<jupyter_start><jupyter_text>Distill 10 NN with different seeds<jupyter_code>for seed in range(5):
    parameters = {
        'random_seed': seed,
        'save_to_disk': True,
        'train_on_logits': True,
        'ensemble_logits': True,
        'model_prefix': f'nn',
    }
    
    _ = pm.execute_notebook(
        '06_NN_ensemble.ipynb',
        '_tmp_last_execution.ipynb',
        parameters=parameters,
        kernel_name='kd')
for seed in range(5):
    parameters = {
        'random_seed': seed,
        'save_to_disk': True,
        'train_on_logits': False,
        'ensemble_logits': True,
        'model_prefix': f'nn',
    }
    
    _ = pm.execute_notebook(
        '06_NN_ensemble.ipynb',
        '_tmp_last_execution.ipynb',
        parameters=parameters,
        kernel_name='kd')
for seed in range(5):
    parameters = {
        'random_seed': seed,
        'save_to_disk': True,
        'train_on_logits': True,
        'ensemble_logits': False,
        'model_prefix': f'nn',
    }
    
    _ = pm.execute_notebook(
        '06_NN_ensemble.ipynb',
        '_tmp_last_execution.ipynb',
        parameters=parameters,
        kernel_name='kd')
for seed in range(5):
    parameters = {
        'random_seed': seed,
        'save_to_disk': True,
        'train_on_logits': False,
        'ensemble_logits': False,
        'model_prefix': f'nn',
    }
    
    _ = pm.execute_notebook(
        '06_NN_ensemble.ipynb',
        '_tmp_last_execution.ipynb',
        parameters=parameters,
        kernel_name='kd')<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.12163892445582586, 'fraction_numerical': 0.008962868117797696, 'mean_word_length': 2.3044397463002113, 'pattern_counts': {'":': 0, '<': 5, '<?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': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '480020', 'license': 'Apache-2.0', 'n_tokens_mistral': 561, 'n_tokens_neox': 549, 'n_words': 85, 'path': 'notebooks/07_distill_multiple_NNs.ipynb', 'repo_name': 'nagra-insight/knowledge-distillation', 'size': '1562'}