update dataset

.gitignore

@@ -0,0 +1,2 @@
+*.csv
+.DS_Store

01-ai/Yi-34B-Chat/results_2024-01-13T14-57-48.json

@@ -0,0 +1,35 @@
+{
+    "config": {
+        "model_name": "01-ai/Yi-34B-Chat",
+        "model_type": "pretrained"
+    },
+    "results": {
+        "SAS": {
+            "weighted_accuracy": 0.6199999999999996
+        },
+        "EDP": {
+            "weighted_accuracy": 0.1654545454545451
+        },
+        "GCP": {
+            "weighted_accuracy": 0.0163636363636362
+        },
+        "GCP_D": {
+            "weighted_accuracy": 0.46363636363636307
+        },
+        "KSP": {
+            "weighted_accuracy": 0.0
+        },
+        "MSP": {
+            "weighted_accuracy": 0.0018181818181818
+        },
+        "SPP": {
+            "weighted_accuracy": 0.0
+        },
+        "TSP": {
+            "weighted_accuracy": 0.0054545454545454
+        },
+        "TSP_D": {
+            "weighted_accuracy": 0.43090909090909046
+        }
+    }
+}

Claude-2/results_2024-01-13T14-57-48.json

@@ -0,0 +1,35 @@
+{
+    "config": {
+        "model_name": "Claude-2",
+        "model_type": "pretrained"
+    },
+    "results": {
+        "SAS": {
+            "weighted_accuracy": 0.4454545454545449
+        },
+        "EDP": {
+            "weighted_accuracy": 0.1199999999999995
+        },
+        "GCP": {
+            "weighted_accuracy": 0.0236363636363635
+        },
+        "GCP_D": {
+            "weighted_accuracy": 0.5218181818181813
+        },
+        "KSP": {
+            "weighted_accuracy": 0.0018181818181818
+        },
+        "MSP": {
+            "weighted_accuracy": 0.0
+        },
+        "SPP": {
+            "weighted_accuracy": 0.3727272727272723
+        },
+        "TSP": {
+            "weighted_accuracy": 0.0199999999999999
+        },
+        "TSP_D": {
+            "weighted_accuracy": 0.8727272727272724
+        }
+    }
+}

Claude-Instant/results_2024-01-13T14-57-48.json

@@ -0,0 +1,35 @@
+{
+    "config": {
+        "model_name": "Claude-Instant",
+        "model_type": "pretrained"
+    },
+    "results": {
+        "SAS": {
+            "weighted_accuracy": 0.4418181818181813
+        },
+        "EDP": {
+            "weighted_accuracy": 0.1763636363636359
+        },
+        "GCP": {
+            "weighted_accuracy": 0.0290909090909089
+        },
+        "GCP_D": {
+            "weighted_accuracy": 0.5018181818181813
+        },
+        "KSP": {
+            "weighted_accuracy": 0.0
+        },
+        "MSP": {
+            "weighted_accuracy": 0.0018181818181818
+        },
+        "SPP": {
+            "weighted_accuracy": 0.2599999999999995
+        },
+        "TSP": {
+            "weighted_accuracy": 0.0199999999999999
+        },
+        "TSP_D": {
+            "weighted_accuracy": 0.723636363636363
+        }
+    }
+}

GPT-3.5-Turbo/results_2024-01-13T14-57-48.json

@@ -0,0 +1,35 @@
+{
+    "config": {
+        "model_name": "GPT-3.5-Turbo",
+        "model_type": "pretrained"
+    },
+    "results": {
+        "SAS": {
+            "weighted_accuracy": 0.9418181818181813
+        },
+        "EDP": {
+            "weighted_accuracy": 0.3181818181818177
+        },
+        "GCP": {
+            "weighted_accuracy": 0.0836363636363634
+        },
+        "GCP_D": {
+            "weighted_accuracy": 0.525454545454545
+        },
+        "KSP": {
+            "weighted_accuracy": 0.0
+        },
+        "MSP": {
+            "weighted_accuracy": 0.0054545454545453995
+        },
+        "SPP": {
+            "weighted_accuracy": 0.2218181818181813
+        },
+        "TSP": {
+            "weighted_accuracy": 0.0163636363636362
+        },
+        "TSP_D": {
+            "weighted_accuracy": 0.21454545454545418
+        }
+    }
+}

GPT-4-Turbo/results_2024-01-13T14-57-48.json

@@ -0,0 +1,35 @@
+{
+    "config": {
+        "model_name": "GPT-4-Turbo",
+        "model_type": "pretrained"
+    },
+    "results": {
+        "SAS": {
+            "weighted_accuracy": 0.9999999999999996
+        },
+        "EDP": {
+            "weighted_accuracy": 0.5363636363636359
+        },
+        "GCP": {
+            "weighted_accuracy": 0.076363636363636
+        },
+        "GCP_D": {
+            "weighted_accuracy": 0.7327272727272724
+        },
+        "KSP": {
+            "weighted_accuracy": 0.1872727272727269
+        },
+        "MSP": {
+            "weighted_accuracy": 0.012727272727272601
+        },
+        "SPP": {
+            "weighted_accuracy": 0.6290909090909085
+        },
+        "TSP": {
+            "weighted_accuracy": 0.0818181818181815
+        },
+        "TSP_D": {
+            "weighted_accuracy": 0.1399999999999996
+        }
+    }
+}

