diff --git "a/data/output_plots.csv" "b/data/output_plots.csv"
--- "a/data/output_plots.csv"
+++ "b/data/output_plots.csv"
@@ -12,7 +12,7 @@ plot_object,header,plot_json,df,arguments,description
'type': 'bar',
'x': array(['Snorkel Mistral PairRM DPO (7B)'], dtype=object),
'xaxis': 'x',
- 'y': array([24.99005381]),
+ 'y': array([19.9867597]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}',
@@ -26,7 +26,7 @@ plot_object,header,plot_json,df,arguments,description
'type': 'bar',
'x': array(['gpt-4'], dtype=object),
'xaxis': 'x',
- 'y': array([17.68367981]),
+ 'y': array([15.98077287]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}',
@@ -40,7 +40,7 @@ plot_object,header,plot_json,df,arguments,description
'type': 'bar',
'x': array(['gpt-4-turbo'], dtype=object),
'xaxis': 'x',
- 'y': array([15.85205264]),
+ 'y': array([14.24463232]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}',
@@ -54,7 +54,7 @@ plot_object,header,plot_json,df,arguments,description
'type': 'bar',
'x': array(['01-ai Yi Chat (34B)'], dtype=object),
'xaxis': 'x',
- 'y': array([10.34810258]),
+ 'y': array([10.99151355]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}',
@@ -68,63 +68,63 @@ plot_object,header,plot_json,df,arguments,description
'type': 'bar',
'x': array(['Chronos Hermes (13B)'], dtype=object),
'xaxis': 'x',
- 'y': array([10.29452815]),
+ 'y': array([8.58972701]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}',
- 'legendgroup': 'Mixtral-8x7B-Instruct-v0.1',
+ 'legendgroup': 'WizardLM v1.2 (13B)',
'marker': {'color': '#19d3f3', 'pattern': {'shape': ''}},
- 'name': 'Mixtral-8x7B-Instruct-v0.1',
- 'offsetgroup': 'Mixtral-8x7B-Instruct-v0.1',
+ 'name': 'WizardLM v1.2 (13B)',
+ 'offsetgroup': 'WizardLM v1.2 (13B)',
'orientation': 'v',
'showlegend': True,
'textposition': 'auto',
'type': 'bar',
- 'x': array(['Mixtral-8x7B-Instruct-v0.1'], dtype=object),
+ 'x': array(['WizardLM v1.2 (13B)'], dtype=object),
'xaxis': 'x',
- 'y': array([6.55972525]),
+ 'y': array([5.86888533]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}',
- 'legendgroup': 'llama-2-70b-chat',
+ 'legendgroup': 'Mixtral-8x7B-Instruct-v0.1',
'marker': {'color': '#FF6692', 'pattern': {'shape': ''}},
- 'name': 'llama-2-70b-chat',
- 'offsetgroup': 'llama-2-70b-chat',
+ 'name': 'Mixtral-8x7B-Instruct-v0.1',
+ 'offsetgroup': 'Mixtral-8x7B-Instruct-v0.1',
'orientation': 'v',
'showlegend': True,
'textposition': 'auto',
'type': 'bar',
- 'x': array(['llama-2-70b-chat'], dtype=object),
+ 'x': array(['Mixtral-8x7B-Instruct-v0.1'], dtype=object),
'xaxis': 'x',
- 'y': array([6.06536523]),
+ 'y': array([5.52183281]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}',
- 'legendgroup': 'WizardLM v1.2 (13B)',
+ 'legendgroup': 'chat-bison-32k (PaLM 2 32K)',
'marker': {'color': '#B6E880', 'pattern': {'shape': ''}},
- 'name': 'WizardLM v1.2 (13B)',
- 'offsetgroup': 'WizardLM v1.2 (13B)',
+ 'name': 'chat-bison-32k (PaLM 2 32K)',
+ 'offsetgroup': 'chat-bison-32k (PaLM 2 32K)',
'orientation': 'v',
'showlegend': True,
'textposition': 'auto',
'type': 'bar',
- 'x': array(['WizardLM v1.2 (13B)'], dtype=object),
+ 'x': array(['chat-bison-32k (PaLM 2 32K)'], dtype=object),
'xaxis': 'x',
- 'y': array([5.50723492]),
+ 'y': array([5.46443628]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}',
- 'legendgroup': 'chat-bison-32k (PaLM 2 32K)',
+ 'legendgroup': 'llama-2-70b-chat',
'marker': {'color': '#FF97FF', 'pattern': {'shape': ''}},
- 'name': 'chat-bison-32k (PaLM 2 32K)',
- 'offsetgroup': 'chat-bison-32k (PaLM 2 32K)',
+ 'name': 'llama-2-70b-chat',
+ 'offsetgroup': 'llama-2-70b-chat',
'orientation': 'v',
'showlegend': True,
'textposition': 'auto',
'type': 'bar',
- 'x': array(['chat-bison-32k (PaLM 2 32K)'], dtype=object),
+ 'x': array(['llama-2-70b-chat'], dtype=object),
'xaxis': 'x',
- 'y': array([5.46443628]),
+ 'y': array([4.80907998]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}',
@@ -138,26 +138,12 @@ plot_object,header,plot_json,df,arguments,description
'type': 'bar',
'x': array(['gpt-3.5-turbo'], dtype=object),
'xaxis': 'x',
- 'y': array([4.59921461]),
- 'yaxis': 'y'},
- {'alignmentgroup': 'True',
- 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}',
- 'legendgroup': 'gemini-pro',
- 'marker': {'color': '#636efa', 'pattern': {'shape': ''}},
- 'name': 'gemini-pro',
- 'offsetgroup': 'gemini-pro',
- 'orientation': 'v',
- 'showlegend': True,
- 'textposition': 'auto',
- 'type': 'bar',
- 'x': array(['gemini-pro'], dtype=object),
- 'xaxis': 'x',
- 'y': array([4.11187035]),
+ 'y': array([4.63821494]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}',
