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Build error

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dh-mc commited on Sep 27, 2024

Commit

11f2c15

1 Parent(s): 8410e14

fix bug in perf calc

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data/Llama3.1-70B-Chinese-Chat_metrics.csv +11 -11
data/Llama3.1-70B-Chinese-Chat_results.csv +0 -0
data/Llama3.1-70B-Chinese-Chat_shots_metrics.csv +5 -5
data/Llama3.1-8B-Chinese-Chat_metrics.csv +11 -11
data/Llama3.1-8B-Chinese-Chat_results.csv +0 -0
data/Llama3.1-8B-Chinese-Chat_shots_metrics.csv +7 -7
data/Mistral-7B-v0.3-Chinese-Chat_metrics.csv +11 -11
data/Mistral-7B-v0.3-Chinese-Chat_results.csv +0 -0
data/Mistral-7B-v0.3-Chinese-Chat_shots_metrics.csv +6 -6
data/Qwen2-72B-Instruct_metrics.csv +11 -11
data/Qwen2-72B-Instruct_shots_metrics.csv +1 -1
data/Qwen2-7B-Instruct_metrics.csv +11 -11
data/Qwen2-7B-Instruct_shots_metrics.csv +2 -2
data/Qwen2.5-0.5B-Instruct_metrics.csv +11 -11
data/Qwen2.5-0.5B-Instruct_results.csv +0 -0
data/Qwen2.5-0.5B-Instruct_shots_metrics.csv +7 -7
data/Qwen2.5-1.5B-Instruct_metrics.csv +1 -1
data/Qwen2.5-1.5B-Instruct_results.csv +0 -0
data/Qwen2.5-1.5B-Instruct_shots_metrics.csv +1 -1
data/Qwen2.5-3B-Instruct_metrics.csv +11 -11
data/Qwen2.5-3B-Instruct_results.csv +0 -0
data/Qwen2.5-3B-Instruct_shots_metrics.csv +7 -7
data/Qwen2.5-72B-Instruct_metrics.csv +11 -11
data/Qwen2.5-72B-Instruct_results.csv +0 -0
data/Qwen2.5-72B-Instruct_shots_metrics.csv +3 -2
data/Qwen2.5-7B-Instruct_results.csv +0 -0
data/best_metrics.csv +17 -15
data/best_results.csv +0 -0
data/few-shots_metrics.csv +74 -84
data/fine-tuning_metrics.csv +110 -110
data/internlm2_5-20b-chat_metrics.csv +11 -11
data/internlm2_5-20b-chat_results.csv +0 -0
data/internlm2_5-20b-chat_shots_metrics.csv +1 -1
data/internlm2_5-7b-chat-1m_metrics.csv +11 -11
data/internlm2_5-7b-chat-1m_results.csv +0 -0
data/internlm2_5-7b-chat-1m_shots_metrics.csv +7 -7
data/internlm2_5-7b-chat_metrics.csv +11 -11
data/internlm2_5-7b-chat_results.csv +0 -0
data/internlm2_5-7b-chat_shots_metrics.csv +7 -7
data/openai_metrics.csv +28 -28
data/openai_results.csv +0 -0
datasets/mgtv/dev.csv +0 -3
datasets/mgtv/val.csv +0 -0
notebooks/00_Data Analysis.ipynb +2 -2
notebooks/01a_internlm2_5-20b-chat_analysis.ipynb +2 -2
notebooks/01a_internlm2_5-7b-chat-1m_analysis.ipynb +2 -2
notebooks/01a_internlm2_5-7b-chat_analysis.ipynb +2 -2
notebooks/01b_Mistral-7B-v0.3-Chinese-Chat_analysis.ipynb +2 -2
notebooks/02a_Qwen2-7B-Instruct_analysis.ipynb +2 -2
notebooks/02b_Qwen2-72B-Instruct_analysis.ipynb +2 -2

