 3.0001 | 0.0473 | inf | 0.9390 | 0.6340 | inf | 0.8245 | -0.0034 | 0.0 | 0.0 | inf | 0.9978 | 0.4132 | 0.8443 | 0.9499 | 0.0684 | 0.9999 |
| 0.0006 | 7.3979 | 75000 | 0.3680 | 0.5893 | 0.9945 | 0.9958 | inf | 0.9505 | 0.5966 | 0.9945 | 0.0 | 1.3942 | inf | 4.8410 | 0.0119 | 0.9904 | 0.2242 | 0.7831 | inf | 0.0 | 2.9993 | 0.0443 | inf | 0.9429 | 0.6321 | inf | 0.8291 | 0.0022 | 0.0 | 0.0 | inf | 0.9958 | 0.3916 | 0.8384 | 0.9505 | 0.0649 | 0.9993 |
| 0.0006 | 7.6445 | 77500 | 0.3600 | 0.5914 | 0.9844 | 0.9988 | inf | 0.9499 | 0.5994 | 0.9844 | 0.0 | 1.5098 | 0.0298 | 5.7886 | 0.0231 | 0.9919 | 0.2759 | 0.7857 | inf | 0.0 | 3.0 | 0.0486 | inf | 0.9340 | 0.6316 | 12393767705382436411654101333133455089762028448191169471447040.0000| 0.8292 | 0.0055 | 0.0 | 0.0 | inf | 0.9988 | 0.6907 | 0.8437 | 0.9499 | 0.0776 | 1.0 |
| 0.0006 | 7.8911 | 80000 | 0.3442 | 0.5889 | 0.9830 | 0.9964 | inf | 0.9527 | 0.5960 | 0.9830 | 0.0 | 1.4641 | 0.0292 | 5.3543 | 0.0158 | 0.9889 | 0.2057 | 0.7866 | 472733711048158617442424011016035594400917981819674736470261760.0000| 0.0 | 2.9997 | 0.0450 | inf | 0.9352 | 0.6297 | 36296033994334280917196682173239166308017879354407269074731008.0000| 0.8214 | 0.0011 | 0.0 | 0.0 | inf | 0.9964 | 0.5424 | 0.8451 | 0.9527 | 0.0723 | 0.9996 |
| 0.0006 | 8.1377 | 82500 | 0.3475 | 0.5930 | 0.9927 | 0.9975 | inf | 0.9552 | 0.6004 | 0.9927 | 0.0 | 1.4236 | inf | 4.7973 | 0.0125 | 0.9905 | 0.2185 | 0.7876 | inf | 0.0 | 3.0 | 0.0429 | inf | 0.9459 | 0.6358 | inf | 0.8276 | 0.0033 | 0.0 | 0.0 | inf | 0.9975 | 0.4410 | 0.8479 | 0.9552 | 0.0636 | 1.0 |
| 0.0006 | 8.3843 | 85000 | 0.3691 | 0.5923 | 0.9934 | 0.9977 | inf | 0.9467 | 0.5998 | 0.9934 | 0.0 | 1.4565 | 0.0290 | 5.2051 | 0.0106 | 0.9875 | 0.2453 | 0.7859 | inf | 0.0 | 3.0001 | 0.0449 | inf | 0.9383 | 0.6351 | 23016997167138810478786188190104988023843767118069314732687360.0000| 0.8279 | 0.0043 | 0.0 | 0.0 | inf | 0.9977 | 0.4311 | 0.8380 | 0.9467 | 0.0692 | 0.9999 |
| 0.001 | 8.6309 | 87500 | 0.3526 | 0.5934 | 0.9881 | 0.9972 | inf | 0.9449 | 0.6006 | 0.9881 | 0.0 | 1.7053 | inf | 5.8499 | 0.0174 | 0.9930 | 0.2047 | 0.7833 | inf | 0.0 | 2.9997 | 0.0520 | inf | 0.9324 | 0.6352 | 28328611898016991803361460794751230257740758655027841832321024.0000| 0.8293 | -0.0009 | 0.0 | 0.0 | inf | 0.9972 | 0.6076 | 0.8429 | 0.9449 | 0.0772 | 0.9997 |
| 0.0011 | 8.8775 | 90000 | 0.3572 | 0.5955 | 0.9827 | 0.9969 | inf | 0.9503 | 0.6022 | 0.9827 | 0.0 | 1.5165 | inf | 5.9425 | 0.0283 | 0.9924 | 0.2921 | 0.7941 | inf | 0.0 | 2.9996 | 0.0475 | inf | 0.9310 | 0.6323 | 30984419263456093883630638744753399840977010019468196444110848.0000| 0.8275 | 0.0069 | 0.0 | 0.0 | inf | 0.9969 | 0.7812 | 0.8484 | 0.9503 | 0.0805 | 0.9996 |
| 0.0003 | 9.1241 | 92500 | 0.3578 | 0.6011 | 0.9813 | 0.9979 | inf | 0.9595 | 0.6080 | 0.9813 | 0.0 | 1.2296 | inf | 5.2612 | 0.0331 | 0.9928 | 0.1763 | 0.7982 | inf | 0.0 | 2.9998 | 0.0392 | inf | 0.9396 | 0.6372 | inf | 0.8302 | 0.0002 | 0.0 | 0.0 | inf | 0.9979 | 0.8631 | 0.8592 | 0.9595 | 0.0723 | 0.9996 |
| 0.0003 | 9.3707 | 95000 | 0.3646 | 0.6000 | 0.9880 | 0.9979 | inf | 0.9614 | 0.6070 | 0.9880 | 0.0 | 1.1567 | 0.0261 | 4.6484 | 0.0210 | 0.9926 | 0.1959 | 0.7989 | inf | 0.0 | 2.9997 | 0.0352 | inf | 0.9479 | 0.6393 | 21246458923512748134264173713943065868163477339756290522480640.0000| 0.8310 | 0.0018 | 0.0 | 0.0 | inf | 0.9979 | 0.6215 | 0.8579 | 0.9614 | 0.0627 | 0.9997 |
| 0.0003 | 9.6173 | 97500 | 0.3708 | 0.6024 | 0.9886 | 0.9982 | inf | 0.9598 | 0.6090 | 0.9886 | 0.0 | 1.1906 | inf | 4.7226 | 0.0237 | 0.9923 | 0.1565 | 0.7978 | inf | 0.0 | 2.9996 | 0.0370 | inf | 0.9478 | 0.6402 | 17705382436260623445220144761619221556802897783130242102067200.0000| 0.8306 | -0.0017 | 0.0 | 0.0 | inf | 0.9982 | 0.6769 | 0.8600 | 0.9598 | 0.0640 | 0.9996 |
| 0.0003 | 9.8639 | 100000 | 0.3692 | 0.6035 | 0.9927 | 0.9984 | inf | 0.9629 | 0.6101 | 0.9927 | 0.0 | 1.0907 | inf | 4.2504 | 0.0208 | 0.9934 | 0.1354 | 0.7987 | inf | 0.0 | 2.9997 | 0.0332 | inf | 0.9550 | 0.6440 | 15934844192634561100698130285457299401122608004817217891860480.0000| 0.8303 | -0.0025 | 0.0 | 0.0 | inf | 0.9984 | 0.6159 | 0.8640 | 0.9629 | 0.0571 | 0.9997 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
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