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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-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_cosine-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: 0.3986
- Poi Has Attachment Point(s): 0.9602
- Num Fragments: 3.0004
- All Ligands Equal: 0.5961
- Linker Equal: 0.8502
- Heavy Atoms Difference: 4.5700
- E3 Has Attachment Point(s): 0.9887
- Reassembly Nostereo: 0.6338
- Poi Graph Edit Distance: inf
- E3 Valid: 0.9887
- E3 Heavy Atoms Difference: 0.1957
- Poi Valid: 0.9602
- Tanimoto Similarity: 0.0
- Linker Tanimoto Similarity: 0.0
- Linker Has Attachment Point(s): 0.9970
- E3 Tanimoto Similarity: 0.0
- Poi Heavy Atoms Difference: 1.1950
- Has All Attachment Points: 0.9904
- Linker Heavy Atoms Difference: 0.1979
- Poi Equal: 0.7910
- Linker Graph Edit Distance Norm: inf
- E3 Equal: 0.8273
- Poi Graph Edit Distance Norm: inf
- Poi Tanimoto Similarity: 0.0
- E3 Heavy Atoms Difference Norm: 0.0011
- E3 Graph Edit Distance: inf
- Heavy Atoms Difference Norm: 0.0620
- Linker Heavy Atoms Difference Norm: 0.0009
- Reassembly: 0.6025
- Has Three Substructures: 0.9995
- Linker Graph Edit Distance: 30099150141643059856874246094752676646564926231321411573514240.0000
- Linker Valid: 0.9970
- Valid: 0.9474
- E3 Graph Edit Distance Norm: inf
- Poi Heavy Atoms Difference Norm: 0.0361
## 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: 100
- 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 |
|:-------------:|:------:|:------:|:-----------------:|:--------:|:----------------------:|:---------------------------:|:--------------------------:|:-------------------------:|:------------------------------:|:----------------------:|:--------:|:-------------------------:|:-----------------------:|:----------------------:|:---------------------------:|:------------:|:-------------------------------------------------------------------:|:-------------------------------:|:------------------------------:|:-----------------------------:|:----------------------------------:|:--------------------------:|:------------:|:---------------:|:-------------:|:---------:|:-----------------------:|:----------------------------:|:---------------------------:|:--------------------------:|:-------------------------------:|:-----------------------:|:---------:|:----------:|:-------------------:|:-------------------:|:------:|
| 0.012 | 0.4932 | 5000 | 0.4824 | 0.7897 | inf | inf | 0.9972 | 0.1648 | -0.0036 | 0.0 | 0.9972 | 0.9873 | 0.9995 | 4.9586 | 0.0650 | 0.6946 | 25672804532577903995569209904347871257364201785538851047997440.0000 | inf | 0.9974 | 0.5344 | 0.0103 | 0.0 | 0.9974 | 0.3055 | 3.0005 | 0.7354 | inf | inf | 0.9479 | 1.4326 | 0.0421 | 0.0 | 0.9479 | 0.4899 | 0.5198 | 0.0 | 0.9441 |