data/Llama3.1-70B-Chinese-Chat_metrics.csv CHANGED Viewed

@@ -1,12 +1,12 @@
 epoch,model,run,accuracy,precision,recall,f1,ratio_valid_classifications
-0.0,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat_torch.bfloat16_4bit_lf,0.7646666666666667,0.7804609488644828,0.7646666666666667,0.7497548621711109,0.009666666666666667
-0.2,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/checkpoint-35_torch.bfloat16_4bit_lf,0.784,0.8105343792887019,0.784,0.7931742141608462,0.9996666666666667
-0.4,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/checkpoint-70_torch.bfloat16_4bit_lf,0.7426666666666667,0.8117033235947096,0.7426666666666667,0.7673825750808414,1.0
-0.6,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/checkpoint-105_torch.bfloat16_4bit_lf,0.736,0.8227236574891071,0.736,0.7650739090144549,1.0
-0.8,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/checkpoint-140_torch.bfloat16_4bit_lf,0.7686666666666667,0.8259659464402258,0.7686666666666667,0.7880870865039342,1.0
-1.0,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/checkpoint-175_torch.bfloat16_4bit_lf,0.809,0.8282732906153989,0.809,0.8166997776775797,1.0
-1.2,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/checkpoint-210_torch.bfloat16_4bit_lf,0.75,0.8287348768409003,0.75,0.7741734526674708,1.0
-1.4,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/checkpoint-245_torch.bfloat16_4bit_lf,0.7703333333333333,0.8271894042316865,0.7703333333333333,0.7907617274354051,1.0
-1.6,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/checkpoint-280_torch.bfloat16_4bit_lf,0.776,0.8315436250878178,0.776,0.7959870550088912,1.0
-1.8,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/checkpoint-315_torch.bfloat16_4bit_lf,0.7733333333333333,0.8327336470976,0.7733333333333333,0.7947537193805649,1.0
-2.0,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/checkpoint-350_torch.bfloat16_4bit_lf,0.7686666666666667,0.8329633784586954,0.7686666666666667,0.7914454794587963,1.0

 epoch,model,run,accuracy,precision,recall,f1,ratio_valid_classifications
+0.0,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat_torch.bfloat16_4bit_lf,0.7636666666666667,0.7806653325131986,0.7636666666666667,0.7525813484548423,0.009666666666666667
+0.2,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/checkpoint-35_torch.bfloat16_4bit_lf,0.778,0.8148707737020212,0.778,0.7910805488003003,0.9996666666666667
+0.4,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/checkpoint-70_torch.bfloat16_4bit_lf,0.7306666666666667,0.8145782271710159,0.7306666666666667,0.7624724104697406,1.0
+0.6,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/checkpoint-105_torch.bfloat16_4bit_lf,0.7193333333333334,0.8213567226911125,0.7193333333333334,0.7560702640626931,1.0
+0.8,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/checkpoint-140_torch.bfloat16_4bit_lf,0.7563333333333333,0.826789897753756,0.7563333333333333,0.7815164366677209,1.0
+1.0,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/checkpoint-175_torch.bfloat16_4bit_lf,0.7963333333333333,0.8248972880055918,0.7963333333333333,0.8076868978089201,1.0
+1.2,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/checkpoint-210_torch.bfloat16_4bit_lf,0.7326666666666667,0.8265345821998035,0.7326666666666667,0.7644418492070342,1.0
+1.4,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/checkpoint-245_torch.bfloat16_4bit_lf,0.7556666666666667,0.8258994609525315,0.7556666666666667,0.7820405339757727,1.0
+1.6,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/checkpoint-280_torch.bfloat16_4bit_lf,0.757,0.8264461657684251,0.757,0.7834496144681513,1.0
+1.8,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/checkpoint-315_torch.bfloat16_4bit_lf,0.7546666666666667,0.8277723752096544,0.7546666666666667,0.7823584779069335,1.0
+2.0,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/checkpoint-350_torch.bfloat16_4bit_lf,0.7496666666666667,0.8282310230333227,0.7496666666666667,0.7791947625361637,1.0

data/Llama3.1-70B-Chinese-Chat_results.csv CHANGED Viewed

The diff for this file is too large to render. See raw diff

data/Llama3.1-70B-Chinese-Chat_shots_metrics.csv CHANGED Viewed

@@ -1,6 +1,6 @@
 shots,model,run,accuracy,precision,recall,f1,ratio_valid_classifications
-0,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/shots-00,0.7646666666666667,0.7804609488644828,0.7646666666666667,0.7497548621711109,0.009666666666666667
-5,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/shots-05,0.754,0.7675695134276339,0.754,0.7530665717237273,0.79
-10,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/shots-10,0.756,0.7695738042762151,0.756,0.7563878737797524,0.8326666666666667
-20,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/shots-20,0.7406666666666667,0.7560876641054418,0.7406666666666667,0.7360011002310723,0.819
-30,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/shots-30,0.7603333333333333,0.7710641222872985,0.7603333333333333,0.7570501796584528,0.548

 shots,model,run,accuracy,precision,recall,f1,ratio_valid_classifications
+0,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/shots-00,0.7636666666666667,0.7806653325131986,0.7636666666666667,0.7525813484548423,0.009666666666666667
+5,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/shots-05,0.7536666666666667,0.772126097633354,0.7536666666666667,0.7545029613768596,0.79
+10,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/shots-10,0.754,0.7729477984842943,0.754,0.756682017266956,0.8326666666666667
+20,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/shots-20,0.738,0.7566938786102072,0.738,0.7348961489952073,0.819
+30,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/shots-30,0.758,0.7731535340331644,0.758,0.7565012256889623,0.548

