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correct_filter/results_wo_norm/molmo/accuracy/accuracy_2m.json

@@ -0,0 +1,25 @@
+{
+  "model": "molmo",
+  "scale": "2m",
+  "left_total": 616,
+  "left_correct": 586,
+  "left_accuracy": 0.9512987012987013,
+  "right_total": 620,
+  "right_correct": 522,
+  "right_accuracy": 0.8419354838709677,
+  "above_total": 596,
+  "above_correct": 586,
+  "above_accuracy": 0.9832214765100671,
+  "under_total": 602,
+  "under_correct": 592,
+  "under_accuracy": 0.9833887043189369,
+  "far_total": 594,
+  "far_correct": 82,
+  "far_accuracy": 0.13804713804713806,
+  "close_total": 612,
+  "close_correct": 573,
+  "close_accuracy": 0.9362745098039216,
+  "overall_total": 3640,
+  "overall_correct": 2941,
+  "overall_accuracy": 0.807967032967033
+}

correct_filter/results_wo_norm/molmo/accuracy/accuracy_400k.json

@@ -0,0 +1,25 @@
+{
+  "model": "molmo",
+  "scale": "400k",
+  "left_total": 616,
+  "left_correct": 583,
+  "left_accuracy": 0.9464285714285714,
+  "right_total": 620,
+  "right_correct": 498,
+  "right_accuracy": 0.8032258064516129,
+  "above_total": 596,
+  "above_correct": 579,
+  "above_accuracy": 0.9714765100671141,
+  "under_total": 602,
+  "under_correct": 568,
+  "under_accuracy": 0.9435215946843853,
+  "far_total": 594,
+  "far_correct": 1,
+  "far_accuracy": 0.0016835016835016834,
+  "close_total": 612,
+  "close_correct": 566,
+  "close_accuracy": 0.9248366013071896,
+  "overall_total": 3640,
+  "overall_correct": 2795,
+  "overall_accuracy": 0.7678571428571429
+}

correct_filter/results_wo_norm/molmo/accuracy/accuracy_800k.json

@@ -0,0 +1,25 @@
+{
+  "model": "molmo",
+  "scale": "800k",
+  "left_total": 616,
+  "left_correct": 578,
+  "left_accuracy": 0.9383116883116883,
+  "right_total": 620,
+  "right_correct": 546,
+  "right_accuracy": 0.8806451612903226,
+  "above_total": 596,
+  "above_correct": 580,
+  "above_accuracy": 0.9731543624161074,
+  "under_total": 602,
+  "under_correct": 578,
+  "under_accuracy": 0.9601328903654485,
+  "far_total": 594,
+  "far_correct": 1,
+  "far_accuracy": 0.0016835016835016834,
+  "close_total": 612,
+  "close_correct": 612,
+  "close_accuracy": 1.0,
+  "overall_total": 3640,
+  "overall_correct": 2895,
+  "overall_accuracy": 0.7953296703296703
+}

correct_filter/results_wo_norm/molmo/accuracy/accuracy_80k.json

@@ -0,0 +1,25 @@
+{
+  "model": "molmo",
+  "scale": "80k",
+  "left_total": 616,
+  "left_correct": 609,
+  "left_accuracy": 0.9886363636363636,
+  "right_total": 620,
+  "right_correct": 169,
+  "right_accuracy": 0.2725806451612903,
+  "above_total": 596,
+  "above_correct": 595,
+  "above_accuracy": 0.9983221476510067,
+  "under_total": 602,
+  "under_correct": 174,
+  "under_accuracy": 0.28903654485049834,
+  "far_total": 594,
+  "far_correct": 0,
+  "far_accuracy": 0.0,
+  "close_total": 612,
+  "close_correct": 612,
+  "close_accuracy": 1.0,
+  "overall_total": 3640,
+  "overall_correct": 2159,
+  "overall_accuracy": 0.5931318681318681
+}

