haoyang commited on
Commit
1e5e2ae
1 Parent(s): 6ca715b

update dataset

Browse files
.gitignore ADDED
@@ -0,0 +1,2 @@
 
 
 
1
+ *.csv
2
+ .DS_Store
01-ai/Yi-34B-Chat/results_2024-01-13T14-57-48.json ADDED
@@ -0,0 +1,35 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "config": {
3
+ "model_name": "01-ai/Yi-34B-Chat",
4
+ "model_type": "pretrained"
5
+ },
6
+ "results": {
7
+ "SAS": {
8
+ "weighted_accuracy": 0.6199999999999996
9
+ },
10
+ "EDP": {
11
+ "weighted_accuracy": 0.1654545454545451
12
+ },
13
+ "GCP": {
14
+ "weighted_accuracy": 0.0163636363636362
15
+ },
16
+ "GCP_D": {
17
+ "weighted_accuracy": 0.46363636363636307
18
+ },
19
+ "KSP": {
20
+ "weighted_accuracy": 0.0
21
+ },
22
+ "MSP": {
23
+ "weighted_accuracy": 0.0018181818181818
24
+ },
25
+ "SPP": {
26
+ "weighted_accuracy": 0.0
27
+ },
28
+ "TSP": {
29
+ "weighted_accuracy": 0.0054545454545454
30
+ },
31
+ "TSP_D": {
32
+ "weighted_accuracy": 0.43090909090909046
33
+ }
34
+ }
35
+ }
Claude-2/results_2024-01-13T14-57-48.json ADDED
@@ -0,0 +1,35 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "config": {
3
+ "model_name": "Claude-2",
4
+ "model_type": "pretrained"
5
+ },
6
+ "results": {
7
+ "SAS": {
8
+ "weighted_accuracy": 0.4454545454545449
9
+ },
10
+ "EDP": {
11
+ "weighted_accuracy": 0.1199999999999995
12
+ },
13
+ "GCP": {
14
+ "weighted_accuracy": 0.0236363636363635
15
+ },
16
+ "GCP_D": {
17
+ "weighted_accuracy": 0.5218181818181813
18
+ },
19
+ "KSP": {
20
+ "weighted_accuracy": 0.0018181818181818
21
+ },
22
+ "MSP": {
23
+ "weighted_accuracy": 0.0
24
+ },
25
+ "SPP": {
26
+ "weighted_accuracy": 0.3727272727272723
27
+ },
28
+ "TSP": {
29
+ "weighted_accuracy": 0.0199999999999999
30
+ },
31
+ "TSP_D": {
32
+ "weighted_accuracy": 0.8727272727272724
33
+ }
34
+ }
35
+ }
Claude-Instant/results_2024-01-13T14-57-48.json ADDED
@@ -0,0 +1,35 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "config": {
3
+ "model_name": "Claude-Instant",
4
+ "model_type": "pretrained"
5
+ },
6
+ "results": {
7
+ "SAS": {
8
+ "weighted_accuracy": 0.4418181818181813
9
+ },
10
+ "EDP": {
11
+ "weighted_accuracy": 0.1763636363636359
12
+ },
13
+ "GCP": {
14
+ "weighted_accuracy": 0.0290909090909089
15
+ },
16
+ "GCP_D": {
17
+ "weighted_accuracy": 0.5018181818181813
18
+ },
19
+ "KSP": {
20
+ "weighted_accuracy": 0.0
21
+ },
22
+ "MSP": {
23
+ "weighted_accuracy": 0.0018181818181818
24
+ },
25
+ "SPP": {
26
+ "weighted_accuracy": 0.2599999999999995
27
+ },
28
+ "TSP": {
29
+ "weighted_accuracy": 0.0199999999999999
30
+ },
31
+ "TSP_D": {
32
+ "weighted_accuracy": 0.723636363636363
33
+ }
34
+ }
35
+ }
GPT-3.5-Turbo/results_2024-01-13T14-57-48.json ADDED
@@ -0,0 +1,35 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "config": {
3
+ "model_name": "GPT-3.5-Turbo",
4
+ "model_type": "pretrained"
5
+ },
6
+ "results": {
7
+ "SAS": {
8
+ "weighted_accuracy": 0.9418181818181813
9
+ },
10
+ "EDP": {
11
+ "weighted_accuracy": 0.3181818181818177
12
+ },
13
+ "GCP": {
14
+ "weighted_accuracy": 0.0836363636363634
15
+ },
16
+ "GCP_D": {
17
+ "weighted_accuracy": 0.525454545454545
18
+ },
19
+ "KSP": {
20
+ "weighted_accuracy": 0.0
21
+ },
22
+ "MSP": {
23
+ "weighted_accuracy": 0.0054545454545453995
24
+ },
25
+ "SPP": {
26
+ "weighted_accuracy": 0.2218181818181813