'legendgroup': 'Mistral (7B) Instruct v0.2 (Together AI)',
- 'marker': {'color': '#EF553B', 'pattern': {'shape': ''}},
+ 'marker': {'color': '#636efa', 'pattern': {'shape': ''}},
'name': 'Mistral (7B) Instruct v0.2 (Together AI)',
'offsetgroup': 'Mistral (7B) Instruct v0.2 (Together AI)',
'orientation': 'v',
@@ -166,26 +152,26 @@ plot_object,header,plot_json,df,arguments,description
'type': 'bar',
'x': array(['Mistral (7B) Instruct v0.2 (Together AI)'], dtype=object),
'xaxis': 'x',
- 'y': array([3.9566073]),
+ 'y': array([3.66314562]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}',
- 'legendgroup': 'Vicuna v1.5 (7B)',
- 'marker': {'color': '#00cc96', 'pattern': {'shape': ''}},
- 'name': 'Vicuna v1.5 (7B)',
- 'offsetgroup': 'Vicuna v1.5 (7B)',
+ 'legendgroup': 'gemini-pro',
+ 'marker': {'color': '#EF553B', 'pattern': {'shape': ''}},
+ 'name': 'gemini-pro',
+ 'offsetgroup': 'gemini-pro',
'orientation': 'v',
'showlegend': True,
'textposition': 'auto',
'type': 'bar',
- 'x': array(['Vicuna v1.5 (7B)'], dtype=object),
+ 'x': array(['gemini-pro'], dtype=object),
'xaxis': 'x',
- 'y': array([3.85673946]),
+ 'y': array([3.64548177]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}',
'legendgroup': 'zephyr-7b-beta',
- 'marker': {'color': '#ab63fa', 'pattern': {'shape': ''}},
+ 'marker': {'color': '#00cc96', 'pattern': {'shape': ''}},
'name': 'zephyr-7b-beta',
'offsetgroup': 'zephyr-7b-beta',
'orientation': 'v',
@@ -199,7 +185,7 @@ plot_object,header,plot_json,df,arguments,description
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}',
'legendgroup': 'Mistral-7B-Instruct-v0.2',
- 'marker': {'color': '#FFA15A', 'pattern': {'shape': ''}},
+ 'marker': {'color': '#ab63fa', 'pattern': {'shape': ''}},
'name': 'Mistral-7B-Instruct-v0.2',
'offsetgroup': 'Mistral-7B-Instruct-v0.2',
'orientation': 'v',
@@ -212,22 +198,22 @@ plot_object,header,plot_json,df,arguments,description
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}',
- 'legendgroup': 'LLaMA-2 Chat (7B)',
- 'marker': {'color': '#19d3f3', 'pattern': {'shape': ''}},
- 'name': 'LLaMA-2 Chat (7B)',
- 'offsetgroup': 'LLaMA-2 Chat (7B)',
+ 'legendgroup': 'Vicuna v1.5 (7B)',
+ 'marker': {'color': '#FFA15A', 'pattern': {'shape': ''}},
+ 'name': 'Vicuna v1.5 (7B)',
+ 'offsetgroup': 'Vicuna v1.5 (7B)',
'orientation': 'v',
'showlegend': True,
'textposition': 'auto',
'type': 'bar',
- 'x': array(['LLaMA-2 Chat (7B)'], dtype=object),
+ 'x': array(['Vicuna v1.5 (7B)'], dtype=object),
'xaxis': 'x',
- 'y': array([3.35083223]),
+ 'y': array([3.35936635]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}',
'legendgroup': 'chat-bison (PaLM 2)',
- 'marker': {'color': '#FF6692', 'pattern': {'shape': ''}},
+ 'marker': {'color': '#19d3f3', 'pattern': {'shape': ''}},
'name': 'chat-bison (PaLM 2)',
'offsetgroup': 'chat-bison (PaLM 2)',
'orientation': 'v',
@@ -238,6 +224,20 @@ plot_object,header,plot_json,df,arguments,description
'xaxis': 'x',
'y': array([3.30885241]),
'yaxis': 'y'},
+ {'alignmentgroup': 'True',
+ 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}',
+ 'legendgroup': 'LLaMA-2 Chat (7B)',
+ 'marker': {'color': '#FF6692', 'pattern': {'shape': ''}},
+ 'name': 'LLaMA-2 Chat (7B)',
+ 'offsetgroup': 'LLaMA-2 Chat (7B)',
+ 'orientation': 'v',
+ 'showlegend': True,
+ 'textposition': 'auto',
+ 'type': 'bar',
+ 'x': array(['LLaMA-2 Chat (7B)'], dtype=object),
+ 'xaxis': 'x',
+ 'y': array([2.94143569]),
+ 'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}',
'legendgroup': 'OpenHermes-2.5-Mistral (7B)',
@@ -250,7 +250,7 @@ plot_object,header,plot_json,df,arguments,description
'type': 'bar',
'x': array(['OpenHermes-2.5-Mistral (7B)'], dtype=object),
'xaxis': 'x',
- 'y': array([2.88827331]),
+ 'y': array([2.81202571]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}',
@@ -264,7 +264,7 @@ plot_object,header,plot_json,df,arguments,description
'type': 'bar',
'x': array(['Qwen 1.5 Chat (7B)'], dtype=object),
'xaxis': 'x',
- 'y': array([2.20103282]),
+ 'y': array([2.2973882]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}',
@@ -278,7 +278,7 @@ plot_object,header,plot_json,df,arguments,description
'type': 'bar',
'x': array(['RedPajama-INCITE Chat (7B)'], dtype=object),
'xaxis': 'x',
- 'y': array([1.98214534]),
+ 'y': array([1.7621016]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}',
@@ -292,7 +292,7 @@ plot_object,header,plot_json,df,arguments,description
'type': 'bar',
'x': array(['TinyLlama/TinyLlama-1.1B-Chat-v1.0'], dtype=object),
'xaxis': 'x',
- 'y': array([1.59549656]),
