aiomics / config.json
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Initial aiomics model
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{
"architecture": "FlipyFlopy",
"ml": {
"model": {
"FlipyFlopy": {
"embedsz": 256,
"head": [
16,
16,
64,
"None",
"None"
],
"units": "None",
"blocks": 9,
"filtend": 512,
"std": 0.01,
"klw": 0.0001,
"drop": 0.0
}
},
"embedding": {
"max_len": 40,
"min_charge": 1,
"max_charge": 8,
"channel_first": true,
"embedding_type": "EmbedPeptide",
"embeddings": [
"peptide",
"mods",
"charge",
"nce_singleton"
],
"nce_bins": [
0,
10,
20,
30,
40,
100
],
"ev_range": [
0,
10,
20,
30,
40,
50,
60,
70,
100
],
"peptide": {
"mods": [
"Carbamidomethyl",
"Oxidation",
"Pyro-carbamidomethyl",
"Glu->pyro-Glu",
"Gln->pyro-Glu",
"Methyl",
"Phospho",
"Acetyl",
"iTRAQ4plex",
"TMT6plex",
"Deamidated"
]
}
},
"batch_size": 100,
"transfer_learning": false,
"limit_train_batches": 1.0,
"max_epochs": 60,
"shuffle": true,
"sampler": {
"sampler_type": "LengthSampler",
"max_length": 40,
"min_length": 10,
"scale": 1.0
},
"bayesian_network": {
"bayes": false,
"sample_nbr": 3
},
"loss": {
"loss_function": "SpectrumCosineLoss",
"sqrt_intensity": true
},
"metrics": [
"SpectrumCosineMetric"
],
"valid_metrics": null,
"train_metrics": null,
"optimizer": {
"optimizer_function": "AdamW",
"lr": 0.0003
},
"output_column": "spectrum",
"precision": 32
},
"ms": {
"bin_size": 0.1,
"max_mz": 2000,
"down_shift": 0.05,
"dataloader": "TandemArrowDataset",
"datamodule": "MasskitDataModule",
"take_max": false,
"take_sqrt": false,
"columns": [
"id",
"charge",
"peptide",
"peptide_len",
"nce",
"ev",
"mod_names",
"mod_positions"
],
"dataset_columns": [
"id",
"charge",
"peptide",
"peptide_len",
"ev",
"mod_names"
]
}
}