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title: "Citations of ECFR Banking Regulation in a spaCy pipeline." |
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description: "Custom text classification project for spaCy v3 adapted from the spaCy v3" |
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vars: |
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lang: "en" |
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train: corpus/train.spacy |
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dev: corpus/dev.spacy |
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version: "0.1.0" |
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gpu_id: -1 |
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vectors_model: "en_core_web_lg" |
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name: ecfr_ner |
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prodigy: |
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ner_labels: ecfr_initial_ner |
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ner_manual_labels: ecfr_manual_ner |
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senter_labels: ecfr_labeled_sents |
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ner_labeled_dataset: ecfr_labeled_ner |
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assets: |
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ner_labels: assets/ecfr_ner_labels.jsonl |
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senter_labels: assets/ecfr_senter_labels.jsonl |
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ner_patterns: assets/patterns.jsonl |
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corpus_labels: corpus/labels |
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data_files: data |
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trained_model: my_trained_model |
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trained_model_textcat: my_trained_model/textcat_multilabel |
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output_models: output |
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python_code: python_Code |
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directories: ["corpus/labels", "data", "my_trained_model/textcat_multilabel", "my_trained_model/vocab", "output/experiment1/model-best/textcat_multilabel", "output/experiment1/model-best/vocab", "output/experiment1/model-last/textcat_multilabel", "output/experiment1/model-last/vocab", "output/experiment3/model-best/textcat_multilabel", "output/experiment3/model-best/vocab", "output/experiment3/model-last/textcat_multilabel", "output/experiment3/model-last/vocab", "python_Code"] |
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assets: |
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- dest: "corpus/labels/ner.json" |
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description: "JSON file containing NER labels" |
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- dest: "corpus/labels/parser.json" |
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description: "JSON file containing parser labels" |
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- dest: "corpus/labels/tagger.json" |
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description: "JSON file containing tagger labels" |
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- dest: "corpus/labels/textcat_multilabel.json" |
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description: "JSON file containing multilabel text classification labels" |
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- dest: "data/eval.jsonl" |
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description: "JSONL file containing evaluation data" |
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- dest: "data/firstStep_file.jsonl" |
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description: "JSONL file containing formatted data from the first step" |
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- dest: "data/five_examples_annotated5.jsonl" |
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description: "JSONL file containing five annotated examples" |
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- dest: "data/goldenEval.jsonl" |
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description: "JSONL file containing golden evaluation data" |
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- dest: "data/thirdStep_file.jsonl" |
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description: "JSONL file containing classified data from the third step" |
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- dest: "data/train.jsonl" |
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description: "JSONL file containing training data" |
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- dest: "data/train200.jsonl" |
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description: "JSONL file containing initial training data" |
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- dest: "data/train4465.jsonl" |
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description: "JSONL file containing formatted and labeled training data" |
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- dest: "my_trained_model/textcat_multilabel/cfg" |
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description: "Configuration files for the text classification model" |
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- dest: "my_trained_model/textcat_multilabel/model" |
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description: "Trained model files for the text classification model" |
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- dest: "my_trained_model/vocab/key2row" |
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description: "Mapping from keys to row indices in the vocabulary" |
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- dest: "my_trained_model/vocab/lookups.bin" |
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description: "Binary lookups file for the vocabulary" |
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- dest: "my_trained_model/vocab/strings.json" |
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description: "JSON file containing string representations of the vocabulary" |
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- dest: "my_trained_model/vocab/vectors" |
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description: "Directory containing vector files for the vocabulary" |
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- dest: "my_trained_model/vocab/vectors.cfg" |
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description: "Configuration file for vectors in the vocabulary" |
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- dest: "my_trained_model/config.cfg" |
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description: "Configuration file for the trained model" |
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- dest: "my_trained_model/meta.json" |
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description: "JSON file containing metadata for the trained model" |
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- dest: "my_trained_model/tokenizer" |
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description: "Tokenizer files for the trained model" |
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- dest: "output/experiment1/model-best/textcat_multilabel/cfg" |
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description: "Configuration files for the best model in experiment 1" |
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- dest: "output/experiment1/model-best/textcat_multilabel/model" |
