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dore-xlmr-base / training_progress_scores.csv
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global_step,eval_loss,train_loss
3200,7.930418889537591,6.148362159729004
6400,12.296674990758104,6.44409704208374
8242,9.484387923883386,6.297712802886963
9600,10.829837249356066,6.274528503417969
12800,8.220191487521005,6.226631164550781
16000,8.53572968983176,6.095396518707275
16484,8.89201227106671,6.356380462646484
19200,7.8864835716462265,5.688492774963379
22400,7.0484312500322055,6.258127212524414
24726,7.654123558227672,6.136369228363037
25600,7.387684218921689,6.068527698516846
28800,7.305299826006124,6.185582160949707
32000,7.906453343631572,6.278289794921875
32968,7.270944936595918,6.148674488067627
35200,6.960241781167183,6.763805866241455
38400,7.082412289393174,5.938570499420166
41210,6.8388658132095,6.321269512176514
41600,6.861103287372469,6.283682346343994
44800,6.908954990540587,6.716731071472168
48000,6.885604741791971,6.241613388061523
49452,7.5381106791248715,5.46036958694458
51200,6.976297252216367,5.663772106170654
54400,7.42415123527227,6.084234714508057
57600,7.38894475287225,6.619105339050293
57694,7.369134920768978,6.553373336791992
60800,7.374053779011615,6.281004905700684
64000,7.177092781233475,6.525512218475342
65936,7.130762249679602,6.066104888916016
67200,7.421877788375269,5.748194694519043
70400,7.465437963829059,5.620741367340088
73600,7.41981489967224,5.701391220092773
74178,7.374407465627967,6.484068870544434
76800,7.334438348267623,6.280816078186035
80000,7.443736958307065,5.787185192108154
82420,7.40604503128148,6.256833553314209