diff --git "a/metrics.csv" "b/metrics.csv"
--- "a/metrics.csv"
+++ "b/metrics.csv"
@@ -688,7 +688,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
 29,31449,,583.008544921875,
 29,31499,,598.2623291015625,
 29,31549,,933.615478515625,
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 29,31649,,643.8433227539062,
 29,31699,,773.4666748046875,
 29,31739,,,750.7279663085938
@@ -707,7 +707,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
 30,32299,,424.9476623535156,
 30,32349,,758.1637573242188,
 30,32399,,806.6527099609375,
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 30,32499,,433.0582275390625,
 30,32549,,454.2977294921875,
 30,32599,,530.1234130859375,
@@ -1118,7 +1118,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
 48,51049,,369.1681823730469,
 48,51099,,529.14111328125,
 48,51149,,285.1032409667969,
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 48,51249,,380.17864990234375,
 48,51299,,206.0561981201172,
 48,51349,,333.6784362792969,
@@ -1295,7 +1295,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
 55,59199,,303.8672180175781,
 55,59247,,,711.0247192382812
 55,59247,330.9780578613281,,
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 56,59299,,418.1961364746094,
 56,59349,,406.3598937988281,
 56,59399,,383.72467041015625,
@@ -1307,7 +1307,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
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 56,59749,,376.3229370117188,
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 56,59999,,459.2874755859375,
@@ -1346,7 +1346,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
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 58,61649,,234.9193420410156,
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 58,61749,,580.49072265625,
@@ -1366,7 +1366,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
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@@ -1404,7 +1404,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
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 60,64199,,254.7671813964844,
 60,64249,,310.0660095214844,
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 60,64349,,190.9644317626953,
 60,64399,,320.3516540527344,
 60,64449,,318.3280639648437,
@@ -1451,7 +1451,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
 62,66299,,533.9501953125,
 62,66349,,303.5518493652344,
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 62,66499,,265.2099914550781,
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 62,66599,,127.68775939941406,
@@ -1534,7 +1534,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
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 66,70299,,391.0115966796875,
 66,70349,,298.70379638671875,
@@ -1542,7 +1542,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
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 66,70649,,307.75390625,
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 66,70749,,297.9549560546875,
@@ -1638,7 +1638,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
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 70,75117,,,759.7333374023438
@@ -1647,14 +1647,14 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
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@@ -1713,7 +1713,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
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@@ -1721,7 +1721,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
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@@ -1750,7 +1750,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
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 75,80249,,309.53302001953125,
@@ -1796,7 +1796,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
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@@ -1911,7 +1911,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
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 82,87499,,215.0204620361328,
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 82,87599,,363.1493225097656,
@@ -1941,7 +1941,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
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 83,88871,,,728.3179321289062
 83,88871,262.15948486328125,,
 84,88899,,204.87234497070312,
@@ -1978,7 +1978,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
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 85,90599,,165.5054931640625,
 85,90649,,326.0424499511719,
@@ -2012,7 +2012,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
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 87,92049,,115.16545867919922,
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 87,92149,,110.29766082763672,
@@ -2105,7 +2105,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
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 90,96277,,,774.70068359375
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 91,96299,,119.88607025146484,
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 91,96399,,211.52880859375,
@@ -2157,7 +2157,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
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@@ -2191,7 +2191,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
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@@ -2253,7 +2253,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
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 97,103149,,68.99594116210938,
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@@ -2303,7 +2303,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
 99,105199,,60.8307991027832,
 99,105249,,99.83039855957033,
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 99,105399,,304.07818603515625,
 99,105449,,126.16554260253906,
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@@ -2332,7 +2332,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
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 100,106599,,160.9970245361328,
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 100,106749,,156.9330291748047,
 100,106799,,330.7934265136719,
 100,106849,,94.85871887207033,
@@ -2367,7 +2367,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
 102,108099,,224.7510986328125,
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 102,108299,,189.9288482666016,
 102,108349,,141.11325073242188,
 102,108399,,51.74876403808594,
@@ -2463,7 +2463,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
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@@ -2564,7 +2564,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
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@@ -2587,15 +2587,15 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
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 112,118699,,149.7482147216797,
 112,118749,,307.6256103515625,
 112,118799,,124.0906753540039,
@@ -2603,7 +2603,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
 112,118899,,150.00392150878906,
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 112,119099,,226.29495239257807,
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@@ -2621,7 +2621,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
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 113,119949,,259.9498291015625,
 113,119999,,203.3893280029297,
@@ -2631,18 +2631,18 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
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 114,120849,,240.4586334228516,
 114,120899,,258.3183288574219,
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@@ -2678,7 +2678,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
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 115,122549,,105.84275817871094,
 115,122599,,117.17337036132812,
 115,122649,,104.23150634765624,
@@ -2688,7 +2688,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
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 116,122949,,206.9390106201172,
 116,122999,,46.798038482666016,
 116,123049,,360.8970947265625,
@@ -2732,7 +2732,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
 117,124843,,,645.7332763671875
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 119,126299,,298.043212890625,
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 119,126499,,476.3018798828125,
 119,126549,,91.06938934326172,
 119,126599,,216.8729248046875,
@@ -2803,7 +2803,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
 120,128017,190.71295166015625,,
 121,128049,,251.20358276367188,
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 121,128199,,126.0013427734375,
 121,128249,,210.5396728515625,
 121,128299,,87.58380126953125,
@@ -2836,7 +2836,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
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 122,129749,,126.46522521972656,
 122,129799,,158.22259521484375,
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@@ -2846,16 +2846,16 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
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 123,130599,,97.52652740478516,
 123,130649,,117.9906234741211,
 123,130699,,159.7198944091797,
@@ -2884,7 +2884,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
 124,131749,,97.69474792480467,
 124,131799,,165.34552001953125,
 124,131849,,136.86399841308594,
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 124,131949,,173.52183532714844,
 124,131999,,90.94783782958984,
 124,132049,,227.0358123779297,
@@ -2899,7 +2899,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
 125,132399,,361.2458801269531,
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 125,132499,,75.2616195678711,
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 125,132599,,443.6803588867188,
 125,132649,,151.0964813232422,
 125,132699,,121.46631622314452,
@@ -2956,7 +2956,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
 127,135049,,41.01333236694336,
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 127,135249,,179.92626953125,
 127,135299,,141.33815002441406,
 127,135349,,72.8736801147461,
@@ -3198,7 +3198,7 @@ epoch,step,train_loss_epoch,train_loss_step,val_loss
 138,146049,,104.5733871459961,
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 138,146249,,175.9146728515625,
 138,146299,,63.8990364074707,
 138,146349,,82.93524932861328,
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