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description: "Trained model files for the best model in experiment 1" |
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- dest: "output/experiment1/model-best/vocab/key2row" |
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description: "Mapping from keys to row indices in the vocabulary for the best model in experiment 1" |
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- dest: "output/experiment1/model-best/vocab/lookups.bin" |
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description: "Binary lookups file for the vocabulary for the best model in experiment 1" |
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- dest: "output/experiment1/model-best/vocab/strings.json" |
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description: "JSON file containing string representations of the vocabulary for the best model in experiment 1" |
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- dest: "output/experiment1/model-best/vocab/vectors" |
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description: "Directory containing vector files for the vocabulary for the best model in experiment 1" |
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- dest: "output/experiment1/model-best/vocab/vectors.cfg" |
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description: "Configuration file for vectors in the vocabulary for the best model in experiment 1" |
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- dest: "output/experiment1/model-best/config.cfg" |
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description: "Configuration file for the best model in experiment 1" |
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- dest: "output/experiment1/model-best/meta.json" |
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description: "JSON file containing metadata for the best model in experiment 1" |
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- dest: "output/experiment1/model-best/tokenizer" |
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description: "Tokenizer files for the best model in experiment 1" |
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- dest: "output/experiment1/model-last/textcat_multilabel/cfg" |
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description: "Configuration files for the last model in experiment 1" |
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- dest: "output/experiment1/model-last/textcat_multilabel/model" |
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description: "Trained model files for the last model in experiment 1" |
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- dest: "output/experiment1/model-last/vocab/key2row" |
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description: "Mapping from keys to row indices in the vocabulary for the last model in experiment 1" |
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- dest: "output/experiment1/model-last/vocab/lookups.bin" |
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description: "Binary lookups file for the vocabulary for the last model in experiment 1" |
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- dest: "output/experiment1/model-last/vocab/strings.json" |
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description: "JSON file containing string representations of the vocabulary for the last model in experiment 1" |
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- dest: "output/experiment1/model-last/vocab/vectors" |
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description: "Directory containing vector files for the vocabulary for the last model in experiment 1" |
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- dest: "output/experiment1/model-last/vocab/vectors.cfg" |
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description: "Configuration file for vectors in the vocabulary for the last model in experiment 1" |
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- dest: "output/experiment1/model-last/config.cfg" |
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description: "Configuration file for the last model in experiment 1" |
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- dest: "output/experiment1/model-last/meta.json" |
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description: "JSON file containing metadata for the last model in experiment 1" |
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- dest: "output/experiment1/model-last/tokenizer" |
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description: "Tokenizer files for the last model in experiment 1" |
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- dest: "output/experiment3/model-best/textcat_multilabel/cfg" |
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description: "Configuration files for the best model in experiment 3" |
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- dest: "output/experiment3/model-best/textcat_multilabel/model" |
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description: "Trained model files for the best model in experiment 3" |
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- dest: "output/experiment3/model-best/vocab/key2row" |
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description: "Mapping from keys to row indices in the vocabulary for the best model in experiment 3" |
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- dest: "output/experiment3/model-best/vocab/lookups.bin" |
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description: "Binary lookups file for the vocabulary for the best model in experiment 3" |
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- dest: "output/experiment3/model-best/vocab/strings.json" |
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description: "JSON file containing string representations of the vocabulary for the best model in experiment 3" |
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- dest: "output/experiment3/model-best/vocab/vectors" |
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description: "Directory containing vector files for the vocabulary for the best model in experiment 3" |
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- dest: "output/experiment3/model-best/vocab/vectors.cfg" |
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description: "Configuration file for vectors in the vocabulary for the best model in experiment 3" |
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- dest: "output/experiment3/model-best/config.cfg" |
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description: "Configuration file for the best model in experiment 3" |
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- dest: "output/experiment3/model-best/meta.json" |
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description: "JSON file containing metadata for the best model in experiment 3" |
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- dest: "output/experiment3/model-best/tokenizer" |
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description: "Tokenizer files for the best model in experiment 3" |
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- dest: "output/experiment3/model-last/textcat_multilabel/cfg" |
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description: "Configuration files for the last model in experiment 3" |
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- dest: "output/experiment3/model-last/textcat_multilabel/model" |
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description: "Trained model files for the last model in experiment 3" |