data/Llama3.1-8B-Chinese-Chat_metrics.csv CHANGED Viewed

@@ -1,12 +1,12 @@
 epoch,model,run,accuracy,precision,recall,f1,ratio_valid_classifications
-0.0,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat_torch.float16_lf,0.7343333333333333,0.7375752740091942,0.7343333333333333,0.7270283652909943,0.8033333333333333
-0.2,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-35_torch.float16_lf,0.717,0.7933072428707201,0.717,0.7447412977676989,1.0
-0.4,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-70_torch.float16_lf,0.7226666666666667,0.7983383063141186,0.7226666666666667,0.7489397350174751,0.9993333333333333
-0.6,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-105_torch.float16_lf,0.7083333333333334,0.7967030927405547,0.7083333333333334,0.738836849803633,1.0
-0.8,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-140_torch.float16_lf,0.7773333333333333,0.805139129977305,0.7773333333333333,0.7882159693114585,1.0
-1.0,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-175_torch.float16_lf,0.7853333333333333,0.8062405645226312,0.7853333333333333,0.7938991590982061,1.0
-1.2,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-210_torch.float16_lf,0.7436666666666667,0.8148316221752646,0.7436666666666667,0.7689773286065246,1.0
-1.4,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-245_torch.float16_lf,0.759,0.8080929326806991,0.759,0.7772842274293189,1.0
-1.6,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-280_torch.float16_lf,0.745,0.8027959680086005,0.745,0.7666181725503965,1.0
-1.8,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-315_torch.float16_lf,0.7303333333333333,0.806805925253305,0.7303333333333333,0.7580841794383364,1.0
-2.0,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-350_torch.float16_lf,0.737,0.808786608325944,0.737,0.7629963845364953,1.0

 epoch,model,run,accuracy,precision,recall,f1,ratio_valid_classifications
+0.0,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat_torch.float16_lf,0.742,0.7477056799746837,0.742,0.7371050181385632,0.8033333333333333
+0.2,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-35_torch.float16_lf,0.709,0.7987219597893886,0.709,0.7427961200958145,1.0
+0.4,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-70_torch.float16_lf,0.7163333333333334,0.8058657875960304,0.7163333333333334,0.7487811196109319,0.9993333333333333
+0.6,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-105_torch.float16_lf,0.6996666666666667,0.802722482275839,0.6996666666666667,0.7370938556711591,1.0
+0.8,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-140_torch.float16_lf,0.7716666666666666,0.8092193821623755,0.7716666666666666,0.7864287269398251,1.0
+1.0,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-175_torch.float16_lf,0.78,0.810582723471486,0.78,0.7924651054056209,1.0
+1.2,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-210_torch.float16_lf,0.7313333333333333,0.8157783263996798,0.7313333333333333,0.7628807622782868,1.0
+1.4,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-245_torch.float16_lf,0.751,0.8125856808988221,0.751,0.7745416635653988,1.0
+1.6,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-280_torch.float16_lf,0.739,0.8097375095673094,0.739,0.7662329023371559,1.0
+1.8,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-315_torch.float16_lf,0.7236666666666667,0.8145530585912838,0.7236666666666667,0.7580428816095297,1.0
+2.0,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-350_torch.float16_lf,0.7293333333333333,0.8151184301713545,0.7293333333333333,0.7616699266814145,1.0

data/Llama3.1-8B-Chinese-Chat_results.csv CHANGED Viewed

The diff for this file is too large to render. See raw diff

data/Llama3.1-8B-Chinese-Chat_shots_metrics.csv CHANGED Viewed

@@ -1,8 +1,8 @@
 shots,model,run,accuracy,precision,recall,f1,ratio_valid_classifications
-0,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/shots-00,0.7343333333333333,0.7375752740091942,0.7343333333333333,0.7270283652909943,0.8033333333333333
-5,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/shots-05,0.7056666666666667,0.7508515184863084,0.7056666666666667,0.7230574380518462,0.9886666666666667
-10,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/shots-10,0.6736666666666666,0.7776004745989736,0.6736666666666666,0.7094104807112239,0.9623333333333334
-20,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/shots-20,0.767,0.764982587229615,0.767,0.7638473265780445,0.979
-30,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/shots-30,0.7713333333333333,0.7725685630276532,0.7713333333333333,0.7692692690410152,0.7326666666666667
-40,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/shots-40,0.6873333333333334,0.773294758147205,0.6873333333333334,0.7075877720686631,0.759
-50,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/shots-50,0.7176666666666667,0.7599215931134234,0.7176666666666667,0.7203550920641806,0.6623333333333333