PaLM-2/results_2024-01-13T14-57-48.json

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+{
+    "config": {
+        "model_name": "PaLM-2",
+        "model_type": "pretrained"
+    },
+    "results": {
+        "SAS": {
+            "weighted_accuracy": 0.41636363636363594
+        },
+        "EDP": {
+            "weighted_accuracy": 0.0327272727272725
+        },
+        "GCP": {
+            "weighted_accuracy": 0.1618181818181814
+        },
+        "GCP_D": {
+            "weighted_accuracy": 0.059999999999999803
+        },
+        "KSP": {
+            "weighted_accuracy": 0.0199999999999999
+        },
+        "MSP": {
+            "weighted_accuracy": 0.0
+        },
+        "SPP": {
+            "weighted_accuracy": 0.2181818181818177
+        },
+        "TSP": {
+            "weighted_accuracy": 0.0072727272727272
+        },
+        "TSP_D": {
+            "weighted_accuracy": 0.565454545454545
+        }
+    }
+}

Qwen/Qwen-14B-Chat/results_2024-01-13T14-57-48.json

@@ -0,0 +1,35 @@
+{
+    "config": {
+        "model_name": "Qwen/Qwen-14B-Chat",
+        "model_type": "pretrained"
+    },
+    "results": {
+        "SAS": {
+            "weighted_accuracy": 0.7054545454545449
+        },
+        "EDP": {
+            "weighted_accuracy": 0.2690909090909086
+        },
+        "GCP": {
+            "weighted_accuracy": 0.0236363636363635
+        },
+        "GCP_D": {
+            "weighted_accuracy": 0.5599999999999994
+        },
+        "KSP": {
+            "weighted_accuracy": 0.0
+        },
+        "MSP": {
+            "weighted_accuracy": 0.0
+        },
+        "SPP": {
+            "weighted_accuracy": 0.0181818181818181
+        },
+        "TSP": {
+            "weighted_accuracy": 0.0127272727272727
+        },
+        "TSP_D": {
+            "weighted_accuracy": 0.41636363636363577
+        }
+    }
+}

export.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import os\n",
+    "import json\n",
+    "import datetime\n",
+    "\n",
+    "time_now = datetime.datetime.now().strftime(\"%Y-%m-%dT%H-%M-%S\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df = pd.read_csv(\"results.csv\")\n",
+    "new_df = df.groupby([\"model\", \"problem\"], as_index=False)[['weighted_accuracy']].sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "open_models = {\n",
+    "    \"Yi-34b\": \"01-ai/Yi-34B-Chat\",\n",
+    "    \"Mistral-7b\": \"mistralai/Mistral-7B-Instruct-v0.1\",\n",
+    "    \"Vicuna-13b\": \"lmsys/vicuna-13b-v1.3\",\n",
+    "    \"Phi-1.5\": \"microsoft/phi-1_5\",\n",
+    "    \"MPT-30b\": \"mosaicml/mpt-30b-instruct\",\n",
+    "    \"Phi-2\": \"microsoft/phi-2\",\n",
+    "    \"Qwen-14b\": \"Qwen/Qwen-14B-Chat\"\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def result_export(model_df, model_name):\n",
+    "    model_df = model_df.set_index(\"problem\")\n",
+    "    model_df = model_df.drop(columns=[\"model\"])\n",
+    "    model_df = model_df.to_dict(orient=\"index\")\n",
+    "    convert_problem_name = lambda x: x.replace(\"_Results\", \"\").replace(\"Results\", \"\").replace(\"bsp\", \"sas\").upper()\n",
+    "    model_df = {convert_problem_name(k): v for k, v in model_df.items()}\n",
+    "    return model_df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for model in new_df.model.unique():   \n",
+    "    model_dir = open_models[model] if model in open_models else model.replace(\" \", \"-\")\n",
+    "    # os.system(f\"rm -rf {model_dir.split('/')[0]}\")\n",
+    "    os.makedirs(f\"{model_dir}\", exist_ok=True)\n",
+    "    model_df = new_df[new_df[\"model\"] == model]\n",
+    "    model_result = result_export(model_df, model)\n",
+    "    model_result = {\n",
+    "        \"config\": {\"model_name\": model_dir, \"model_type\": \"pretrained\"},\n",
+    "        \"results\": model_result\n",
+    "    }\n",
+    "    with open(f\"{model_dir}/results_{time_now}.json\", \"w\") as f:\n",
+    "        json.dump(model_result, f, indent=4)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "llm_reason",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