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- dest: "output/experiment3/model-last/vocab/key2row" |
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description: "Mapping from keys to row indices in the vocabulary for the last model in experiment 3" |
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- dest: "output/experiment3/model-last/vocab/lookups.bin" |
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description: "Binary lookups file for the vocabulary for the last model in experiment 3" |
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- dest: "output/experiment3/model-last/vocab/strings.json" |
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description: "JSON file containing string representations of the vocabulary for the last model in experiment 3" |
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- dest: "output/experiment3/model-last/vocab/vectors" |
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description: "Directory containing vector files for the vocabulary for the last model in experiment 3" |
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- dest: "output/experiment3/model-last/vocab/vectors.cfg" |
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description: "Configuration file for vectors in the vocabulary for the last model in experiment 3" |
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- dest: "output/experiment3/model-last/config.cfg" |
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description: "Configuration file for the last model in experiment 3" |
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- dest: "output/experiment3/model-last/meta.json" |
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description: "JSON file containing metadata for the last model in experiment 3" |
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- dest: "output/experiment3/model-last/tokenizer" |
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description: "Tokenizer files for the last model in experiment 3" |
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- dest: "python_Code/finalStep-formatLabel.py" |
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description: "Python script for formatting labeled data in the final step" |
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- dest: "python_Code/firstStep-format.py" |
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description: "Python script for formatting data in the first step" |
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- dest: "python_Code/five_examples_annotated.ipynb" |
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description: "Jupyter notebook containing five annotated examples" |
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- dest: "python_Code/secondStep-score.py" |
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description: "Python script for scoring data in the second step" |
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- dest: "python_Code/thirdStep-label.py" |
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description: "Python script for labeling data in the third step" |
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- dest: "python_Code/train_eval_split.ipynb" |
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description: "Jupyter notebook for training and evaluation data splitting" |
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- dest: "TerminalCode.txt" |
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description: "Text file containing terminal code" |
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- dest: "README.md" |
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description: "Markdown file containing project documentation" |
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- dest: "prodigy.json" |
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description: "JSON file containing Prodigy configuration" |
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workflows: |
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all: |
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- format-script |
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- train-text-classification-model |
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- classify-unlabeled-data |
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- format-labeled-data |
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- setup-environment |
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- review-evaluation-data |
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- export-reviewed-evaluation-data |
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- import-training-data |
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- import-golden-evaluation-data |
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- train-model-experiment1 |
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- download-model |
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- convert-data-to-spacy-format |
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- train-custom-model |
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commands: |
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- name: "format-script" |
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help: | |
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Execute the Python script `firstStep-format.py`, which performs the initial formatting of a dataset file for the first step of the project. This script extracts text and labels from a dataset file in JSONL format and writes them to a new JSONL file in a specific format. |
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Usage: |
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``` |
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spacy project run execute-first-step-format-script |
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``` |
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Explanation: |
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- The script `firstStep-format.py` reads data from the file specified in the `dataset_file` variable (`data/train200.jsonl` by default). |
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- It extracts text and labels from each JSON object in the dataset file. |
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- If both text and at least one label are available, it writes a new JSON object to the output file specified in the `output_file` variable (`data/firstStep_file.jsonl` by default) with the extracted text and label. |
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- If either text or label is missing in a JSON object, a warning message is printed. |
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- Upon completion, the script prints a message confirming the processing and the path to the output file. |
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script: |
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- "python3 python_Code/firstStep-format.py" |
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- name: "train-text-classification-model" |
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help: | |
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Train the text classification model for the second step of the project using the `secondStep-score.py` script. This script loads a blank English spaCy model and adds a text classification pipeline to it. It then trains the model using the processed data from the first step. |
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Usage: |
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``` |
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spacy project run train-text-classification-model |