| 0.0064 | 0.7398 | 7500 | 0.5282 | 0.8017 | inf | inf | 0.9944 | 0.3429 | 0.0053 | 0.0 | 0.9944 | 0.9873 | 0.9985 | 4.5195 | 0.0593 | 0.7533 | 40722379603399433924006332951724209580646664901199556834754560.0000 | 0.0452 | 0.9959 | 0.2564 | -0.0000 | 0.0 | 0.9959 | 0.3156 | 3.0003 | 0.7551 | inf | inf | 0.9532 | 1.3395 | 0.0396 | 0.0 | 0.9532 | 0.5359 | 0.5689 | 0.0 | 0.9477 |
| 0.0051 | 0.9864 | 10000 | 0.5390 | 0.8036 | inf | inf | 0.9966 | 0.2976 | 0.0033 | 0.0 | 0.9966 | 0.9905 | 0.9992 | 4.1049 | 0.0536 | 0.7668 | 28328611898016997512352231618590754490884636453008387363307520.0000 | inf | 0.9972 | 0.3031 | 0.0034 | 0.0 | 0.9972 | 0.3184 | 3.0003 | 0.7620 | inf | inf | 0.9589 | 1.1856 | 0.0352 | 0.0 | 0.9589 | 0.5459 | 0.5799 | 0.0 | 0.9547 |
| 0.0003 | 6.9047 | 70000 | 0.3939 | 0.9555 | 3.0004 | 0.5924 | 0.8415 | 4.5431 | 0.9915 | 0.6323 | inf | 0.9915 | 0.1461 | 0.9555 | 0.0 | 0.0 | 0.9978 | 0.0 | 1.2542 | 0.9910 | 0.1698 | 0.7887 | inf | 0.8258 | inf | 0.0 | -0.0020 | inf | 0.0607 | -0.0016 | 0.5999 | 0.9996 | 22131728045325776452029795540104264829431683329922529862090752.0000| 0.9978 | 0.9464 | inf | 0.0349 |
| 0.0003 | 7.1513 | 72500 | 0.3921 | 0.9602 | 3.0002 | 0.5919 | 0.8427 | 4.5754 | 0.9887 | 0.6308 | inf | 0.9887 | 0.3155 | 0.9602 | 0.0 | 0.0 | 0.9963 | 0.0 | 1.1927 | 0.9888 | 0.2604 | 0.7898 | inf | 0.8252 | inf | 0.0 | 0.0047 | inf | 0.0611 | 0.0043 | 0.5992 | 0.9991 | 37181303116147309234962303999400365269286085344573508414341120.0000| 0.9963 | 0.9479 | inf | 0.0355 |
| 0.0003 | 7.3979 | 75000 | 0.3946 | 0.9585 | 2.9998 | 0.5922 | 0.8430 | 4.6840 | 0.9876 | 0.6307 | inf | 0.9876 | 0.2445 | 0.9585 | 0.0 | 0.0 | 0.9972 | 0.0 | 1.2902 | 0.9894 | 0.2403 | 0.7896 | inf | 0.8269 | inf | 0.0 | 0.0029 | inf | 0.0631 | 0.0042 | 0.5991 | 0.9988 | 28328611898016997512352231618590754490884636453008387363307520.0000| 0.9972 | 0.9464 | inf | 0.0394 |
| 0.0003 | 7.6445 | 77500 | 0.3915 | 0.9580 | 3.0004 | 0.5952 | 0.8483 | 4.5722 | 0.9893 | 0.6334 | inf | 0.9893 | 0.2443 | 0.9580 | 0.0 | 0.0 | 0.9977 | 0.0 | 1.2063 | 0.9888 | 0.2202 | 0.7890 | inf | 0.8266 | inf | 0.0 | 0.0019 | inf | 0.0619 | 0.0031 | 0.6016 | 0.9993 | 23016997167138810478786188190104988023843767118069314732687360.0000| 0.9977 | 0.9475 | inf | 0.0368 |
| 0.0003 | 7.8911 | 80000 | 0.3949 | 0.9589 | 3.0004 | 0.5950 | 0.8472 | 4.5701 | 0.9879 | 0.6330 | inf | 0.9879 | 0.1097 | 0.9589 | 0.0 | 0.0 | 0.9973 | 0.0 | 1.2103 | 0.9905 | 0.1845 | 0.7888 | 0.0285 | 0.8258 | inf | 0.0 | -0.0029 | inf | 0.0615 | -0.0007 | 0.6022 | 0.9989 | 26558073654390935167830217142428832335204346674695363153100800.0000| 0.9973 | 0.9466 | inf | 0.0350 |
| 0.0002 | 8.1377 | 82500 | 0.3974 | 0.9626 | 3.0002 | 0.5951 | 0.8476 | 4.1669 | 0.9908 | 0.6333 | inf | 0.9908 | 0.0201 | 0.9626 | 0.0 | 0.0 | 0.9973 | 0.0 | 1.1490 | 0.9909 | 0.1837 | 0.7907 | inf | 0.8269 | inf | 0.0 | -0.0051 | inf | 0.0565 | 0.0004 | 0.6021 | 0.9995 | inf | 0.9973 | 0.9523 | inf | 0.0342 |
