Datasets:
ArXiv:
License:
feat: add notebook for parsing evaluation results
Browse files- ParseEvaluations.ipynb +55 -34
ParseEvaluations.ipynb
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"cells": [
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"cell_type": "code",
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"id": "5cbc726d-b9ed-4a87-8424-780a4db25a36",
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"metadata": {},
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"outputs": [],
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"source": [
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"import json\n",
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"\n",
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"from pathlib import Path\n",
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"from tabulate import tabulate"
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"cell_type": "code",
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"execution_count":
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"id": "dbffdf82-5cb2-485d-9334-6e6fb8cc9c91",
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"metadata": {},
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"outputs": [
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"{'dbmdz/
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}
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"cell_type": "code",
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"execution_count":
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"id": "7170ec01-f0f1-49bb-9beb-7927c3b5b3f7",
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"metadata": {},
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"outputs": [
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"cell_type": "code",
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"execution_count":
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"id": "5c444bbe-93e7-4e85-8560-56bff13e1bb0",
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"metadata": {},
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"outputs": [
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"source": [
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"headers = [\"Phenomenon\"] + model_names\n",
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"\n",
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"
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"\n",
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"table = []\n",
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"\n",
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"for model_name in model_names:\n",
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"
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" \n",
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" with open(model_name_evaluation_filename_mapping[model_name], \"rt\") as f_p:\n",
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" \n",
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" for line in f_p:\n",
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" data = json.loads(line)\n",
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"\n",
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" current_task_name = data[\"file_name\"]\n",
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" current_task_accuracy = round(data[\"accuracy\"],
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"\n",
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"
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" phenomenon = task_phenomenon_mapping[data_task_name]\n",
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" accuracy = phenomenon_accuracy_mapping[data_task_name]\n",
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" table.append([phenomenon, accuracy])\n",
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" print(current_row)\n",
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"\n",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.
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}
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},
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"nbformat": 4,
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "5cbc726d-b9ed-4a87-8424-780a4db25a36",
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"metadata": {},
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"outputs": [],
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"source": [
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"import json\n",
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"import numpy as np\n",
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"\n",
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"from pathlib import Path\n",
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"from tabulate import tabulate"
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "dbffdf82-5cb2-485d-9334-6e6fb8cc9c91",
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"metadata": {},
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"outputs": [
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"{'dbmdz/distilbert-base-turkish-cased': 'results-dbmdz-distilbert-base-turkish-cased.jsonl', 'dbmdz/convbert-base-turkish-mc4-cased': 'results-dbmdz-convbert-base-turkish-mc4-cased.jsonl', 'dbmdz/bert-base-turkish-uncased': 'results-dbmdz-bert-base-turkish-uncased.jsonl', 'dbmdz/bert-base-turkish-128k-cased': 'results-dbmdz-bert-base-turkish-128k-cased.jsonl', 'dbmdz/bert-base-turkish-cased': 'results-dbmdz-bert-base-turkish-cased.jsonl', 'dbmdz/electra-small-turkish-cased-generator': 'results-dbmdz-electra-small-turkish-cased-generator.jsonl', 'dbmdz/convbert-base-turkish-cased': 'results-dbmdz-convbert-base-turkish-cased.jsonl', 'dbmdz/electra-base-turkish-cased-generator': 'results-dbmdz-electra-base-turkish-cased-generator.jsonl', 'dbmdz/convbert-base-turkish-mc4-uncased': 'results-dbmdz-convbert-base-turkish-mc4-uncased.jsonl', 'dbmdz/electra-base-turkish-mc4-cased-generator': 'results-dbmdz-electra-base-turkish-mc4-cased-generator.jsonl', 'dbmdz/bert-base-turkish-128k-uncased': 'results-dbmdz-bert-base-turkish-128k-uncased.jsonl', 'dbmdz/electra-base-turkish-mc4-uncased-generator': 'results-dbmdz-electra-base-turkish-mc4-uncased-generator.jsonl'}\n"
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]
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}
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],
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "7170ec01-f0f1-49bb-9beb-7927c3b5b3f7",
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"metadata": {},
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"outputs": [
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"id": "5c444bbe-93e7-4e85-8560-56bff13e1bb0",
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"metadata": {},
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"outputs": [