27
+ },
28
+ "TSP": {
29
+ "weighted_accuracy": 0.0163636363636362
30
+ },
31
+ "TSP_D": {
32
+ "weighted_accuracy": 0.21454545454545418
33
+ }
34
+ }
35
+ }
GPT-4-Turbo/results_2024-01-13T14-57-48.json ADDED
@@ -0,0 +1,35 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "config": {
3
+ "model_name": "GPT-4-Turbo",
4
+ "model_type": "pretrained"
5
+ },
6
+ "results": {
7
+ "SAS": {
8
+ "weighted_accuracy": 0.9999999999999996
9
+ },
10
+ "EDP": {
11
+ "weighted_accuracy": 0.5363636363636359
12
+ },
13
+ "GCP": {
14
+ "weighted_accuracy": 0.076363636363636
15
+ },
16
+ "GCP_D": {
17
+ "weighted_accuracy": 0.7327272727272724
18
+ },
19
+ "KSP": {
20
+ "weighted_accuracy": 0.1872727272727269
21
+ },
22
+ "MSP": {
23
+ "weighted_accuracy": 0.012727272727272601
24
+ },
25
+ "SPP": {
26
+ "weighted_accuracy": 0.6290909090909085
27
+ },
28
+ "TSP": {
29
+ "weighted_accuracy": 0.0818181818181815
30
+ },
31
+ "TSP_D": {
32
+ "weighted_accuracy": 0.1399999999999996
33
+ }
34
+ }
35
+ }
PaLM-2/results_2024-01-13T14-57-48.json ADDED
@@ -0,0 +1,35 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "config": {
3
+ "model_name": "PaLM-2",
4
+ "model_type": "pretrained"
5
+ },
6
+ "results": {
7
+ "SAS": {
8
+ "weighted_accuracy": 0.41636363636363594
9
+ },
10
+ "EDP": {
11
+ "weighted_accuracy": 0.0327272727272725
12
+ },
13
+ "GCP": {
14
+ "weighted_accuracy": 0.1618181818181814
15
+ },
16
+ "GCP_D": {
17
+ "weighted_accuracy": 0.059999999999999803
18
+ },
19
+ "KSP": {
20
+ "weighted_accuracy": 0.0199999999999999
21
+ },
22
+ "MSP": {
23
+ "weighted_accuracy": 0.0
24
+ },
25
+ "SPP": {
26
+ "weighted_accuracy": 0.2181818181818177
27
+ },
28
+ "TSP": {
29
+ "weighted_accuracy": 0.0072727272727272
30
+ },
31
+ "TSP_D": {
32
+ "weighted_accuracy": 0.565454545454545
33
+ }
34
+ }
35
+ }
Qwen/Qwen-14B-Chat/results_2024-01-13T14-57-48.json ADDED
@@ -0,0 +1,35 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "config": {
3
+ "model_name": "Qwen/Qwen-14B-Chat",
4
+ "model_type": "pretrained"
5
+ },
6
+ "results": {
7
+ "SAS": {
8
+ "weighted_accuracy": 0.7054545454545449
9
+ },
10
+ "EDP": {
11
+ "weighted_accuracy": 0.2690909090909086
12
+ },
13
+ "GCP": {
14
+ "weighted_accuracy": 0.0236363636363635
15
+ },
16
+ "GCP_D": {
17
+ "weighted_accuracy": 0.5599999999999994
18
+ },
19
+ "KSP": {
20
+ "weighted_accuracy": 0.0
21
+ },
22
+ "MSP": {
23
+ "weighted_accuracy": 0.0
24
+ },
25
+ "SPP": {
26
+ "weighted_accuracy": 0.0181818181818181
27
+ },
28
+ "TSP": {
29
+ "weighted_accuracy": 0.0127272727272727
30
+ },
31
+ "TSP_D": {
32
+ "weighted_accuracy": 0.41636363636363577
33
+ }
34
+ }
35
+ }
export.ipynb ADDED
@@ -0,0 +1,108 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "cells": [
3
+ {
4
+ "cell_type": "code",
5
+ "execution_count": 1,
6
+ "metadata": {},
7
+ "outputs": [],
8
+ "source": [
9
+ "import pandas as pd\n",
10
+ "import os\n",
11
+ "import json\n",
12
+ "import datetime\n",
13
+ "\n",
14
+ "time_now = datetime.datetime.now().strftime(\"%Y-%m-%dT%H-%M-%S\")"
15
+ ]
16
+ },
17
+ {
18
+ "cell_type": "code",
19
+ "execution_count": 2,
20
+ "metadata": {},
21
+ "outputs": [],
22
+ "source": [
23
+ "df = pd.read_csv(\"results.csv\")\n",
24