| 0.0002 | 8.3843 | 85000 | 0.3964 | 0.9615 | 3.0006 | 0.5960 | 0.8492 | 4.2838 | 0.9900 | 0.6346 | inf | 0.9900 | 0.1197 | 0.9615 | 0.0 | 0.0 | 0.9971 | 0.0 | 1.1409 | 0.9894 | 0.1703 | 0.7904 | inf | 0.8274 | inf | 0.0 | -0.0009 | inf | 0.0581 | -0.0010 | 0.6024 | 0.9994 | 29213881019830025830117853444751953452152842443174626702917632.0000| 0.9971 | 0.9502 | inf | 0.0336 |
| 0.0002 | 8.6309 | 87500 | 0.3990 | 0.9604 | 3.0001 | 0.5953 | 0.8501 | 4.5262 | 0.9888 | 0.6329 | inf | 0.9888 | 0.1731 | 0.9604 | 0.0 | 0.0 | 0.9973 | 0.0 | 1.1703 | 0.9884 | 0.2064 | 0.7899 | inf | 0.8263 | inf | 0.0 | 0.0008 | inf | 0.0616 | 0.0013 | 0.6017 | 0.9996 | inf | 0.9973 | 0.9479 | inf | 0.0349 |
| 0.0002 | 8.8775 | 90000 | 0.3977 | 0.9608 | 3.0003 | 0.5956 | 0.8498 | 4.7022 | 0.9862 | 0.6330 | inf | 0.9862 | 0.2705 | 0.9608 | 0.0 | 0.0 | 0.9970 | 0.0 | 1.1535 | 0.9884 | 0.1989 | 0.7905 | 0.0278 | 0.8270 | inf | 0.0 | 0.0049 | inf | 0.0641 | 0.0014 | 0.6022 | 0.9996 | 30099150141643059856874246094752676646564926231321411573514240.0000| 0.9970 | 0.9456 | inf | 0.0346 |
| 0.0002 | 9.1241 | 92500 | 0.3981 | 0.9606 | 3.0003 | 0.5966 | 0.8514 | 4.5609 | 0.9883 | 0.6340 | inf | 0.9883 | 0.2075 | 0.9606 | 0.0 | 0.0 | 0.9968 | 0.0 | 1.1666 | 0.9898 | 0.1784 | 0.7913 | 0.0278 | 0.8275 | inf | 0.0 | 0.0023 | inf | 0.0620 | -0.0004 | 0.6030 | 0.9996 | 31869688385269122201396260570914598802245216009634435783720960.0000| 0.9968 | 0.9471 | inf | 0.0352 |
| 0.0002 | 9.3707 | 95000 | 0.3984 | 0.9596 | 3.0004 | 0.5964 | 0.8510 | 4.6478 | 0.9884 | 0.6343 | inf | 0.9884 | 0.1992 | 0.9596 | 0.0 | 0.0 | 0.9965 | 0.0 | 1.2270 | 0.9898 | 0.2018 | 0.7906 | inf | 0.8270 | inf | 0.0 | 0.0013 | inf | 0.0630 | 0.0011 | 0.6030 | 0.9995 | 34525495750708218572674667697077244152337589576094244864524288.0000| 0.9965 | 0.9464 | inf | 0.0375 |
| 0.0002 | 9.6173 | 97500 | 0.3987 | 0.9603 | 3.0004 | 0.5961 | 0.8502 | 4.5589 | 0.9888 | 0.6339 | inf | 0.9888 | 0.1958 | 0.9603 | 0.0 | 0.0 | 0.9969 | 0.0 | 1.1934 | 0.9904 | 0.1982 | 0.7909 | inf | 0.8273 | inf | 0.0 | 0.0010 | inf | 0.0619 | 0.0008 | 0.6026 | 0.9995 | 30984419263456093883630638744753399840977010019468196444110848.0000| 0.9969 | 0.9476 | inf | 0.0361 |
| 0.0002 | 9.8639 | 100000 | 0.3986 | 0.9602 | 3.0004 | 0.5961 | 0.8502 | 4.5700 | 0.9887 | 0.6338 | inf | 0.9887 | 0.1957 | 0.9602 | 0.0 | 0.0 | 0.9970 | 0.0 | 1.1950 | 0.9904 | 0.1979 | 0.7910 | inf | 0.8273 | inf | 0.0 | 0.0011 | inf | 0.0620 | 0.0009 | 0.6025 | 0.9995 | 30099150141643059856874246094752676646564926231321411573514240.0000| 0.9970 | 0.9474 | inf | 0.0361 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
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