+ 'y': array([1.65637505]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}',
@@ -315,45 +315,45 @@ plot_object,header,plot_json,df,arguments,description
'xaxis': {'anchor': 'y',
'categoryarray': [Snorkel Mistral PairRM DPO (7B), gpt-4,
gpt-4-turbo, 01-ai Yi Chat (34B),
- Chronos Hermes (13B),
- Mixtral-8x7B-Instruct-v0.1,
- llama-2-70b-chat, WizardLM v1.2 (13B),
- chat-bison-32k (PaLM 2 32K),
- gpt-3.5-turbo, gemini-pro, Mistral (7B)
- Instruct v0.2 (Together AI), Vicuna v1.5
- (7B), zephyr-7b-beta,
- Mistral-7B-Instruct-v0.2, LLaMA-2 Chat
- (7B), chat-bison (PaLM 2),
- OpenHermes-2.5-Mistral (7B), Qwen 1.5
- Chat (7B), RedPajama-INCITE Chat (7B),
+ Chronos Hermes (13B), WizardLM v1.2
+ (13B), Mixtral-8x7B-Instruct-v0.1, chat-
+ bison-32k (PaLM 2 32K),
+ llama-2-70b-chat, gpt-3.5-turbo, Mistral
+ (7B) Instruct v0.2 (Together AI),
+ gemini-pro, zephyr-7b-beta,
+ Mistral-7B-Instruct-v0.2, Vicuna v1.5
+ (7B), chat-bison (PaLM 2), LLaMA-2 Chat
+ (7B), OpenHermes-2.5-Mistral (7B), Qwen
+ 1.5 Chat (7B), RedPajama-INCITE Chat
+ (7B),
TinyLlama/TinyLlama-1.1B-Chat-v1.0,
Falcon Instruct (7B)],
'categoryorder': 'array',
'domain': [0.0, 1.0],
'title': {'text': 'Model'}},
'yaxis': {'anchor': 'x', 'domain': [0.0, 1.0], 'title': {'text': 'Execution time (s)'}}}
-})",Plot of execution time given the same input for summarization task,"{""data"":[{""alignmentgroup"":""True"",""hovertemplate"":""Model=%{x}\u003cbr\u003eExecution time (s)=%{y}\u003cextra\u003e\u003c\u002fextra\u003e"",""legendgroup"":""Snorkel Mistral PairRM DPO (7B)"",""marker"":{""color"":""#636efa"",""pattern"":{""shape"":""""}},""name"":""Snorkel Mistral PairRM DPO (7B)"",""offsetgroup"":""Snorkel Mistral PairRM DPO (7B)"",""orientation"":""v"",""showlegend"":true,""textposition"":""auto"",""x"":[""Snorkel Mistral PairRM DPO (7B)""],""xaxis"":""x"",""y"":[24.990053808560074],""yaxis"":""y"",""type"":""bar""},{""alignmentgroup"":""True"",""hovertemplate"":""Model=%{x}\u003cbr\u003eExecution time 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Mistral PairRM DPO (7B)"",""gpt-4"",""gpt-4-turbo"",""01-ai Yi Chat (34B)"",""Chronos Hermes (13B)"",""WizardLM v1.2 (13B)"",""Mixtral-8x7B-Instruct-v0.1"",""chat-bison-32k (PaLM 2 32K)"",""llama-2-70b-chat"",""gpt-3.5-turbo"",""Mistral (7B) Instruct v0.2 (Together AI)"",""gemini-pro"",""zephyr-7b-beta"",""Mistral-7B-Instruct-v0.2"",""Vicuna v1.5 (7B)"",""chat-bison (PaLM 2)"",""LLaMA-2 Chat (7B)"",""OpenHermes-2.5-Mistral (7B)"",""Qwen 1.5 Chat (7B)"",""RedPajama-INCITE Chat (7B)"",""TinyLlama\u002fTinyLlama-1.1B-Chat-v1.0"",""Falcon Instruct (7B)""]},""yaxis"":{""anchor"":""x"",""domain"":[0.0,1.0],""title"":{""text"":""Execution time (s)""}},""legend"":{""title"":{""text"":""Model""},""tracegroupgap"":0},""title"":{""text"":""Plot of execution time given the same input for summarization task""},""barmode"":""relative""}}",",model,execution_time
+10,Snorkel Mistral PairRM DPO (7B),19.986759704265395
+18,gpt-4,15.98077287161498
+19,gpt-4-turbo,14.244632319505602
+0,01-ai Yi Chat (34B),10.991513552391007
+1,Chronos Hermes (13B),8.589727006841095
+13,WizardLM v1.2 (13B),5.868885332229091
+6,Mixtral-8x7B-Instruct-v0.1,5.5218328136697465
15,chat-bison-32k (PaLM 2 32K),5.464436282749687
-17,gpt-3.5-turbo,4.599214611078473
-16,gemini-pro,4.111870346541831
-4,Mistral (7B) Instruct v0.2 (Together AI),3.95660729618315
-12,Vicuna v1.5 (7B),3.8567394597322227
+20,llama-2-70b-chat,4.8090799786202965
+17,gpt-3.5-turbo,4.638214940246723
+4,Mistral (7B) Instruct v0.2 (Together AI),3.6631456230179738
+16,gemini-pro,3.645481765456671
21,zephyr-7b-beta,3.5767457232334547
5,Mistral-7B-Instruct-v0.2,3.386921099240709
-3,LLaMA-2 Chat (7B),3.3508322324998163
+12,Vicuna v1.5 (7B),3.35936635421319
14,chat-bison (PaLM 2),3.3088524077087644
-7,OpenHermes-2.5-Mistral (7B),2.888273307162782
-8,Qwen 1.5 Chat (7B),2.201032818057145
-9,RedPajama-INCITE Chat (7B),1.9821453389905843
-11,TinyLlama/TinyLlama-1.1B-Chat-v1.0,1.5954965559732053
+3,LLaMA-2 Chat (7B),2.941435688511993
+7,OpenHermes-2.5-Mistral (7B),2.812025713575059
+8,Qwen 1.5 Chat (7B),2.2973882044010723
+9,RedPajama-INCITE Chat (7B),1.7621016023810012
+11,TinyLlama/TinyLlama-1.1B-Chat-v1.0,1.6563750527772214
2,Falcon Instruct (7B),1.3390633107409045
","{""x"": ""model"", ""y"": ""execution_time"", ""color"": ""model"", ""labels"": {""model"": ""Model"", ""execution_time"": ""Execution time (s)""}, ""title"": ""Plot of execution time given the same input for summarization task""}","This plot shows averaged response time for one query for each model.