correct_filter/results_wo_norm/molmo/accuracy/accuracy_summary.csv

@@ -0,0 +1,6 @@
+model,scale,left_total,left_correct,left_accuracy,right_total,right_correct,right_accuracy,above_total,above_correct,above_accuracy,under_total,under_correct,under_accuracy,far_total,far_correct,far_accuracy,close_total,close_correct,close_accuracy,overall_total,overall_correct,overall_accuracy
+molmo,vanilla,616,579,0.939935064935065,620,372,0.6,596,526,0.8825503355704698,602,431,0.7159468438538206,594,53,0.08922558922558922,612,606,0.9901960784313726,3640,2567,0.7052197802197803
+molmo,80k,616,609,0.9886363636363636,620,169,0.2725806451612903,596,595,0.9983221476510067,602,174,0.28903654485049834,594,0,0.0,612,612,1.0,3640,2159,0.5931318681318681
+molmo,400k,616,583,0.9464285714285714,620,498,0.8032258064516129,596,579,0.9714765100671141,602,568,0.9435215946843853,594,1,0.0016835016835016834,612,566,0.9248366013071896,3640,2795,0.7678571428571429
+molmo,800k,616,578,0.9383116883116883,620,546,0.8806451612903226,596,580,0.9731543624161074,602,578,0.9601328903654485,594,1,0.0016835016835016834,612,612,1.0,3640,2895,0.7953296703296703
+molmo,2m,616,586,0.9512987012987013,620,522,0.8419354838709677,596,586,0.9832214765100671,602,592,0.9833887043189369,594,82,0.13804713804713806,612,573,0.9362745098039216,3640,2941,0.807967032967033

correct_filter/results_wo_norm/molmo/accuracy/accuracy_vanilla.json

@@ -0,0 +1,25 @@
+{
+  "model": "molmo",
+  "scale": "vanilla",
+  "left_total": 616,
+  "left_correct": 579,
+  "left_accuracy": 0.939935064935065,
+  "right_total": 620,
+  "right_correct": 372,
+  "right_accuracy": 0.6,
+  "above_total": 596,
+  "above_correct": 526,
+  "above_accuracy": 0.8825503355704698,
+  "under_total": 602,
+  "under_correct": 431,
+  "under_accuracy": 0.7159468438538206,
+  "far_total": 594,
+  "far_correct": 53,
+  "far_accuracy": 0.08922558922558922,
+  "close_total": 612,
+  "close_correct": 606,
+  "close_accuracy": 0.9901960784313726,
+  "overall_total": 3640,
+  "overall_correct": 2567,
+  "overall_accuracy": 0.7052197802197803
+}

correct_filter/results_wo_norm/molmo/all_samples/similarity_2m_L0.csv

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+,left,right,above,under,far,close
+left,1.0,0.99999595,0.99944806,0.99944544,0.9988256,0.9988305
+right,0.99999595,1.0000004,0.9994674,0.9994634,0.99886453,0.9988709
+above,0.99944806,0.9994674,0.99999994,0.9999965,0.9992513,0.99925494
+under,0.99944544,0.9994634,0.9999965,0.9999997,0.9992531,0.99925476
+far,0.9988256,0.99886453,0.9992513,0.9992531,1.0000006,0.9999966
+close,0.9988305,0.9988709,0.99925494,0.99925476,0.9999966,0.9999998

correct_filter/results_wo_norm/molmo/all_samples/similarity_2m_L1.csv

@@ -0,0 +1,7 @@
+,left,right,above,under,far,close
+left,1.0000002,0.9999931,0.99883854,0.9988599,0.9922035,0.9922641
+right,0.9999931,1.0,0.9988415,0.9988643,0.9921667,0.99223226
+above,0.99883854,0.9988415,1.0000004,0.9999918,0.9932217,0.9932554
+under,0.9988599,0.9988643,0.9999918,1.000001,0.9931125,0.9931502
+far,0.9922035,0.9921667,0.9932217,0.9931125,0.99999994,0.99999166
+close,0.9922641,0.99223226,0.9932554,0.9931502,0.99999166,1.0000002