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"| Phenomenon | [`dbmdz/electra-small-turkish-cased-generator`](https://huggingface.co/dbmdz/electra-small-turkish-cased-generator) | [`dbmdz/electra-base-turkish-cased-generator`](https://huggingface.co/dbmdz/electra-base-turkish-cased-generator) | [`dbmdz/electra-base-turkish-mc4-cased-generator`](https://huggingface.co/dbmdz/electra-base-turkish-mc4-cased-generator) | [`dbmdz/electra-base-turkish-mc4-uncased-generator`](https://huggingface.co/dbmdz/electra-base-turkish-mc4-uncased-generator) | [`dbmdz/bert-base-turkish-cased`](https://huggingface.co/dbmdz/bert-base-turkish-cased) | [`dbmdz/bert-base-turkish-uncased`](https://huggingface.co/dbmdz/bert-base-turkish-uncased) | [`dbmdz/bert-base-turkish-128k-cased`](https://huggingface.co/dbmdz/bert-base-turkish-128k-cased) | [`dbmdz/bert-base-turkish-128k-uncased`](https://huggingface.co/dbmdz/bert-base-turkish-128k-uncased) | [`dbmdz/distilbert-base-turkish-cased`](https://huggingface.co/dbmdz/distilbert-base-turkish-cased) | [`dbmdz/convbert-base-turkish-cased`](https://huggingface.co/dbmdz/convbert-base-turkish-cased) | [`dbmdz/convbert-base-turkish-mc4-cased`](https://huggingface.co/dbmdz/convbert-base-turkish-mc4-cased) | [`dbmdz/convbert-base-turkish-mc4-uncased`](https://huggingface.co/dbmdz/convbert-base-turkish-mc4-uncased) |\n",
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"|----------------------|-----------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------|\n",
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"| Anaphor Agreement | 74.1 | 94.3 | 94.3 | 92.8 | 96.7 | 97.3 | 97.3 | 97.7 | 96.9 | 58.1 | 44.3 | 44.6 |\n",
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"| Argument Str. Tran. | 86.6 | 99.6 | 99.4 | 98.7 | 99.7 | 99.6 | 99.8 | 99.1 | 97.5 | 51.9 | 58.1 | 51.3 |\n",
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"| Argument Str. Ditr. | 79.3 | 96.1 | 95.5 | 95.2 | 99.8 | 96.1 | 96.1 | 96.1 | 95.4 | 64.6 | 58.6 | 64.5 |\n",
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"| Binding | 70.7 | 96.2 | 91.4 | 89.6 | 99.9 | 98.5 | 97.7 | 99 | 93 | 89.1 | 49.4 | 78.4 |\n",
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"| Determiners | 91.8 | 99.3 | 98.2 | 99.1 | 99.9 | 100 | 99 | 99.3 | 82.9 | 0 | 0 | 0 |\n",
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"| Ellipsis | 10.6 | 49.7 | 46.3 | 49 | 87.4 | 73.6 | 96.6 | 87.5 | 13.6 | 54.7 | 57.8 | 67.9 |\n",
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"| Irregular Forms | 98.7 | 97.9 | 99 | 99.8 | 98.8 | 100 | 99.9 | 99.6 | 94.1 | 82.9 | 86.6 | 95.2 |\n",
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"| Island Effects | 39.1 | 35.3 | 41.8 | 44 | 49.4 | 39.8 | 60.9 | 51.2 | 47.4 | 96.7 | 99.4 | 100 |\n",
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"| Nominalization | 90 | 96.6 | 97 | 95.4 | 97.4 | 97 | 98.9 | 97.4 | 95.6 | 55.2 | 59.2 | 60.6 |\n",
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"| NPI Licensing | 90.9 | 96.1 | 95 | 98 | 98.2 | 97.6 | 97.2 | 95 | 92.1 | 82.1 | 95.6 | 71.9 |\n",
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"| Passives | 100 | 91.2 | 93.6 | 91.6 | 82.2 | 78.1 | 84.4 | 81.3 | 98.8 | 100 | 100 | 99 |\n",
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"| Quantifiers | 97.9 | 98 | 98 | 97.6 | 95.7 | 94.6 | 98 | 98.4 | 98.4 | 99 | 99 | 99 |\n",
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"| Relative Clauses | 79.9 | 90.7 | 92 | 91.6 | 97.7 | 97.5 | 97 | 98.5 | 92 | 53.4 | 53.7 | 56.9 |\n",
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"| Scrambling | 99.5 | 100 | 100 | 99.8 | 100 | 100 | 99.6 | 100 | 99.8 | 38.7 | 59.3 | 63.3 |\n",
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"| Subject Agreement | 82.8 | 99 | 97.2 | 96.1 | 98.3 | 99.2 | 99.1 | 98.8 | 97 | 47.7 | 43.9 | 56.4 |\n",
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"| Suspended Affixation | 97.5 | 99 | 99.1 | 98.8 | 100 | 100 | 100 | 100 | 100 | 25.4 | 12.8 | 23.2 |\n",
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"| Model Average | 80.6 | 89.9 | 89.9 | 89.8 | 93.8 | 91.8 | 95.1 | 93.7 | 87.2 | 62.5 | 61.1 | 64.5 |\n"
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]
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}
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],
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"source": [
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"headers = [\"Phenomenon\"] + [f\"[`{model_name}`](https://huggingface.co/{model_name})\" for model_name in model_names]\n",
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"\n",
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"model_results = {}\n",
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"\n",
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"for model_name in model_names:\n",
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" current_model_results = {}\n",
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" with open(model_name_evaluation_filename_mapping[model_name], \"rt\") as f_p:\n",
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" for line in f_p:\n",
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" data = json.loads(line)\n",
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"\n",
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" current_task_name = data[\"file_name\"]\n",
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" current_task_accuracy = round(data[\"accuracy\"], 1)\n",
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" current_task_phenomenon = task_phenomenon_mapping[current_task_name]\n",
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" current_model_results[current_task_phenomenon] = current_task_accuracy\n",
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"\n",
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" model_average = list(current_model_results.values())\n",
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" model_average = np.mean(model_average)\n",
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" model_average = round(model_average, 1)\n",
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"\n",
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" current_model_results[\"Model Average\"] = model_average\n",
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"\n",
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" model_results[model_name] = current_model_results\n",
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"\n",
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"table = []\n",
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"phenomenons.append(\"Model Average\")\n",
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"\n",
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"for phenomenon in phenomenons:\n",
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" current_row = []\n",
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"\n",
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" current_row.append(phenomenon)\n",
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"\n",
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" for model_name in model_names:\n",
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" current_phenomenon_accuracy = model_results[model_name][phenomenon]\n",
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" current_row.append(current_phenomenon_accuracy)\n",
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"\n",
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" table.append(current_row)\n",
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" \n",
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"print(tabulate(table, headers=headers, tablefmt=\"github\"))"
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}
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],
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.13.3"
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}
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},
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"nbformat": 4,
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