CLTrier ProSem
Usage
from cltrier_prosem import Pipeline
# init pipeline object (load model, data, trainer)
pipeline = Pipeline({
'encoder': {
'model': 'deepset/gbert-base', # huggingface model slug
},
'dataset': {
'path': './path/data', # path to data directory (containing train/test.parquet)
'text_column': 'text', # column containing src text
'label_column': 'label', # column containing target label
'label_classes': ['class_1', 'class_2'], # list of target classes
},
'classifier': {
'hid_size': 512, # size of classifier perceptron
'dropout': 0.2, # dropout value
},
'pooler': {
'form': 'cls',
# type of pooling, possible values:
# 'cls', 'sent_mean', 'subword_{first|last|mean|min|max}'
# if subword probing used
'span_columns': ['span']
},
'trainer': {
'num_epochs': 5, # number of training epochs
'batch_size': 32, # batch size in both training and evaluation
'learning_rate': 1e-3, # trainer learning rate
'export_path': './path/output', # output path for logging and results
},
})
# call pipeline object (training and evaluation)
pipeline()
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Release files for cltrier_prosem 0.4.3
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Source distribution (sdist)
| File | Size | Uploaded | |
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| cltrier_prosem-0.4.3.tar.gz | 2.5 MB | Details |
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| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| cltrier_prosem-0.4.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size:2.5 MB
Release files / cltrier_prosem-0.4.3.tar.gz
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| Size | 2.5 MB |
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Release files / cltrier_prosem-0.4.3-py3-none-any.whl
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|---|---|
| Size | 15.8 kB |
| Tags | Python 3 |
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