<jupyter_start><jupyter_text>Try find best combination after tweeks<jupyter_code>all_preds = os.listdir("../predicts/")
xlnet_preds = sorted([pred for pred in all_preds if "Exp_045" in pred])
roberta_preds = sorted([pred for pred in all_preds if "Exp_043" in pred])
deberta_preds = sorted([pred for pred in all_preds if "Exp_044" in pred])
additional_confidences = [round(0.05*i,3) for i in range(3,11)]
additional_confidences
min_error_probabilities = [round(0.05*i,3) for i in range(6,16)]
min_error_probabilities
len(additional_confidences)*len(min_error_probabilities)
all_comb = []
for ac in additional_confidences:
    for mep in min_error_probabilities:
        s_ac = str(ac)
        s_mep = str(mep)
        comb =  [
            'Exp_043_roberta_large_ac_'+s_ac+'_mep_'+s_mep+'.txt',
            'Exp_044_deberta_large_ac_'+s_ac+'_mep_'+s_mep+'.txt',
            'Exp_045_xlnet_large_ac_'+s_ac+'_mep_'+s_mep+'.txt',
            'Exp_merge_large_ac_'+s_ac+'_mep_'+s_mep+'.txt'
        ]
        all_comb.append(comb)
#all_comb<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.12488262910798122, 'fraction_numerical': 0.03004694835680751, 'mean_word_length': 4.610526315789474, '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': '186942', 'license': 'Apache-2.0', 'n_tokens_mistral': 445, 'n_tokens_neox': 421, 'n_words': 72, 'path': 'notebooks/Ensemble/Custom_ensemble.ipynb', 'repo_name': 'MaksTarnavskyi/improve-sequence-tagging', 'size': '1065'}