 shots,model,run,accuracy,precision,recall,f1,ratio_valid_classifications
+0,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/shots-00,0.742,0.7477056799746837,0.742,0.7371050181385632,0.8033333333333333
+5,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/shots-05,0.7056666666666667,0.7605745196939752,0.7056666666666667,0.7269189565098723,0.9886666666666667
+10,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/shots-10,0.6676666666666666,0.7834080522821993,0.6676666666666666,0.7082605860921491,0.9623333333333334
+20,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/shots-20,0.767,0.7690587905035869,0.767,0.7661695279121855,0.979
+30,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/shots-30,0.7693333333333333,0.7765844200886581,0.7693333333333333,0.7697325957683855,0.7326666666666667
+40,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/shots-40,0.6813333333333333,0.7801328325609714,0.6813333333333333,0.7066801804415871,0.759
+50,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/shots-50,0.7173333333333334,0.770076853795054,0.7173333333333334,0.723119179918213,0.6623333333333333

data/Mistral-7B-v0.3-Chinese-Chat_metrics.csv CHANGED Viewed

@@ -1,12 +1,12 @@
 epoch,model,run,accuracy,precision,recall,f1,ratio_valid_classifications
-0.0,Mistral-7B-v0.3-Chinese-Chat,shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat_torch.float16_lf,0.6923333333333334,0.7009179792741449,0.6923333333333334,0.6605899639694456,0.011666666666666667
-0.2,Mistral-7B-v0.3-Chinese-Chat,shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-35_torch.float16_lf,0.706,0.7832545046834243,0.706,0.7323466131711432,1.0
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data/Mistral-7B-v0.3-Chinese-Chat_results.csv CHANGED Viewed

The diff for this file is too large to render. See raw diff

data/Mistral-7B-v0.3-Chinese-Chat_shots_metrics.csv CHANGED Viewed

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data/Qwen2-72B-Instruct_metrics.csv CHANGED Viewed

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data/Qwen2-72B-Instruct_shots_metrics.csv CHANGED Viewed

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data/Qwen2-7B-Instruct_metrics.csv CHANGED Viewed

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data/Qwen2-7B-Instruct_shots_metrics.csv CHANGED Viewed

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data/Qwen2.5-0.5B-Instruct_results.csv CHANGED Viewed

The diff for this file is too large to render. See raw diff

data/Qwen2.5-0.5B-Instruct_shots_metrics.csv CHANGED Viewed

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data/Qwen2.5-1.5B-Instruct_metrics.csv CHANGED Viewed

@@ -1,5 +1,5 @@
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data/Qwen2.5-1.5B-Instruct_results.csv CHANGED Viewed

The diff for this file is too large to render. See raw diff

data/Qwen2.5-1.5B-Instruct_shots_metrics.csv CHANGED Viewed

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data/Qwen2.5-3B-Instruct_metrics.csv CHANGED Viewed

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data/Qwen2.5-3B-Instruct_results.csv CHANGED Viewed

The diff for this file is too large to render. See raw diff

data/Qwen2.5-3B-Instruct_shots_metrics.csv CHANGED Viewed

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data/Qwen2.5-72B-Instruct_metrics.csv CHANGED Viewed

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data/Qwen2.5-72B-Instruct_results.csv CHANGED Viewed

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data/Qwen2.5-72B-Instruct_shots_metrics.csv CHANGED Viewed

@@ -1,3 +1,4 @@
 shots,model,run,accuracy,precision,recall,f1,ratio_valid_classifications
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data/Qwen2.5-7B-Instruct_results.csv CHANGED Viewed

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data/best_metrics.csv CHANGED Viewed

@@ -1,16 +1,18 @@
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data/best_results.csv CHANGED Viewed

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data/few-shots_metrics.csv CHANGED Viewed

@@ -1,86 +1,75 @@
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 0,Qwen2.5-7B-Instruct,Qwen/Qwen2.5-7B-Instruct/shots-00,0.6436666666666667,0.717651042027604,0.6436666666666667,0.6066932578767255,1.0
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@@ -88,5 +77,6 @@ shots,model,run,accuracy,precision,recall,f1,ratio_valid_classifications
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data/fine-tuning_metrics.csv CHANGED Viewed