lmsys/vicuna-13b-v1.3/results_2024-01-13T14-57-48.json

@@ -0,0 +1,35 @@
+{
+    "config": {
+        "model_name": "lmsys/vicuna-13b-v1.3",
+        "model_type": "pretrained"
+    },
+    "results": {
+        "SAS": {
+            "weighted_accuracy": 0.11272727272727251
+        },
+        "EDP": {
+            "weighted_accuracy": 0.1472727272727268
+        },
+        "GCP": {
+            "weighted_accuracy": 0.047272727272727105
+        },
+        "GCP_D": {
+            "weighted_accuracy": 0.3436363636363633
+        },
+        "KSP": {
+            "weighted_accuracy": 0.0
+        },
+        "MSP": {
+            "weighted_accuracy": 0.0
+        },
+        "SPP": {
+            "weighted_accuracy": 0.0
+        },
+        "TSP": {
+            "weighted_accuracy": 0.0
+        },
+        "TSP_D": {
+            "weighted_accuracy": 0.029090909090909
+        }
+    }
+}

microsoft/phi-1_5/results_2024-01-13T14-57-48.json

@@ -0,0 +1,35 @@
+{
+    "config": {
+        "model_name": "microsoft/phi-1_5",
+        "model_type": "pretrained"
+    },
+    "results": {
+        "SAS": {
+            "weighted_accuracy": 0.0
+        },
+        "EDP": {
+            "weighted_accuracy": 0.0
+        },
+        "GCP": {
+            "weighted_accuracy": 0.0199999999999999
+        },
+        "GCP_D": {
+            "weighted_accuracy": 0.0
+        },
+        "KSP": {
+            "weighted_accuracy": 0.0
+        },
+        "MSP": {
+            "weighted_accuracy": 0.0
+        },
+        "SPP": {
+            "weighted_accuracy": 0.0
+        },
+        "TSP": {
+            "weighted_accuracy": 0.0
+        },
+        "TSP_D": {
+            "weighted_accuracy": 0.0
+        }
+    }
+}

microsoft/phi-2/results_2024-01-13T14-57-48.json

@@ -0,0 +1,35 @@
+{
+    "config": {
+        "model_name": "microsoft/phi-2",
+        "model_type": "pretrained"
+    },
+    "results": {
+        "SAS": {
+            "weighted_accuracy": 0.1909090909090904
+        },
+        "EDP": {
+            "weighted_accuracy": 0.009090909090909
+        },
+        "GCP": {
+            "weighted_accuracy": 0.012727272727272601
+        },
+        "GCP_D": {
+            "weighted_accuracy": 0.5581818181818176
+        },
+        "KSP": {
+            "weighted_accuracy": 0.0
+        },
+        "MSP": {
+            "weighted_accuracy": 0.0
+        },
+        "SPP": {
+            "weighted_accuracy": 0.0327272727272726
+        },
+        "TSP": {
+            "weighted_accuracy": 0.0109090909090909
+        },
+        "TSP_D": {
+            "weighted_accuracy": 0.0145454545454545
+        }
+    }
+}

mistralai/Mistral-7B-Instruct-v0.1/results_2024-01-13T14-57-48.json

@@ -0,0 +1,35 @@
+{
+    "config": {
+        "model_name": "mistralai/Mistral-7B-Instruct-v0.1",
+        "model_type": "pretrained"
+    },
+    "results": {
+        "SAS": {
+            "weighted_accuracy": 0.1490909090909086
+        },
+        "EDP": {
+            "weighted_accuracy": 0.058181818181818
+        },
+        "GCP": {
+            "weighted_accuracy": 0.2090909090909085
+        },
+        "GCP_D": {
+            "weighted_accuracy": 0.5799999999999995
+        },
+        "KSP": {
+            "weighted_accuracy": 0.0
+        },
+        "MSP": {
+            "weighted_accuracy": 0.0
+        },
+        "SPP": {
+            "weighted_accuracy": 0.0163636363636363
+        },
+        "TSP": {
+            "weighted_accuracy": 0.0
+        },
+        "TSP_D": {
+            "weighted_accuracy": 0.6272727272727268
+        }
+    }
+}

mosaicml/mpt-30b-instruct/results_2024-01-13T14-57-48.json

@@ -0,0 +1,35 @@
+{
+    "config": {
+        "model_name": "mosaicml/mpt-30b-instruct",
+        "model_type": "pretrained"
+    },
+    "results": {
+        "SAS": {
+            "weighted_accuracy": 0.0
+        },
+        "EDP": {
+            "weighted_accuracy": 0.0018181818181818
+        },
+        "GCP": {
+            "weighted_accuracy": 0.0
+        },
+        "GCP_D": {
+            "weighted_accuracy": 0.0
+        },
+        "KSP": {
+            "weighted_accuracy": 0.0
+        },
+        "MSP": {
+            "weighted_accuracy": 0.0
+        },
+        "SPP": {
+            "weighted_accuracy": 0.0
+        },
+        "TSP": {
+            "weighted_accuracy": 0.0
+        },
+        "TSP_D": {
+            "weighted_accuracy": 0.0
+        }
+    }
+}