@@ -373,7 +373,7 @@ It is also important to note that we used litellm python library for all of the
'type': 'bar',
'x': array(['Snorkel Mistral PairRM DPO (7B)'], dtype=object),
'xaxis': 'x',
- 'y': array([216.81729501]),
+ 'y': array([231.74486334]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Output words count=%{y}',
@@ -387,7 +387,7 @@ It is also important to note that we used litellm python library for all of the
'type': 'bar',
'x': array(['llama-2-70b-chat'], dtype=object),
'xaxis': 'x',
- 'y': array([95.35066814]),
+ 'y': array([84.28377876]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Output words count=%{y}',
@@ -401,7 +401,7 @@ It is also important to note that we used litellm python library for all of the
'type': 'bar',
'x': array(['Chronos Hermes (13B)'], dtype=object),
'xaxis': 'x',
- 'y': array([71.56112097]),
+ 'y': array([74.84074732]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Output words count=%{y}',
@@ -415,7 +415,7 @@ It is also important to note that we used litellm python library for all of the
'type': 'bar',
'x': array(['Mistral (7B) Instruct v0.2 (Together AI)'], dtype=object),
'xaxis': 'x',
- 'y': array([68.1734857]),
+ 'y': array([73.7573238]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Output words count=%{y}',
@@ -429,49 +429,49 @@ It is also important to note that we used litellm python library for all of the
'type': 'bar',
'x': array(['LLaMA-2 Chat (7B)'], dtype=object),
'xaxis': 'x',
- 'y': array([62.66994559]),
+ 'y': array([66.83829706]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Output words count=%{y}',
- 'legendgroup': 'Mixtral-8x7B-Instruct-v0.1',
+ 'legendgroup': '01-ai Yi Chat (34B)',
'marker': {'color': '#19d3f3', 'pattern': {'shape': ''}},
- 'name': 'Mixtral-8x7B-Instruct-v0.1',
- 'offsetgroup': 'Mixtral-8x7B-Instruct-v0.1',
+ 'name': '01-ai Yi Chat (34B)',
+ 'offsetgroup': '01-ai Yi Chat (34B)',
'orientation': 'v',
'showlegend': True,
'textposition': 'auto',
'type': 'bar',
- 'x': array(['Mixtral-8x7B-Instruct-v0.1'], dtype=object),
+ 'x': array(['01-ai Yi Chat (34B)'], dtype=object),
'xaxis': 'x',
- 'y': array([54.16817689]),
+ 'y': array([64.86385624]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Output words count=%{y}',
- 'legendgroup': '01-ai Yi Chat (34B)',
+ 'legendgroup': 'Mixtral-8x7B-Instruct-v0.1',
'marker': {'color': '#FF6692', 'pattern': {'shape': ''}},
- 'name': '01-ai Yi Chat (34B)',
- 'offsetgroup': '01-ai Yi Chat (34B)',
+ 'name': 'Mixtral-8x7B-Instruct-v0.1',
+ 'offsetgroup': 'Mixtral-8x7B-Instruct-v0.1',
'orientation': 'v',
'showlegend': True,
'textposition': 'auto',
'type': 'bar',
- 'x': array(['01-ai Yi Chat (34B)'], dtype=object),
+ 'x': array(['Mixtral-8x7B-Instruct-v0.1'], dtype=object),
'xaxis': 'x',
- 'y': array([44.25828436]),
+ 'y': array([62.02878459]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Output words count=%{y}',
- 'legendgroup': 'chat-bison (PaLM 2)',
+ 'legendgroup': 'WizardLM v1.2 (13B)',
'marker': {'color': '#B6E880', 'pattern': {'shape': ''}},
- 'name': 'chat-bison (PaLM 2)',
- 'offsetgroup': 'chat-bison (PaLM 2)',
+ 'name': 'WizardLM v1.2 (13B)',
+ 'offsetgroup': 'WizardLM v1.2 (13B)',
'orientation': 'v',
'showlegend': True,
'textposition': 'auto',
'type': 'bar',
- 'x': array(['chat-bison (PaLM 2)'], dtype=object),
+ 'x': array(['WizardLM v1.2 (13B)'], dtype=object),
'xaxis': 'x',
- 'y': array([40.9371875]),
+ 'y': array([54.62341982]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Output words count=%{y}',
@@ -485,77 +485,77 @@ It is also important to note that we used litellm python library for all of the
'type': 'bar',
'x': array(['gemini-pro'], dtype=object),
'xaxis': 'x',
- 'y': array([39.69346182]),
+ 'y': array([49.23743043]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Output words count=%{y}',
- 'legendgroup': 'gpt-3.5-turbo',
+ 'legendgroup': 'Qwen 1.5 Chat (7B)',
'marker': {'color': '#FECB52', 'pattern': {'shape': ''}},
- 'name': 'gpt-3.5-turbo',
- 'offsetgroup': 'gpt-3.5-turbo',
+ 'name': 'Qwen 1.5 Chat (7B)',
+ 'offsetgroup': 'Qwen 1.5 Chat (7B)',
'orientation': 'v',
'showlegend': True,
'textposition': 'auto',
'type': 'bar',
- 'x': array(['gpt-3.5-turbo'], dtype=object),
+ 'x': array(['Qwen 1.5 Chat (7B)'], dtype=object),
'xaxis': 'x',
- 'y': array([39.25851284]),
+ 'y': array([45.20889867]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Output words count=%{y}',
- 'legendgroup': 'chat-bison-32k (PaLM 2 32K)',
+ 'legendgroup': 'Vicuna v1.5 (7B)',
'marker': {'color': '#636efa', 'pattern': {'shape': ''}},
- 'name': 'chat-bison-32k (PaLM 2 32K)',
- 'offsetgroup': 'chat-bison-32k (PaLM 2 32K)',
+ 'name': 'Vicuna v1.5 (7B)',
