<jupyter_start><jupyter_text>Glove Training<jupyter_code>glove_settings
model_trainer = ModelTrainer(glove_settings)
model_trainer.train()
model_trainer.save_plots()<jupyter_output><empty_output><jupyter_text>Word2Vec Training<jupyter_code>word2vec_settings
model_trainer = ModelTrainer(word2vec_settings)
model_trainer.train()
model_trainer.save_plots()<jupyter_output><empty_output><jupyter_text>BERT Training<jupyter_code>bert_settings
model_trainer = ModelTrainer(bert_settings)
model_trainer.train()
model_trainer.save_plots()<jupyter_output><empty_output><jupyter_text>How to Load&Continue<jupyter_code>path_chkp = "./output/BertRun/20-03-10_200018_BertLSTM/checkpoints/last_epoch.chkp"
bert_settings["load_checkpoint"] = path_chkp
model_trainer = ModelTrainer(bert_settings)
model_trainer.epoch_counter
model_trainer.train()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.09988385598141696, 'fraction_numerical': 0.017421602787456445, 'mean_word_length': 16.958333333333332, 'pattern_counts': {'":': 0, '<': 17, '<?xml version=': 0, '>': 17, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '4', 'dir': 'jupyter-structured-clean-dedup', 'id': '369570', 'license': 'MIT', 'n_tokens_mistral': 336, 'n_tokens_neox': 324, 'n_words': 25, 'path': '4. Training.ipynb', 'repo_name': 'rubicco/music-genre-classification', 'size': '861'}