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``` |
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Explanation: |
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- The script `secondStep-score.py` loads a blank English spaCy model and adds a text classification pipeline to it. |
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- It reads processed data from the file specified in the `processed_data_file` variable (`data/firstStep_file.jsonl` by default). |
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- The processed data is converted to spaCy format for training the model. |
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- The model is trained using the converted data for a specified number of iterations (`n_iter`). |
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- Losses are printed for each iteration during training. |
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- Upon completion, the trained model is saved to the specified output directory (`./my_trained_model` by default). |
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script: |
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- "python3 python_Code/secondStep-score.py" |
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- name: "classify-unlabeled-data" |
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help: | |
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Classify the unlabeled data for the third step of the project using the `thirdStep-label.py` script. This script loads the trained spaCy model from the previous step and classifies each record in the unlabeled dataset. |
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Usage: |
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``` |
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spacy project run classify-unlabeled-data |
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``` |
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Explanation: |
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- The script `thirdStep-label.py` loads the trained spaCy model from the specified model directory (`./my_trained_model` by default). |
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- It reads the unlabeled data from the file specified in the `unlabeled_data_file` variable (`data/train.jsonl` by default). |
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- Each record in the unlabeled data is classified using the loaded model. |
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- The predicted labels for each record are extracted and stored along with the text. |
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- The classified data is optionally saved to a file specified in the `output_file` variable (`data/thirdStep_file.jsonl` by default). |
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script: |
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- "python3 python_Code/thirdStep-label.py" |
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- name: "format-labeled-data" |
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help: | |
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Format the labeled data for the final step of the project using the `finalStep-formatLabel.py` script. This script processes the classified data from the third step and transforms it into a specific format, considering a threshold for label acceptance. |
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Usage: |
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``` |
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spacy project run format-labeled-data |
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``` |
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Explanation: |
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- The script `finalStep-formatLabel.py` reads classified data from the file specified in the `input_file` variable (`data/thirdStep_file.jsonl` by default). |
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- For each record, it determines accepted categories based on a specified threshold. |
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- It constructs an output record containing the text, predicted labels, accepted categories, answer (accept/reject), and options with meta information. |
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- The transformed data is written to the file specified in the `output_file` variable (`data/train4465.jsonl` by default). |
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script: |
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- "python3 python_Code/finalStep-formatLabel.py" |
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- name: "setup-environment" |
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help: | |
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Set up the Python virtual environment. |
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script: |
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- "python3 -m virtualenv venv" |
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- "source venv/bin/activate" |
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- name: "review-evaluation-data" |
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help: | |
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Review the evaluation data in Prodigy and automatically accept annotations. |
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Usage: |
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``` |
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spacy project run review-evaluation-data |
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``` |
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Explanation: |
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- The command reviews the evaluation data in Prodigy. |
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- It automatically accepts annotations made during the review process. |
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- Only sessions allowed by the environment variable PRODIGY_ALLOWED_SESSIONS are permitted to review data. In this case, the session 'reviwer' is allowed. |
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script: |
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- "PRODIGY_ALLOWED_SESSIONS=reviwer python3 -m prodigy review project3eval-review project3eval --auto-accept" |
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- name: "export-reviewed-evaluation-data" |
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help: | |
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Export the reviewed evaluation data from Prodigy to a JSONL file named 'goldenEval.jsonl'. |
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Usage: |
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``` |
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spacy project run export-reviewed-evaluation-data |
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``` |
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Explanation: |
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- The command exports the reviewed evaluation data from Prodigy to a JSONL file. |
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- The data is exported from the Prodigy database associated with the project named 'project3eval-review'. |
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- The exported data is saved to the file 'goldenEval.jsonl'. |
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- This command helps in preserving the reviewed annotations for further analysis or processing. |