+ 'offsetgroup': 'Vicuna v1.5 (7B)',
'orientation': 'v',
'showlegend': True,
'textposition': 'auto',
'type': 'bar',
- 'x': array(['chat-bison-32k (PaLM 2 32K)'], dtype=object),
+ 'x': array(['Vicuna v1.5 (7B)'], dtype=object),
'xaxis': 'x',
- 'y': array([38.72477679]),
+ 'y': array([44.23524076]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Output words count=%{y}',
- 'legendgroup': 'gpt-4-turbo',
+ 'legendgroup': 'gpt-3.5-turbo',
'marker': {'color': '#EF553B', 'pattern': {'shape': ''}},
- 'name': 'gpt-4-turbo',
- 'offsetgroup': 'gpt-4-turbo',
+ 'name': 'gpt-3.5-turbo',
+ 'offsetgroup': 'gpt-3.5-turbo',
'orientation': 'v',
'showlegend': True,
'textposition': 'auto',
'type': 'bar',
- 'x': array(['gpt-4-turbo'], dtype=object),
+ 'x': array(['gpt-3.5-turbo'], dtype=object),
'xaxis': 'x',
- 'y': array([38.36012473]),
+ 'y': array([43.083453]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Output words count=%{y}',
- 'legendgroup': 'Vicuna v1.5 (7B)',
+ 'legendgroup': 'OpenHermes-2.5-Mistral (7B)',
'marker': {'color': '#00cc96', 'pattern': {'shape': ''}},
- 'name': 'Vicuna v1.5 (7B)',
- 'offsetgroup': 'Vicuna v1.5 (7B)',
+ 'name': 'OpenHermes-2.5-Mistral (7B)',
+ 'offsetgroup': 'OpenHermes-2.5-Mistral (7B)',
'orientation': 'v',
'showlegend': True,
'textposition': 'auto',
'type': 'bar',
- 'x': array(['Vicuna v1.5 (7B)'], dtype=object),
+ 'x': array(['OpenHermes-2.5-Mistral (7B)'], dtype=object),
'xaxis': 'x',
- 'y': array([36.52786114]),
+ 'y': array([42.84559302]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Output words count=%{y}',
- 'legendgroup': 'WizardLM v1.2 (13B)',
+ 'legendgroup': 'chat-bison (PaLM 2)',
'marker': {'color': '#ab63fa', 'pattern': {'shape': ''}},
- 'name': 'WizardLM v1.2 (13B)',
- 'offsetgroup': 'WizardLM v1.2 (13B)',
+ 'name': 'chat-bison (PaLM 2)',
+ 'offsetgroup': 'chat-bison (PaLM 2)',
'orientation': 'v',
'showlegend': True,
'textposition': 'auto',
'type': 'bar',
- 'x': array(['WizardLM v1.2 (13B)'], dtype=object),
+ 'x': array(['chat-bison (PaLM 2)'], dtype=object),
'xaxis': 'x',
- 'y': array([33.48512973]),
+ 'y': array([40.9371875]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Output words count=%{y}',
@@ -569,63 +569,63 @@ It is also important to note that we used litellm python library for all of the
'type': 'bar',
'x': array(['gpt-4'], dtype=object),
'xaxis': 'x',
- 'y': array([32.90737496]),
+ 'y': array([40.80491664]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Output words count=%{y}',
- 'legendgroup': 'OpenHermes-2.5-Mistral (7B)',
+ 'legendgroup': 'gpt-4-turbo',
'marker': {'color': '#19d3f3', 'pattern': {'shape': ''}},
- 'name': 'OpenHermes-2.5-Mistral (7B)',
- 'offsetgroup': 'OpenHermes-2.5-Mistral (7B)',
+ 'name': 'gpt-4-turbo',
+ 'offsetgroup': 'gpt-4-turbo',
'orientation': 'v',
'showlegend': True,
'textposition': 'auto',
'type': 'bar',
- 'x': array(['OpenHermes-2.5-Mistral (7B)'], dtype=object),
+ 'x': array(['gpt-4-turbo'], dtype=object),
'xaxis': 'x',
- 'y': array([32.78088953]),
+ 'y': array([40.57897205]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
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- 'legendgroup': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0',
+ 'legendgroup': 'chat-bison-32k (PaLM 2 32K)',
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- 'name': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0',
- 'offsetgroup': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0',
+ 'name': 'chat-bison-32k (PaLM 2 32K)',
+ 'offsetgroup': 'chat-bison-32k (PaLM 2 32K)',
'orientation': 'v',
'showlegend': True,
'textposition': 'auto',
'type': 'bar',
- 'x': array(['TinyLlama/TinyLlama-1.1B-Chat-v1.0'], dtype=object),
+ 'x': array(['chat-bison-32k (PaLM 2 32K)'], dtype=object),
'xaxis': 'x',
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+ 'y': array([38.72477679]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Output words count=%{y}',
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+ 'legendgroup': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0',
'marker': {'color': '#B6E880', 'pattern': {'shape': ''}},
- 'name': 'zephyr-7b-beta',
- 'offsetgroup': 'zephyr-7b-beta',
+ 'name': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0',
+ 'offsetgroup': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0',
'orientation': 'v',
'showlegend': True,
'textposition': 'auto',
'type': 'bar',
- 'x': array(['zephyr-7b-beta'], dtype=object),
+ 'x': array(['TinyLlama/TinyLlama-1.1B-Chat-v1.0'], dtype=object),
'xaxis': 'x',
- 'y': array([32.25400169]),
+ 'y': array([36.08376437]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Output words count=%{y}',
- 'legendgroup': 'Qwen 1.5 Chat (7B)',