@@ -1,103 +1,103 @@
 epoch,model,run,accuracy,precision,recall,f1,ratio_valid_classifications
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-0.6,Qwen2.5-1.5B-Instruct,Qwen/Qwen2.5-1.5B-Instruct/checkpoint-105_torch.bfloat16_lf,0.544,0.7064593462910856,0.544,0.5946365105633672,1.0
-0.8,Qwen2.5-1.5B-Instruct,Qwen/Qwen2.5-1.5B-Instruct/checkpoint-140_torch.bfloat16_lf,0.659,0.7267092412287238,0.659,0.6825875108247536,1.0
-1.0,Qwen2.5-1.5B-Instruct,Qwen/Qwen2.5-1.5B-Instruct/checkpoint-175_torch.bfloat16_lf,0.637,0.7191389576964738,0.637,0.6562859054038414,1.0
-1.2,Qwen2.5-1.5B-Instruct,Qwen/Qwen2.5-1.5B-Instruct/checkpoint-210_torch.bfloat16_lf,0.6086666666666667,0.7293412868960213,0.6086666666666667,0.6479350184617141,1.0
-1.4,Qwen2.5-1.5B-Instruct,Qwen/Qwen2.5-1.5B-Instruct/checkpoint-245_torch.bfloat16_lf,0.6326666666666667,0.716380475510422,0.6326666666666667,0.6591217616290708,1.0
-1.6,Qwen2.5-1.5B-Instruct,Qwen/Qwen2.5-1.5B-Instruct/checkpoint-280_torch.bfloat16_lf,0.6273333333333333,0.7224778228100358,0.6273333333333333,0.6551405164716649,1.0
-1.8,Qwen2.5-1.5B-Instruct,Qwen/Qwen2.5-1.5B-Instruct/checkpoint-315_torch.bfloat16_lf,0.5973333333333334,0.7263124149931549,0.5973333333333334,0.6349391744052281,1.0
-2.0,Qwen2.5-1.5B-Instruct,Qwen/Qwen2.5-1.5B-Instruct/checkpoint-350_torch.bfloat16_lf,0.6046666666666667,0.7203284046544999,0.6046666666666667,0.6377776248713325,1.0
-0.0,Qwen2.5-3B-Instruct,Qwen/Qwen2.5-3B-Instruct_torch.bfloat16_lf,0.569,0.6886829973126811,0.569,0.5333701103243736,1.0
-0.2,Qwen2.5-3B-Instruct,Qwen/Qwen2.5-3B-Instruct/checkpoint-35_torch.bfloat16_lf,0.6833333333333333,0.7269965624622317,0.6833333333333333,0.6985990460224034,0.999
-0.4,Qwen2.5-3B-Instruct,Qwen/Qwen2.5-3B-Instruct/checkpoint-70_torch.bfloat16_lf,0.6766666666666666,0.7583682510610537,0.6766666666666666,0.705917900971524,1.0
-0.6,Qwen2.5-3B-Instruct,Qwen/Qwen2.5-3B-Instruct/checkpoint-105_torch.bfloat16_lf,0.7023333333333334,0.7500816082620184,0.7023333333333334,0.7196546370690564,1.0
-0.8,Qwen2.5-3B-Instruct,Qwen/Qwen2.5-3B-Instruct/checkpoint-140_torch.bfloat16_lf,0.71,0.7658586215313521,0.71,0.7318979017034846,1.0
-1.0,Qwen2.5-3B-Instruct,Qwen/Qwen2.5-3B-Instruct/checkpoint-175_torch.bfloat16_lf,0.7053333333333334,0.7645466069416816,0.7053333333333334,0.7278931369071717,1.0
-1.2,Qwen2.5-3B-Instruct,Qwen/Qwen2.5-3B-Instruct/checkpoint-210_torch.bfloat16_lf,0.6943333333333334,0.7711644797484947,0.6943333333333334,0.7225635970673485,1.0
-1.4,Qwen2.5-3B-Instruct,Qwen/Qwen2.5-3B-Instruct/checkpoint-245_torch.bfloat16_lf,0.7303333333333333,0.7695138336135122,0.7303333333333333,0.7445711153936881,1.0
-1.6,Qwen2.5-3B-Instruct,Qwen/Qwen2.5-3B-Instruct/checkpoint-280_torch.bfloat16_lf,0.7273333333333334,0.7726772149368513,0.7273333333333334,0.7426310656072148,1.0
-1.8,Qwen2.5-3B-Instruct,Qwen/Qwen2.5-3B-Instruct/checkpoint-315_torch.bfloat16_lf,0.7093333333333334,0.7726776026356509,0.7093333333333334,0.7321516443823387,1.0