+ "new_df = df.groupby([\"model\", \"problem\"], as_index=False)[['weighted_accuracy']].sum()"
25
+ ]
26
+ },
27
+ {
28
+ "cell_type": "code",
29
+ "execution_count": 3,
30
+ "metadata": {},
31
+ "outputs": [],
32
+ "source": [
33
+ "open_models = {\n",
34
+ " \"Yi-34b\": \"01-ai/Yi-34B-Chat\",\n",
35
+ " \"Mistral-7b\": \"mistralai/Mistral-7B-Instruct-v0.1\",\n",
36
+ " \"Vicuna-13b\": \"lmsys/vicuna-13b-v1.3\",\n",
37
+ " \"Phi-1.5\": \"microsoft/phi-1_5\",\n",
38
+ " \"MPT-30b\": \"mosaicml/mpt-30b-instruct\",\n",
39
+ " \"Phi-2\": \"microsoft/phi-2\",\n",
40
+ " \"Qwen-14b\": \"Qwen/Qwen-14B-Chat\"\n",
41
+ "}"
42
+ ]
43
+ },
44
+ {
45
+ "cell_type": "code",
46
+ "execution_count": 4,
47
+ "metadata": {},
48
+ "outputs": [],
49
+ "source": [
50
+ "def result_export(model_df, model_name):\n",
51
+ " model_df = model_df.set_index(\"problem\")\n",
52
+ " model_df = model_df.drop(columns=[\"model\"])\n",
53
+ " model_df = model_df.to_dict(orient=\"index\")\n",
54
+ " convert_problem_name = lambda x: x.replace(\"_Results\", \"\").replace(\"Results\", \"\").replace(\"bsp\", \"sas\").upper()\n",
55
+ " model_df = {convert_problem_name(k): v for k, v in model_df.items()}\n",
56
+ " return model_df"
57
+ ]
58
+ },
59
+ {
60
+ "cell_type": "code",
61
+ "execution_count": 5,
62
+ "metadata": {},
63
+ "outputs": [],
64
+ "source": [
65
+ "for model in new_df.model.unique(): \n",
66
+ " model_dir = open_models[model] if model in open_models else model.replace(\" \", \"-\")\n",
67
+ " # os.system(f\"rm -rf {model_dir.split('/')[0]}\")\n",
68
+ " os.makedirs(f\"{model_dir}\", exist_ok=True)\n",
69
+ " model_df = new_df[new_df[\"model\"] == model]\n",
70
+ " model_result = result_export(model_df, model)\n",
71
+ " model_result = {\n",
72
+ " \"config\": {\"model_name\": model_dir, \"model_type\": \"pretrained\"},\n",
73
+ " \"results\": model_result\n",
74
+ " }\n",
75
+ " with open(f\"{model_dir}/results_{time_now}.json\", \"w\") as f:\n",
76
+ " json.dump(model_result, f, indent=4)"
77
+ ]
78
+ },
79
+ {
80
+ "cell_type": "code",
81
+ "execution_count": null,
82
+ "metadata": {},
83
+ "outputs": [],
84
+ "source": []
85
+ }
86
+ ],
87
+ "metadata": {
88
+ "kernelspec": {
89
+ "display_name": "llm_reason",
90
+ "language": "python",
91
+ "name": "python3"
92
+ },
93
+ "language_info": {
94
+ "codemirror_mode": {
95
+ "name": "ipython",
96
+ "version": 3
97
+ },
98
+ "file_extension": ".py",
99
+ "mimetype": "text/x-python",
100
+ "name": "python",
101
+ "nbconvert_exporter": "python",
102
+ "pygments_lexer": "ipython3",
103
+ "version": "3.10.13"
104
+ }
105
+ },
106
+ "nbformat": 4,
107
+ "nbformat_minor": 2
108
+ }
lmsys/vicuna-13b-v1.3/results_2024-01-13T14-57-48.json ADDED
@@ -0,0 +1,35 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "config": {
3
+ "model_name": "lmsys/vicuna-13b-v1.3",
4
+ "model_type": "pretrained"
5
+ },
6
+ "results": {
7
+ "SAS": {
8
+ "weighted_accuracy": 0.11272727272727251
9
+ },
10
+ "EDP": {
11
+ "weighted_accuracy": 0.1472727272727268
12
+ },
13
+ "GCP": {
14
+ "weighted_accuracy": 0.047272727272727105
15
+ },
16
+ "GCP_D": {
17
+ "weighted_accuracy": 0.3436363636363633
18
+ },
19
+ "KSP": {
20
+ "weighted_accuracy": 0.0
21
+ },
22
+ "MSP": {
23
+ "weighted_accuracy": 0.0
24
+ },
25
+ "SPP": {
26
+ "weighted_accuracy": 0.0
