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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-train-0.25
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-train-0.25
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: 0.3624
- Linker Equal: 0.8351
- E3 Graph Edit Distance Norm: inf
- Poi Heavy Atoms Difference Norm: 0.0311
- Poi Has Attachment Point(s): 0.9593
- Poi Graph Edit Distance Norm: inf
- Valid: 0.9367
- Poi Valid: 0.9593
- Poi Graph Edit Distance: inf
- Reassembly Nostereo: 0.6220
- Linker Has Attachment Point(s): 0.9970
- Poi Heavy Atoms Difference: 1.1101
- Has Three Substructures: 1.0
- E3 Heavy Atoms Difference Norm: 0.0153
- Linker Valid: 0.9970
- Linker Tanimoto Similarity: 0.0
- E3 Has Attachment Point(s): 0.9798
- Poi Equal: 0.7936
- All Ligands Equal: 0.5870
- Heavy Atoms Difference Norm: 0.0731
- Linker Heavy Atoms Difference Norm: 0.0030
- Heavy Atoms Difference: 5.4708
- Tanimoto Similarity: 0.0
- Num Fragments: 3.0
- E3 Graph Edit Distance: inf
- Linker Graph Edit Distance: inf
- Linker Heavy Atoms Difference: 0.2800
- Poi Tanimoto Similarity: 0.0
- Linker Graph Edit Distance Norm: inf
- Has All Attachment Points: 0.9888
- E3 Tanimoto Similarity: 0.0
- Reassembly: 0.5944
- E3 Heavy Atoms Difference: 0.4994
- E3 Equal: 0.8276
- E3 Valid: 0.9798
## 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 | Validation Loss | Linker Equal | E3 Graph Edit Distance Norm | Poi Heavy Atoms Difference Norm | Poi Has Attachment Point(s) | Poi Graph Edit Distance Norm | Valid | Poi Valid | Poi Graph Edit Distance | Reassembly Nostereo | Linker Has Attachment Point(s) | Poi Heavy Atoms Difference | Has Three Substructures | E3 Heavy Atoms Difference Norm | Linker Valid | Linker Tanimoto Similarity | E3 Has Attachment Point(s) | Poi Equal | All Ligands Equal | Heavy Atoms Difference Norm | Linker Heavy Atoms Difference Norm | Heavy Atoms Difference | Tanimoto Similarity | Num Fragments | E3 Graph Edit Distance | Linker Graph Edit Distance | Linker Heavy Atoms Difference | Poi Tanimoto Similarity | Linker Graph Edit Distance Norm | Has All Attachment Points | E3 Tanimoto Similarity | Reassembly | E3 Heavy Atoms Difference | E3 Equal | E3 Valid |
|:-------------:|:-------:|:------:|:---------------:|:------------:|:---------------------------:|:-------------------------------:|:---------------------------:|:----------------------------:|:------:|:---------:|:-----------------------:|:-------------------:|:------------------------------:|:--------------------------:|:-----------------------:|:------------------------------:|:------------:|:--------------------------:|:--------------------------:|:---------:|:-----------------:|:---------------------------:|:----------------------------------:|:----------------------:|:-------------------:|:-------------:|:----------------------:|:--------------------------:|:-----------------------------:|:-----------------------:|:-------------------------------:|:-------------------------:|:----------------------:|:----------:|:-------------------------:|:--------:|:--------:|
| 0.0006 | 31.5582 | 80000 | 0.3577 | 0.8324 | inf | 0.0305 | 0.9579 | inf | 0.9328 | 0.9579 | inf | 0.6230 | 0.9967 | 1.0626 | 0.9999 | 0.0251 | 0.9967 | 0.0 | 0.9771 | 0.7863 | 0.5856 | 0.0758 | 0.0051 | 5.7523 | 0.0 | 3.0001 | inf | inf | 0.2647 | 0.0 | inf | 0.9890 | 0.0 | 0.5934 | 0.8042 | 0.8272 | 0.9771 |
| 0.0005 | 39.4477 | 100000 | 0.3624 | 0.8351 | inf | 0.0311 | 0.9593 | inf | 0.9367 | 0.9593 | inf | 0.6220 | 0.9970 | 1.1101 | 1.0 | 0.0153 | 0.9970 | 0.0 | 0.9798 | 0.7936 | 0.5870 | 0.0731 | 0.0030 | 5.4708 | 0.0 | 3.0 | inf | inf | 0.2800 | 0.0 | inf | 0.9888 | 0.0 | 0.5944 | 0.4994 | 0.8276 | 0.9798 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
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