-2.0,Qwen2.5-3B-Instruct,Qwen/Qwen2.5-3B-Instruct/checkpoint-350_torch.bfloat16_lf,0.7166666666666667,0.7741275713911147,0.7166666666666667,0.7370173522943904,1.0
 0.0,Qwen2.5-7B-Instruct,Qwen/Qwen2.5-7B-Instruct_torch.bfloat16_lf,0.6436666666666667,0.717651042027604,0.6436666666666667,0.6066932578767255,1.0
 0.2,Qwen2.5-7B-Instruct,Qwen/Qwen2.5-7B-Instruct/checkpoint-35_torch.bfloat16_lf,0.7473333333333333,0.759526705532232,0.7473333333333333,0.7480522291877509,0.998
 0.4,Qwen2.5-7B-Instruct,Qwen/Qwen2.5-7B-Instruct/checkpoint-70_torch.bfloat16_lf,0.752,0.7774114736945115,0.752,0.7611191332452362,0.9996666666666668
@@ -109,14 +109,14 @@ epoch,model,run,accuracy,precision,recall,f1,ratio_valid_classifications
 1.6,Qwen2.5-7B-Instruct,Qwen/Qwen2.5-7B-Instruct/checkpoint-280_torch.bfloat16_lf,0.7726666666666666,0.8006851113573145,0.7726666666666666,0.7813968284378919,0.9996666666666668
 1.8,Qwen2.5-7B-Instruct,Qwen/Qwen2.5-7B-Instruct/checkpoint-315_torch.bfloat16_lf,0.7696666666666667,0.799287702962426,0.7696666666666667,0.7792120245789584,0.9993333333333332
 2.0,Qwen2.5-7B-Instruct,Qwen/Qwen2.5-7B-Instruct/checkpoint-350_torch.bfloat16_lf,0.769,0.8010881984531473,0.769,0.7793801070552965,0.9996666666666668
-0.0,Qwen2.5-72B-Instruct,Qwen/Qwen2.5-72B-Instruct_torch.bfloat16_4bit_lf,0.7956666666666666,0.8098073411161181,0.7956666666666666,0.7771317592221199,0.994
-0.2,Qwen2.5-72B-Instruct,Qwen/Qwen2.5-72B-Instruct/checkpoint-35_torch.bfloat16_4bit_lf,0.792,0.8180793658647517,0.792,0.80166512366027,1.0
-0.4,Qwen2.5-72B-Instruct,Qwen/Qwen2.5-72B-Instruct/checkpoint-70_torch.bfloat16_4bit_lf,0.7716666666666666,0.8199569804721152,0.7716666666666666,0.7895879011938259,1.0
-0.6,Qwen2.5-72B-Instruct,Qwen/Qwen2.5-72B-Instruct/checkpoint-105_torch.bfloat16_4bit_lf,0.798,0.8379062379534957,0.798,0.812148680520218,1.0
-0.8,Qwen2.5-72B-Instruct,Qwen/Qwen2.5-72B-Instruct/checkpoint-140_torch.bfloat16_4bit_lf,0.8213333333333334,0.8447926258362122,0.8213333333333334,0.8299486611547571,1.0
-1.0,Qwen2.5-72B-Instruct,Qwen/Qwen2.5-72B-Instruct/checkpoint-175_torch.bfloat16_4bit_lf,0.7643333333333333,0.8235366724638146,0.7643333333333333,0.7858148913986999,1.0
-1.2,Qwen2.5-72B-Instruct,Qwen/Qwen2.5-72B-Instruct/checkpoint-210_torch.bfloat16_4bit_lf,0.7986666666666666,0.83233218480008,0.7986666666666666,0.8115886421806521,1.0
-1.4,Qwen2.5-72B-Instruct,Qwen/Qwen2.5-72B-Instruct/checkpoint-245_torch.bfloat16_4bit_lf,0.7923333333333333,0.8231874218285514,0.7923333333333333,0.803363661387202,1.0
-1.6,Qwen2.5-72B-Instruct,Qwen/Qwen2.5-72B-Instruct/checkpoint-280_torch.bfloat16_4bit_lf,0.7936666666666666,0.8268750473800219,0.7936666666666666,0.8057720333101867,1.0
-1.8,Qwen2.5-72B-Instruct,Qwen/Qwen2.5-72B-Instruct/checkpoint-315_torch.bfloat16_4bit_lf,0.801,0.830389411421043,0.801,0.8117656427717702,1.0
-2.0,Qwen2.5-72B-Instruct,Qwen/Qwen2.5-72B-Instruct/checkpoint-350_torch.bfloat16_4bit_lf,0.795,0.8280696193638868,0.795,0.8068114730639832,1.0