27
+ },
28
+ "TSP": {
29
+ "weighted_accuracy": 0.0
30
+ },
31
+ "TSP_D": {
32
+ "weighted_accuracy": 0.029090909090909
33
+ }
34
+ }
35
+ }
microsoft/phi-1_5/results_2024-01-13T14-57-48.json ADDED
@@ -0,0 +1,35 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "config": {
3
+ "model_name": "microsoft/phi-1_5",
4
+ "model_type": "pretrained"
5
+ },
6
+ "results": {
7
+ "SAS": {
8
+ "weighted_accuracy": 0.0
9
+ },
10
+ "EDP": {
11
+ "weighted_accuracy": 0.0
12
+ },
13
+ "GCP": {
14
+ "weighted_accuracy": 0.0199999999999999
15
+ },
16
+ "GCP_D": {
17
+ "weighted_accuracy": 0.0
18
+ },
19
+ "KSP": {
20
+ "weighted_accuracy": 0.0
21
+ },
22
+ "MSP": {
23
+ "weighted_accuracy": 0.0
24
+ },
25
+ "SPP": {
26
+ "weighted_accuracy": 0.0
27
+ },
28
+ "TSP": {
29
+ "weighted_accuracy": 0.0
30
+ },
31
+ "TSP_D": {
32
+ "weighted_accuracy": 0.0
33
+ }
34
+ }
35
+ }
microsoft/phi-2/results_2024-01-13T14-57-48.json ADDED
@@ -0,0 +1,35 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "config": {
3
+ "model_name": "microsoft/phi-2",
4
+ "model_type": "pretrained"
5
+ },
6
+ "results": {
7
+ "SAS": {
8
+ "weighted_accuracy": 0.1909090909090904
9
+ },
10
+ "EDP": {
11
+ "weighted_accuracy": 0.009090909090909
12
+ },
13
+ "GCP": {
14
+ "weighted_accuracy": 0.012727272727272601
15
+ },
16
+ "GCP_D": {
17
+ "weighted_accuracy": 0.5581818181818176
18
+ },
19
+ "KSP": {
20
+ "weighted_accuracy": 0.0
21
+ },
22
+ "MSP": {
23
+ "weighted_accuracy": 0.0
24
+ },
25
+ "SPP": {
26
+ "weighted_accuracy": 0.0327272727272726
27
+ },
28
+ "TSP": {
29
+ "weighted_accuracy": 0.0109090909090909
30
+ },
31
+ "TSP_D": {
32
+ "weighted_accuracy": 0.0145454545454545
33
+ }
34
+ }
35
+ }
mistralai/Mistral-7B-Instruct-v0.1/results_2024-01-13T14-57-48.json ADDED
@@ -0,0 +1,35 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "config": {
3
+ "model_name": "mistralai/Mistral-7B-Instruct-v0.1",
4
+ "model_type": "pretrained"
5
+ },
6
+ "results": {
7
+ "SAS": {
8
+ "weighted_accuracy": 0.1490909090909086
9
+ },
10
+ "EDP": {
11
+ "weighted_accuracy": 0.058181818181818
12
+ },
13
+ "GCP": {
14
+ "weighted_accuracy": 0.2090909090909085
15
+ },
16
+ "GCP_D": {
17
+ "weighted_accuracy": 0.5799999999999995
18
+ },
19
+ "KSP": {
20
+ "weighted_accuracy": 0.0
21
+ },
22
+ "MSP": {
23
+ "weighted_accuracy": 0.0
24
+ },
25
+ "SPP": {
26
+ "weighted_accuracy": 0.0163636363636363
27
+ },
28
+ "TSP": {
29
+ "weighted_accuracy": 0.0
30
+ },
31
+ "TSP_D": {
32
+ "weighted_accuracy": 0.6272727272727268
33
+ }
34
+ }
35
+ }
mosaicml/mpt-30b-instruct/results_2024-01-13T14-57-48.json ADDED
@@ -0,0 +1,35 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "config": {
3
+ "model_name": "mosaicml/mpt-30b-instruct",
4
+ "model_type": "pretrained"
5
+ },
6
+ "results": {
7
+ "SAS": {
8
+ "weighted_accuracy": 0.0
9
+ },
10
+ "EDP": {
11
+ "weighted_accuracy": 0.0018181818181818
12
+ },
13
+ "GCP": {
14
+ "weighted_accuracy": 0.0
15
+ },
16
+ "GCP_D": {
17
+ "weighted_accuracy": 0.0
18
+ },
19
+ "KSP": {
20
+ "weighted_accuracy": 0.0
21
+ },
22
+ "MSP": {
23
+ "weighted_accuracy": 0.0
24
+ },
25
+ "SPP": {
26
+ "weighted_accuracy": 0.0
27
+ },
28
+ "TSP": {
29
+ "weighted_accuracy": 0.0
30
+ },
31
+ "TSP_D": {
32
+ "weighted_accuracy": 0.0
33
+ }
34
+ }
35
+ }