correct_filter/results_wo_norm/molmo/all_samples/similarity_2m_L10.csv

@@ -0,0 +1,7 @@
+,left,right,above,under,far,close
+left,0.99999976,0.9999628,0.98735034,0.9868248,0.9739153,0.9735924
+right,0.9999628,1.0000004,0.9873911,0.9869112,0.97387993,0.97355944
+above,0.98735034,0.9873911,0.9999994,0.9996705,0.9728755,0.97234094
+under,0.9868248,0.9869112,0.9996705,1.0,0.9727328,0.9720068
+far,0.9739153,0.97387993,0.9728755,0.9727328,0.99999976,0.9997798
+close,0.9735924,0.97355944,0.97234094,0.9720068,0.9997798,1.0

correct_filter/results_wo_norm/molmo/all_samples/similarity_2m_L11.csv

@@ -0,0 +1,7 @@
+,left,right,above,under,far,close
+left,1.0000002,0.9998207,0.975669,0.97483253,0.93304,0.9329291
+right,0.9998207,1.0,0.9754914,0.97480977,0.93243194,0.93232757
+above,0.975669,0.9754914,1.0000005,0.9994197,0.9413995,0.94066346
+under,0.97483253,0.97480977,0.9994197,0.9999999,0.9418358,0.9409922
+far,0.93304,0.93243194,0.9413995,0.9418358,1.0,0.9996316
+close,0.9329291,0.93232757,0.94066346,0.9409922,0.9996316,1.0000002

correct_filter/results_wo_norm/molmo/all_samples/similarity_2m_L12.csv

@@ -0,0 +1,7 @@
+,left,right,above,under,far,close
+left,1.0000001,0.99958426,0.97294736,0.97160774,0.93564856,0.9355189
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+far,0.93564856,0.9354133,0.9405666,0.94103605,0.9999998,0.99925554
+close,0.9355189,0.93529075,0.9395374,0.9401265,0.99925554,1.0000002

correct_filter/results_wo_norm/molmo/all_samples/similarity_2m_L13.csv

@@ -0,0 +1,7 @@
+,left,right,above,under,far,close
+left,1.0000005,0.998732,0.9684684,0.96719295,0.9331372,0.93420315
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+close,0.93420315,0.93346375,0.9308036,0.9310835,0.9977601,0.9999998

correct_filter/results_wo_norm/molmo/all_samples/similarity_2m_L14.csv

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+,left,right,above,under,far,close
+left,1.0,0.9602881,0.9341542,0.93069535,0.91541594,0.9159156
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+under,0.93069535,0.93433154,0.90430236,1.0,0.88727206,0.9048346
+far,0.91541594,0.92293715,0.9087677,0.88727206,0.9999999,0.9891723
+close,0.9159156,0.9177855,0.88882333,0.9048346,0.9891723,1.0000004

correct_filter/results_wo_norm/molmo/all_samples/similarity_2m_L15.csv

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+,left,right,above,under,far,close
+left,0.99999976,0.9531184,0.87769186,0.87831855,0.88208884,0.8800998
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+far,0.88208884,0.8900313,0.877947,0.8500281,0.9999998,0.98495615
+close,0.8800998,0.8848122,0.849118,0.868364,0.98495615,0.99999994

correct_filter/results_wo_norm/molmo/all_samples/similarity_2m_L16.csv

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+,left,right,above,under,far,close
+left,0.9999998,0.93509364,0.8494278,0.8429825,0.8483933,0.84407157
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+far,0.8483933,0.860275,0.8453083,0.8155161,1.0,0.97748834
+close,0.84407157,0.85325617,0.8032402,0.84567255,0.97748834,1.0000005

correct_filter/results_wo_norm/molmo/all_samples/similarity_2m_L17.csv

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+,left,right,above,under,far,close
+left,1.0000004,0.9235279,0.84540886,0.83762026,0.8535774,0.84527254
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+close,0.84527254,0.8538659,0.7859585,0.85078573,0.97247946,1.0000001

correct_filter/results_wo_norm/molmo/all_samples/similarity_2m_L18.csv

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+,left,right,above,under,far,close
+left,1.0000005,0.91171646,0.767186,0.7552635,0.7618721,0.75355834
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+close,0.75355834,0.7537444,0.7021058,0.77178437,0.9715382,1.0