 epoch,model,run,accuracy,precision,recall,f1,ratio_valid_classifications
+0.0,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat_torch.float16_lf,0.742,0.7477056799746837,0.742,0.7371050181385632,0.8033333333333333
+0.2,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-35_torch.float16_lf,0.709,0.7987219597893886,0.709,0.7427961200958145,1.0
+0.4,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-70_torch.float16_lf,0.7163333333333334,0.8058657875960304,0.7163333333333334,0.7487811196109319,0.9993333333333332
+0.6,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-105_torch.float16_lf,0.6996666666666667,0.802722482275839,0.6996666666666667,0.7370938556711591,1.0
+0.8,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-140_torch.float16_lf,0.7716666666666666,0.8092193821623755,0.7716666666666666,0.7864287269398251,1.0
+1.0,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-175_torch.float16_lf,0.78,0.810582723471486,0.78,0.7924651054056209,1.0
+1.2,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-210_torch.float16_lf,0.7313333333333333,0.8157783263996798,0.7313333333333333,0.7628807622782868,1.0
+1.4,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-245_torch.float16_lf,0.751,0.8125856808988221,0.751,0.7745416635653988,1.0
+1.6,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-280_torch.float16_lf,0.739,0.8097375095673094,0.739,0.7662329023371559,1.0
+1.8,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-315_torch.float16_lf,0.7236666666666667,0.8145530585912838,0.7236666666666667,0.7580428816095297,1.0
+2.0,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-350_torch.float16_lf,0.7293333333333333,0.8151184301713545,0.7293333333333333,0.7616699266814145,1.0
+0.0,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat_torch.bfloat16_4bit_lf,0.7636666666666667,0.7806653325131986,0.7636666666666667,0.7525813484548423,0.0096666666666666
+0.2,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/checkpoint-35_torch.bfloat16_4bit_lf,0.778,0.8148707737020212,0.778,0.7910805488003003,0.9996666666666668
+0.4,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/checkpoint-70_torch.bfloat16_4bit_lf,0.7306666666666667,0.8145782271710159,0.7306666666666667,0.7624724104697406,1.0
+0.6,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/checkpoint-105_torch.bfloat16_4bit_lf,0.7193333333333334,0.8213567226911125,0.7193333333333334,0.7560702640626931,1.0
+0.8,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/checkpoint-140_torch.bfloat16_4bit_lf,0.7563333333333333,0.826789897753756,0.7563333333333333,0.7815164366677209,1.0
+1.0,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/checkpoint-175_torch.bfloat16_4bit_lf,0.7963333333333333,0.8248972880055918,0.7963333333333333,0.8076868978089201,1.0
+1.2,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/checkpoint-210_torch.bfloat16_4bit_lf,0.7326666666666667,0.8265345821998035,0.7326666666666667,0.7644418492070342,1.0
+1.4,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/checkpoint-245_torch.bfloat16_4bit_lf,0.7556666666666667,0.8258994609525315,0.7556666666666667,0.7820405339757727,1.0
+1.6,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/checkpoint-280_torch.bfloat16_4bit_lf,0.757,0.8264461657684251,0.757,0.7834496144681513,1.0
+1.8,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/checkpoint-315_torch.bfloat16_4bit_lf,0.7546666666666667,0.8277723752096544,0.7546666666666667,0.7823584779069335,1.0
+2.0,Llama3.1-70B-Chinese-Chat,shenzhi-wang/Llama3.1-70B-Chinese-Chat/checkpoint-350_torch.bfloat16_4bit_lf,0.7496666666666667,0.8282310230333227,0.7496666666666667,0.7791947625361637,1.0
+0.0,Mistral-7B-v0.3-Chinese-Chat,shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat_torch.float16_lf,0.6946666666666667,0.701136267898111,0.6946666666666667,0.6634078645357937,0.0116666666666666
+0.2,Mistral-7B-v0.3-Chinese-Chat,shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-35_torch.float16_lf,0.702,0.7932731014186957,0.702,0.7342714734731689,1.0
+0.4,Mistral-7B-v0.3-Chinese-Chat,shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70_torch.float16_lf,0.742,0.78982949223512,0.742,0.7536681109811127,1.0
+0.6,Mistral-7B-v0.3-Chinese-Chat,shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-105_torch.float16_lf,0.6596666666666666,0.7923396753604393,0.6596666666666666,0.7067542301676931,1.0
+0.8,Mistral-7B-v0.3-Chinese-Chat,shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-140_torch.float16_lf,0.7146666666666667,0.7861341885687435,0.7146666666666667,0.7404677278137267,1.0
+1.0,Mistral-7B-v0.3-Chinese-Chat,shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-175_torch.float16_lf,0.7326666666666667,0.7876867721932461,0.7326666666666667,0.7471869515031995,1.0
+1.2,Mistral-7B-v0.3-Chinese-Chat,shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-210_torch.float16_lf,0.7016666666666667,0.7903119228393193,0.7016666666666667,0.7348708822385348,1.0