+ 'legendgroup': 'zephyr-7b-beta',
'marker': {'color': '#FF97FF', 'pattern': {'shape': ''}},
- 'name': 'Qwen 1.5 Chat (7B)',
- 'offsetgroup': 'Qwen 1.5 Chat (7B)',
+ 'name': 'zephyr-7b-beta',
+ 'offsetgroup': 'zephyr-7b-beta',
'orientation': 'v',
'showlegend': True,
'textposition': 'auto',
'type': 'bar',
- 'x': array(['Qwen 1.5 Chat (7B)'], dtype=object),
+ 'x': array(['zephyr-7b-beta'], dtype=object),
'xaxis': 'x',
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+ 'y': array([32.25400169]),
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@@ -667,7 +667,7 @@ It is also important to note that we used litellm python library for all of the
'type': 'bar',
'x': array(['RedPajama-INCITE Chat (7B)'], dtype=object),
'xaxis': 'x',
- 'y': array([5.2095088]),
+ 'y': array([5.3563392]),
'yaxis': 'y'}],
'layout': {'barmode': 'relative',
'legend': {'title': {'text': 'Model'}, 'tracegroupgap': 0},
@@ -677,15 +677,16 @@ It is also important to note that we used litellm python library for all of the
'categoryarray': [Snorkel Mistral PairRM DPO (7B),
llama-2-70b-chat, Chronos Hermes (13B),
Mistral (7B) Instruct v0.2 (Together
- AI), LLaMA-2 Chat (7B),
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- Chat (34B), chat-bison (PaLM 2), gemini-
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- 2 32K), gpt-4-turbo, Vicuna v1.5 (7B),
- WizardLM v1.2 (13B), gpt-4,
- OpenHermes-2.5-Mistral (7B),
+ AI), LLaMA-2 Chat (7B), 01-ai Yi Chat
+ (34B), Mixtral-8x7B-Instruct-v0.1,
+ WizardLM v1.2 (13B), gemini-pro, Qwen
+ 1.5 Chat (7B), Vicuna v1.5 (7B),
+ gpt-3.5-turbo, OpenHermes-2.5-Mistral
+ (7B), chat-bison (PaLM 2), gpt-4,
+ gpt-4-turbo, chat-bison-32k (PaLM 2
+ 32K),
TinyLlama/TinyLlama-1.1B-Chat-v1.0,
- zephyr-7b-beta, Qwen 1.5 Chat (7B),
+ zephyr-7b-beta,
Mistral-7B-Instruct-v0.2, Falcon
Instruct (7B), RedPajama-INCITE Chat
(7B)],
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'domain': [0.0, 1.0],
'title': {'text': 'Model'}},
'yaxis': {'anchor': 'x', 'domain': [0.0, 1.0], 'title': {'text': 'Output words count'}}}
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'type': 'bar',
- 'x': array(['llama-2-70b-chat'], dtype=object),
+ 'x': array(['TinyLlama/TinyLlama-1.1B-Chat-v1.0'], dtype=object),
'xaxis': 'x',
- 'y': array([3.20032418]),
+ 'y': array([3.2040858]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}',
@@ -800,189 +801,189 @@ It is also important to note that we used litellm python library for all of the
'type': 'bar',
'x': array(['RedPajama-INCITE Chat (7B)'], dtype=object),
'xaxis': 'x',
- 'y': array([3.15892476]),
+ 'y': array([3.17327871]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}',
- 'legendgroup': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0',
+ 'legendgroup': 'llama-2-70b-chat',
'marker': {'color': '#FF6692', 'pattern': {'shape': ''}},
- 'name': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0',
- 'offsetgroup': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0',
+ 'name': 'llama-2-70b-chat',
+ 'offsetgroup': 'llama-2-70b-chat',
'orientation': 'v',
'showlegend': True,
'textposition': 'auto',
'type': 'bar',
- 'x': array(['TinyLlama/TinyLlama-1.1B-Chat-v1.0'], dtype=object),
+ 'x': array(['llama-2-70b-chat'], dtype=object),
'xaxis': 'x',
- 'y': array([3.14663951]),
+ 'y': array([2.99479736]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}',
- 'legendgroup': 'gpt-3.5-turbo',
+ 'legendgroup': 'Mixtral-8x7B-Instruct-v0.1',
'marker': {'color': '#B6E880', 'pattern': {'shape': ''}},
- 'name': 'gpt-3.5-turbo',
- 'offsetgroup': 'gpt-3.5-turbo',
+ 'name': 'Mixtral-8x7B-Instruct-v0.1',
+ 'offsetgroup': 'Mixtral-8x7B-Instruct-v0.1',
'orientation': 'v',
'showlegend': True,
'textposition': 'auto',
'type': 'bar',
- 'x': array(['gpt-3.5-turbo'], dtype=object),
+ 'x': array(['Mixtral-8x7B-Instruct-v0.1'], dtype=object),
'xaxis': 'x',
- 'y': array([3.04399416]),
+ 'y': array([2.81103164]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}',
- 'legendgroup': 'gpt-4',
+ 'legendgroup': 'LLaMA-2 Chat (7B)',
'marker': {'color': '#FF97FF', 'pattern': {'shape': ''}},
- 'name': 'gpt-4',
- 'offsetgroup': 'gpt-4',
+ 'name': 'LLaMA-2 Chat (7B)',
+ 'offsetgroup': 'LLaMA-2 Chat (7B)',
'orientation': 'v',
'showlegend': True,
'textposition': 'auto',
'type': 'bar',
- 'x': array(['gpt-4'], dtype=object),
+ 'x': array(['LLaMA-2 Chat (7B)'], dtype=object),
'xaxis': 'x',
- 'y': array([3.01875517]),
+ 'y': array([2.7218178]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}',
- 'legendgroup': 'gpt-4-turbo',
+ 'legendgroup': 'zephyr-7b-beta',
'marker': {'color': '#FECB52', 'pattern': {'shape': ''}},
- 'name': 'gpt-4-turbo',
- 'offsetgroup': 'gpt-4-turbo',
+ 'name': 'zephyr-7b-beta',
