<jupyter_start><jupyter_text>Uncomment to Start TensorboardLet's start Tensorboard and point to the tensorboard logs that we downloaded from S3 directly.Note:  If you pointed Tensorboard to S3 directly, you must prepend this command with `S3_REGION=[your-region]`.<jupyter_code>outputs_dir = './outputs'
!aws s3 cp --recursive s3://$bucket/$training_job_name/debug-output/events/ $outputs_dir/events/
!ls -al $outputs_dir/events
#!S3_REGION=us-east-1 tensorboard --port 6006 --logdir s3://$bucket/$training_job_name/debug-output/events/  # <== MAKE SURE YOU INCLUDE THE TRAILING `/`
!tensorboard --port 6006 --logdir $outputs_dir/events/ # <== MAKE SURE YOU INCLUDE THE TRAILING `/`<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.12219101123595505, 'fraction_numerical': 0.02247191011235955, 'mean_word_length': 5.3097345132743365, 'pattern_counts': {'":': 0, '<': 7, '<?xml version=': 0, '>': 5, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 1, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '366925', 'license': 'Apache-2.0', 'n_tokens_mistral': 251, 'n_tokens_neox': 237, 'n_words': 66, 'path': '07_train/archive/99_Tensorboard.ipynb', 'repo_name': 'MarcusFra/workshop', 'size': '712'}