correct_filter/results_wo_norm/molmo/all_samples/similarity_2m_L19.csv

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+,left,right,above,under,far,close
+left,1.0000004,0.9213134,0.78069097,0.7653611,0.7696275,0.76052904
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+close,0.76052904,0.7571479,0.70519954,0.76923674,0.9702768,1.0000004

correct_filter/results_wo_norm/molmo/all_samples/similarity_2m_L2.csv

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+,left,right,above,under,far,close
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+close,0.9876915,0.98767686,0.9879702,0.9878222,0.99998784,0.99999994

correct_filter/results_wo_norm/molmo/all_samples/similarity_2m_L20.csv

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+,left,right,above,under,far,close
+left,1.0000001,0.93193257,0.79287475,0.7799577,0.7761234,0.77275914
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+close,0.77275914,0.7723502,0.71386063,0.76680493,0.97372574,1.0000001

correct_filter/results_wo_norm/molmo/all_samples/similarity_2m_L21.csv

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+,left,right,above,under,far,close
+left,0.9999997,0.9177052,0.72975075,0.7284441,0.73510575,0.7341003
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+close,0.7341003,0.7454985,0.66596425,0.7376301,0.97059715,0.9999998

correct_filter/results_wo_norm/molmo/all_samples/similarity_2m_L22.csv

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+,left,right,above,under,far,close
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+close,0.69680935,0.7038574,0.6382874,0.69398695,0.97199374,1.0000001

correct_filter/results_wo_norm/molmo/all_samples/similarity_2m_L23.csv

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+,left,right,above,under,far,close
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+close,0.7051712,0.7100235,0.6354837,0.6856754,0.97433436,1.0000001

correct_filter/results_wo_norm/molmo/all_samples/similarity_2m_L24.csv

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+,left,right,above,under,far,close
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+close,0.7071076,0.7131977,0.6424474,0.6927831,0.97612774,0.99999994

correct_filter/results_wo_norm/molmo/all_samples/similarity_2m_L25.csv

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+,left,right,above,under,far,close
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+close,0.70038253,0.7086322,0.6299084,0.6788422,0.9769813,1.0000002

correct_filter/results_wo_norm/molmo/all_samples/similarity_2m_L26.csv

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correct_filter/results_wo_norm/molmo/all_samples/similarity_2m_L27.csv

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correct_filter/results_wo_norm/molmo/all_samples/similarity_2m_L28.csv

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correct_filter/results_wo_norm/molmo/all_samples/similarity_2m_L29.csv

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correct_filter/results_wo_norm/molmo/all_samples/similarity_2m_L3.csv

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correct_filter/results_wo_norm/molmo/all_samples/similarity_2m_L30.csv

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correct_filter/results_wo_norm/molmo/all_samples/similarity_2m_L31.csv

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correct_filter/results_wo_norm/molmo/all_samples/similarity_2m_L4.csv

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correct_filter/results_wo_norm/molmo/all_samples/similarity_2m_L5.csv

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correct_filter/results_wo_norm/molmo/all_samples/similarity_2m_L6.csv

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correct_filter/results_wo_norm/molmo/all_samples/similarity_2m_L7.csv

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correct_filter/results_wo_norm/molmo/all_samples/similarity_2m_L8.csv

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correct_filter/results_wo_norm/molmo/all_samples/similarity_2m_L9.csv

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correct_filter/results_wo_norm/molmo/all_samples/similarity_400k_L0.csv

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correct_filter/results_wo_norm/molmo/all_samples/similarity_400k_L1.csv

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correct_filter/results_wo_norm/molmo/all_samples/similarity_400k_L10.csv

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correct_filter/results_wo_norm/molmo/all_samples/similarity_400k_L11.csv

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correct_filter/results_wo_norm/molmo/all_samples/similarity_400k_L12.csv

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correct_filter/results_wo_norm/molmo/all_samples/similarity_400k_L13.csv

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correct_filter/results_wo_norm/molmo/all_samples/similarity_400k_L14.csv

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