+ 'offsetgroup': 'zephyr-7b-beta',
'orientation': 'v',
'showlegend': True,
'textposition': 'auto',
'type': 'bar',
- 'x': array(['gpt-4-turbo'], dtype=object),
+ 'x': array(['zephyr-7b-beta'], dtype=object),
'xaxis': 'x',
- 'y': array([3.0126559]),
+ 'y': array([2.70854999]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}',
- 'legendgroup': 'Mixtral-8x7B-Instruct-v0.1',
+ 'legendgroup': 'Mistral-7B-Instruct-v0.2',
'marker': {'color': '#636efa', 'pattern': {'shape': ''}},
- 'name': 'Mixtral-8x7B-Instruct-v0.1',
- 'offsetgroup': 'Mixtral-8x7B-Instruct-v0.1',
+ 'name': 'Mistral-7B-Instruct-v0.2',
+ 'offsetgroup': 'Mistral-7B-Instruct-v0.2',
'orientation': 'v',
'showlegend': True,
'textposition': 'auto',
'type': 'bar',
- 'x': array(['Mixtral-8x7B-Instruct-v0.1'], dtype=object),
+ 'x': array(['Mistral-7B-Instruct-v0.2'], dtype=object),
'xaxis': 'x',
- 'y': array([2.95880337]),
+ 'y': array([2.64769775]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}',
- 'legendgroup': 'LLaMA-2 Chat (7B)',
+ 'legendgroup': 'Chronos Hermes (13B)',
'marker': {'color': '#EF553B', 'pattern': {'shape': ''}},
- 'name': 'LLaMA-2 Chat (7B)',
- 'offsetgroup': 'LLaMA-2 Chat (7B)',
+ 'name': 'Chronos Hermes (13B)',
+ 'offsetgroup': 'Chronos Hermes (13B)',
'orientation': 'v',
'showlegend': True,
'textposition': 'auto',
'type': 'bar',
- 'x': array(['LLaMA-2 Chat (7B)'], dtype=object),
+ 'x': array(['Chronos Hermes (13B)'], dtype=object),
'xaxis': 'x',
- 'y': array([2.77311537]),
+ 'y': array([2.64238254]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}',
- 'legendgroup': 'Qwen 1.5 Chat (7B)',
+ 'legendgroup': 'gpt-3.5-turbo',
'marker': {'color': '#00cc96', 'pattern': {'shape': ''}},
- 'name': 'Qwen 1.5 Chat (7B)',
- 'offsetgroup': 'Qwen 1.5 Chat (7B)',
+ 'name': 'gpt-3.5-turbo',
+ 'offsetgroup': 'gpt-3.5-turbo',
'orientation': 'v',
'showlegend': True,
'textposition': 'auto',
'type': 'bar',
- 'x': array(['Qwen 1.5 Chat (7B)'], dtype=object),
+ 'x': array(['gpt-3.5-turbo'], dtype=object),
'xaxis': 'x',
- 'y': array([2.75041217]),
+ 'y': array([2.62098816]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}',
- 'legendgroup': 'Snorkel Mistral PairRM DPO (7B)',
+ 'legendgroup': 'gpt-4-turbo',
'marker': {'color': '#ab63fa', 'pattern': {'shape': ''}},
- 'name': 'Snorkel Mistral PairRM DPO (7B)',
- 'offsetgroup': 'Snorkel Mistral PairRM DPO (7B)',
+ 'name': 'gpt-4-turbo',
+ 'offsetgroup': 'gpt-4-turbo',
'orientation': 'v',
'showlegend': True,
'textposition': 'auto',
'type': 'bar',
- 'x': array(['Snorkel Mistral PairRM DPO (7B)'], dtype=object),
+ 'x': array(['gpt-4-turbo'], dtype=object),
'xaxis': 'x',
- 'y': array([2.71229258]),
+ 'y': array([2.59991471]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}',
- 'legendgroup': 'zephyr-7b-beta',
+ 'legendgroup': 'gpt-4',
'marker': {'color': '#FFA15A', 'pattern': {'shape': ''}},
- 'name': 'zephyr-7b-beta',
- 'offsetgroup': 'zephyr-7b-beta',
+ 'name': 'gpt-4',
+ 'offsetgroup': 'gpt-4',
'orientation': 'v',
'showlegend': True,
'textposition': 'auto',
'type': 'bar',
- 'x': array(['zephyr-7b-beta'], dtype=object),
+ 'x': array(['gpt-4'], dtype=object),
'xaxis': 'x',
- 'y': array([2.70854999]),
+ 'y': array([2.59580904]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}',
- 'legendgroup': 'Chronos Hermes (13B)',
+ 'legendgroup': 'Snorkel Mistral PairRM DPO (7B)',
'marker': {'color': '#19d3f3', 'pattern': {'shape': ''}},
- 'name': 'Chronos Hermes (13B)',
- 'offsetgroup': 'Chronos Hermes (13B)',
+ 'name': 'Snorkel Mistral PairRM DPO (7B)',
+ 'offsetgroup': 'Snorkel Mistral PairRM DPO (7B)',
'orientation': 'v',
'showlegend': True,
'textposition': 'auto',
'type': 'bar',
- 'x': array(['Chronos Hermes (13B)'], dtype=object),
+ 'x': array(['Snorkel Mistral PairRM DPO (7B)'], dtype=object),
'xaxis': 'x',
- 'y': array([2.69286913]),
+ 'y': array([2.57228422]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}',
- 'legendgroup': 'Mistral-7B-Instruct-v0.2',
+ 'legendgroup': 'Mistral (7B) Instruct v0.2 (Together AI)',
'marker': {'color': '#FF6692', 'pattern': {'shape': ''}},
- 'name': 'Mistral-7B-Instruct-v0.2',
- 'offsetgroup': 'Mistral-7B-Instruct-v0.2',
+ 'name': 'Mistral (7B) Instruct v0.2 (Together AI)',
+ 'offsetgroup': 'Mistral (7B) Instruct v0.2 (Together AI)',
'orientation': 'v',
'showlegend': True,
'textposition': 'auto',
'type': 'bar',
- 'x': array(['Mistral-7B-Instruct-v0.2'], dtype=object),
+ 'x': array(['Mistral (7B) Instruct v0.2 (Together AI)'], dtype=object),
'xaxis': 'x',
- 'y': array([2.64769775]),
+ 'y': array([2.55559184]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}',
- 'legendgroup': 'Mistral (7B) Instruct v0.2 (Together AI)',
+ 'legendgroup': 'Qwen 1.5 Chat (7B)',