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script: |
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- "prodigy db-out project3eval-review > goldenEval.jsonl" |
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- name: "import-training-data" |
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help: | |
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Import the training data into Prodigy from a JSONL file named 'train200.jsonl'. |
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Usage: |
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``` |
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spacy project run import-training-data |
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``` |
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Explanation: |
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- The command imports the training data into Prodigy from the specified JSONL file. |
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- The data is imported into the Prodigy database associated with the project named 'prodigy3train'. |
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- This command prepares the training data for annotation and model training in Prodigy. |
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script: |
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- "prodigy db-in prodigy3train train200.jsonl" |
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- name: "import-golden-evaluation-data" |
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help: | |
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Import the golden evaluation data into Prodigy from a JSONL file named 'goldeneval.jsonl'. |
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Usage: |
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``` |
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spacy project run import-golden-evaluation-data |
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``` |
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Explanation: |
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- The command imports the golden evaluation data into Prodigy from the specified JSONL file. |
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- The data is imported into the Prodigy database associated with the project named 'golden3'. |
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- This command prepares the golden evaluation data for further analysis and model evaluation in Prodigy. |
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script: |
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- "prodigy db-in golden3 goldeneval.jsonl" |
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- name: "train-model-experiment1" |
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help: | |
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Train a text classification model using Prodigy with the 'prodigy3train' dataset and evaluating on 'golden3'. |
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Usage: |
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``` |
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spacy project run train-model-experiment1 |
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``` |
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Explanation: |
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- The command trains a text classification model using Prodigy. |
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- It uses the 'prodigy3train' dataset for training and evaluates the model on the 'golden3' dataset. |
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- The trained model is saved to the './output/experiment1' directory. |
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script: |
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- "python3 -m prodigy train --textcat-multilabel prodigy3train,eval:golden3 ./output/experiment1" |
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- name: "download-model" |
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help: | |
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Download the English language model 'en_core_web_lg' from spaCy. |
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Usage: |
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``` |
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spacy project run download-model |
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``` |
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Explanation: |
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- The command downloads the English language model 'en_core_web_lg' from spaCy. |
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- This model is used as the base model for further data processing and training in the project. |
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script: |
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- "python3 -m spacy download en_core_web_lg" |
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|
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- name: "convert-data-to-spacy-format" |
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help: | |
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Convert the annotated data from Prodigy to spaCy format using the 'prodigy3train' and 'golden3' datasets. |
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Usage: |
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``` |
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spacy project run convert-data-to-spacy-format |
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``` |
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Explanation: |
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- The command converts the annotated data from Prodigy to spaCy format. |
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- It uses the 'prodigy3train' and 'golden3' datasets for conversion. |
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- The converted data is saved to the './corpus' directory with the base model 'en_core_web_lg'. |
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script: |
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- "python3 -m prodigy data-to-spacy --textcat-multilabel prodigy3train,eval:golden3 ./corpus --base-model en_core_web_lg" |
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|
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- name: "train-custom-model" |
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help: | |
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Train a custom text classification model using spaCy with the converted data in spaCy format. |
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Usage: |
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``` |
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spacy project run train-custom-model |
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``` |
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Explanation: |
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- The command trains a custom text classification model using spaCy. |
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- It uses the converted data in spaCy format located in the './corpus' directory. |
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- The model is trained using the configuration defined in 'corpus/config.cfg'. |
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script: |
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- "python -m spacy train corpus/config.cfg --paths.train corpus/train.spacy --paths.dev corpus/dev.spacy" |
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|