+1.4,Mistral-7B-v0.3-Chinese-Chat,shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-245_torch.float16_lf,0.75,0.7885868317699068,0.75,0.7648234347578796,1.0
+1.6,Mistral-7B-v0.3-Chinese-Chat,shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-280_torch.float16_lf,0.7156666666666667,0.7846106674095725,0.7156666666666667,0.7410042005708856,1.0
+1.8,Mistral-7B-v0.3-Chinese-Chat,shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-315_torch.float16_lf,0.6916666666666667,0.7864256994491394,0.6916666666666667,0.7257499426487266,1.0
+2.0,Mistral-7B-v0.3-Chinese-Chat,shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-350_torch.float16_lf,0.6976666666666667,0.7889443494370009,0.6976666666666667,0.7307996137659796,1.0
+0.0,internlm2_5-7b-chat,internlm/internlm2_5-7b-chat_torch.bfloat16_lf,0.705,0.7398041613378253,0.705,0.6906357423169466,1.0
+0.2,internlm2_5-7b-chat,internlm/internlm2_5-7b-chat/checkpoint-35_torch.bfloat16_lf,0.7193333333333334,0.7863486093365692,0.7193333333333334,0.7330498811142795,1.0
+0.4,internlm2_5-7b-chat,internlm/internlm2_5-7b-chat/checkpoint-70_torch.bfloat16_lf,0.726,0.7900250828103491,0.726,0.7396583495246526,1.0
+0.6,internlm2_5-7b-chat,internlm/internlm2_5-7b-chat/checkpoint-105_torch.bfloat16_lf,0.6736666666666666,0.8044565554629858,0.6736666666666666,0.7104123104529902,1.0
+0.8,internlm2_5-7b-chat,internlm/internlm2_5-7b-chat/checkpoint-140_torch.bfloat16_lf,0.7496666666666667,0.8041871978859686,0.7496666666666667,0.7660159670998776,1.0
+1.0,internlm2_5-7b-chat,internlm/internlm2_5-7b-chat/checkpoint-175_torch.bfloat16_lf,0.726,0.8094634420846424,0.726,0.751394838822856,1.0
+1.2,internlm2_5-7b-chat,internlm/internlm2_5-7b-chat/checkpoint-210_torch.bfloat16_lf,0.7276666666666667,0.8039673699820601,0.7276666666666667,0.7488653386949028,1.0
+1.4,internlm2_5-7b-chat,internlm/internlm2_5-7b-chat/checkpoint-245_torch.bfloat16_lf,0.747,0.8055537753403307,0.747,0.76527383722639,1.0
+1.6,internlm2_5-7b-chat,internlm/internlm2_5-7b-chat/checkpoint-280_torch.bfloat16_lf,0.7166666666666667,0.8059535682746547,0.7166666666666667,0.7432427946178835,1.0
+1.8,internlm2_5-7b-chat,internlm/internlm2_5-7b-chat/checkpoint-315_torch.bfloat16_lf,0.6983333333333334,0.8119110469658597,0.6983333333333334,0.7347246872892312,1.0
+2.0,internlm2_5-7b-chat,internlm/internlm2_5-7b-chat/checkpoint-350_torch.bfloat16_lf,0.7076666666666667,0.8120132783051135,0.7076666666666667,0.7408145046817652,1.0
+0.0,internlm2_5-7b-chat-1m,internlm/internlm2_5-7b-chat-1m_torch.bfloat16_lf,0.4813333333333333,0.7605248207587668,0.4813333333333333,0.5244515621126862,0.9986666666666668
+0.2,internlm2_5-7b-chat-1m,internlm/internlm2_5-7b-chat-1m/checkpoint-35_torch.bfloat16_lf,0.7843333333333333,0.7977648302848388,0.7843333333333333,0.7864944570659659,1.0
+0.4,internlm2_5-7b-chat-1m,internlm/internlm2_5-7b-chat-1m/checkpoint-70_torch.bfloat16_lf,0.7836666666666666,0.7996977262947886,0.7836666666666666,0.7886881726841081,1.0
+0.6,internlm2_5-7b-chat-1m,internlm/internlm2_5-7b-chat-1m/checkpoint-105_torch.bfloat16_lf,0.7243333333333334,0.8171172705912051,0.7243333333333334,0.7565804830382912,1.0
+0.8,internlm2_5-7b-chat-1m,internlm/internlm2_5-7b-chat-1m/checkpoint-140_torch.bfloat16_lf,0.803,0.8031411888150441,0.803,0.8028064320197301,1.0
+1.0,internlm2_5-7b-chat-1m,internlm/internlm2_5-7b-chat-1m/checkpoint-175_torch.bfloat16_lf,0.7676666666666667,0.8108441731715863,0.7676666666666667,0.7843187816704813,1.0
+1.2,internlm2_5-7b-chat-1m,internlm/internlm2_5-7b-chat-1m/checkpoint-210_torch.bfloat16_lf,0.7736666666666666,0.8091671780923799,0.7736666666666666,0.7876874850235454,1.0
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data/internlm2_5-20b-chat_metrics.csv CHANGED Viewed

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data/internlm2_5-20b-chat_results.csv CHANGED Viewed

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data/internlm2_5-7b-chat-1m_results.csv CHANGED Viewed

The diff for this file is too large to render. See raw diff

data/internlm2_5-7b-chat-1m_shots_metrics.csv CHANGED Viewed

@@ -1,8 +1,8 @@
 shots,model,run,accuracy,precision,recall,f1,ratio_valid_classifications
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 shots,model,run,accuracy,precision,recall,f1,ratio_valid_classifications
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data/internlm2_5-7b-chat_metrics.csv CHANGED Viewed

@@ -1,12 +1,12 @@
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data/internlm2_5-7b-chat_results.csv CHANGED Viewed

The diff for this file is too large to render. See raw diff

data/internlm2_5-7b-chat_shots_metrics.csv CHANGED Viewed

@@ -1,8 +1,8 @@
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data/openai_metrics.csv CHANGED Viewed

@@ -1,29 +1,29 @@
 shots,model,run,accuracy,precision,recall,f1,ratio_valid_classifications
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