'marker': {'color': '#B6E880', 'pattern': {'shape': ''}},
- 'name': 'Mistral (7B) Instruct v0.2 (Together AI)',
- 'offsetgroup': 'Mistral (7B) Instruct v0.2 (Together AI)',
+ 'name': 'Qwen 1.5 Chat (7B)',
+ 'offsetgroup': 'Qwen 1.5 Chat (7B)',
'orientation': 'v',
'showlegend': True,
'textposition': 'auto',
'type': 'bar',
- 'x': array(['Mistral (7B) Instruct v0.2 (Together AI)'], dtype=object),
+ 'x': array(['Qwen 1.5 Chat (7B)'], dtype=object),
'xaxis': 'x',
- 'y': array([2.63474314]),
+ 'y': array([2.49843277]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}',
- 'legendgroup': '01-ai Yi Chat (34B)',
+ 'legendgroup': 'Vicuna v1.5 (7B)',
'marker': {'color': '#FF97FF', 'pattern': {'shape': ''}},
- 'name': '01-ai Yi Chat (34B)',
- 'offsetgroup': '01-ai Yi Chat (34B)',
+ 'name': 'Vicuna v1.5 (7B)',
+ 'offsetgroup': 'Vicuna v1.5 (7B)',
'orientation': 'v',
'showlegend': True,
'textposition': 'auto',
'type': 'bar',
- 'x': array(['01-ai Yi Chat (34B)'], dtype=object),
+ 'x': array(['Vicuna v1.5 (7B)'], dtype=object),
'xaxis': 'x',
- 'y': array([2.5995706]),
+ 'y': array([2.42986939]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}',
@@ -996,21 +997,21 @@ It is also important to note that we used litellm python library for all of the
'type': 'bar',
'x': array(['OpenHermes-2.5-Mistral (7B)'], dtype=object),
'xaxis': 'x',
- 'y': array([2.4002878]),
+ 'y': array([2.3836649]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}',
- 'legendgroup': 'Vicuna v1.5 (7B)',
+ 'legendgroup': '01-ai Yi Chat (34B)',
'marker': {'color': '#636efa', 'pattern': {'shape': ''}},
- 'name': 'Vicuna v1.5 (7B)',
- 'offsetgroup': 'Vicuna v1.5 (7B)',
+ 'name': '01-ai Yi Chat (34B)',
+ 'offsetgroup': '01-ai Yi Chat (34B)',
'orientation': 'v',
'showlegend': True,
'textposition': 'auto',
'type': 'bar',
- 'x': array(['Vicuna v1.5 (7B)'], dtype=object),
+ 'x': array(['01-ai Yi Chat (34B)'], dtype=object),
'xaxis': 'x',
- 'y': array([2.36590999]),
+ 'y': array([2.35026191]),
'yaxis': 'y'},
{'alignmentgroup': 'True',
'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}',
@@ -1024,7 +1025,7 @@ It is also important to note that we used litellm python library for all of the
'type': 'bar',
'x': array(['WizardLM v1.2 (13B)'], dtype=object),
'xaxis': 'x',
- 'y': array([2.32204331]),
+ 'y': array([2.27685339]),
'yaxis': 'y'}],
'layout': {'barmode': 'relative',
'legend': {'title': {'text': 'Model'}, 'tracegroupgap': 0},
@@ -1033,43 +1034,44 @@ It is also important to note that we used litellm python library for all of the
'xaxis': {'anchor': 'y',
'categoryarray': [gemini-pro, chat-bison (PaLM 2), chat-
bison-32k (PaLM 2 32K), Falcon Instruct
- (7B), llama-2-70b-chat, RedPajama-INCITE
- Chat (7B),
+ (7B),
TinyLlama/TinyLlama-1.1B-Chat-v1.0,
- gpt-3.5-turbo, gpt-4, gpt-4-turbo,
+ RedPajama-INCITE Chat (7B),
+ llama-2-70b-chat,
Mixtral-8x7B-Instruct-v0.1, LLaMA-2 Chat
- (7B), Qwen 1.5 Chat (7B), Snorkel
- Mistral PairRM DPO (7B), zephyr-7b-beta,
- Chronos Hermes (13B),
- Mistral-7B-Instruct-v0.2, Mistral (7B)
- Instruct v0.2 (Together AI), 01-ai Yi
- Chat (34B), OpenHermes-2.5-Mistral (7B),
- Vicuna v1.5 (7B), WizardLM v1.2 (13B)],
+ (7B), zephyr-7b-beta,
+ Mistral-7B-Instruct-v0.2, Chronos Hermes
+ (13B), gpt-3.5-turbo, gpt-4-turbo,
+ gpt-4, Snorkel Mistral PairRM DPO (7B),
+ Mistral (7B) Instruct v0.2 (Together
+ AI), Qwen 1.5 Chat (7B), Vicuna v1.5
+ (7B), OpenHermes-2.5-Mistral (7B), 01-ai
+ Yi Chat (34B), WizardLM v1.2 (13B)],
'categoryorder': 'array',
'domain': [0.0, 1.0],
'title': {'text': 'Model'}},
'yaxis': {'anchor': 'x', 'domain': [0.0, 1.0], 'title': {'text': 'Chunks mean size (characters)'}}}
-})",Plot of chunks mean size given the same input for summarization task,"{""data"":[{""alignmentgroup"":""True"",""hovertemplate"":""Model=%{x}\u003cbr\u003eChunks mean size (characters)=%{y}\u003cextra\u003e\u003c\u002fextra\u003e"",""legendgroup"":""gemini-pro"",""marker"":{""color"":""#636efa"",""pattern"":{""shape"":""""}},""name"":""gemini-pro"",""offsetgroup"":""gemini-pro"",""orientation"":""v"",""showlegend"":true,""textposition"":""auto"",""x"":[""gemini-pro""],""xaxis"":""x"",""y"":[142.5030152620613],""yaxis"":""y"",""type"":""bar""},{""alignmentgroup"":""True"",""hovertemplate"":""Model=%{x}\u003cbr\u003eChunks mean size (characters)=%{y}\u003cextra\u003e\u003c\u002fextra\u003e"",""legendgroup"":""chat-bison (PaLM 2)"",""marker"":{""color"":""#EF553B"",""pattern"":{""shape"":""""}},""name"":""chat-bison (PaLM 2)"",""offsetgroup"":""chat-bison (PaLM 2)"",""orientation"":""v"",""showlegend"":true,""textposition"":""auto"",""x"":[""chat-bison (PaLM 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