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epoch
int64
-1
20k
num_tokens_seen
int64
0
4.1B
train_loss_ctx0
float64
0.72
1.52
βŒ€
val_loss_ctx0
float64
1
2.13
train_loss_ctx1
float64
0.76
1.46
βŒ€
val_loss_ctx1
float64
1
2.07
train_loss_ctx2
float64
0.77
1.38
βŒ€
val_loss_ctx2
float64
1
2.28
train_loss_ctx3
float64
0.78
1.38
βŒ€
val_loss_ctx3
float64
1
2.07
train_loss_ctx4
float64
0.75
1.38
βŒ€
val_loss_ctx4
float64
1
2.5
train_loss_ctx5
float64
0.77
1.38
βŒ€
val_loss_ctx5
float64
1
2.53
train_loss_ctx6
float64
0.77
1.37
βŒ€
val_loss_ctx6
float64
1
2.52
train_loss_ctx7
float64
0.74
1.37
βŒ€
val_loss_ctx7
float64
1
2.29
train_loss_mean
float64
0.92
1.36
βŒ€
val_loss_mean
float64
1
2.3
learning_rate
float64
0
0
-1
0
null
1.583977
null
1.599219
null
1.610021
null
1.613485
null
1.615111
null
1.615752
null
1.615798
null
1.615796
null
1.608645
0.0001
0
204,800
1.522285
1.467032
1.461267
1.326275
1.383603
1.171325
1.310438
1.069803
1.268434
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1.260487
1.045101
1.266508
1.057436
1.247793
1.068003
1.340102
1.155615
0.0001
1
409,600
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0.0001
2
614,400
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0.0001
3
819,200
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0.0001
4
1,024,000
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0.0001
5
1,228,800
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0.0001
6
1,433,600
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0.0001
7
1,638,400
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0.0001
8
1,843,200
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0.0001
9
2,048,000
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0.0001
10
2,252,800
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0.0001
11
2,457,600
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1.035158
1.047588
1.037423
1.044123
1.038726
1.045383
1.039451
1.039719
1.039762
1.044546
1.039988
1.039284
1.034831
0.0001
12
2,662,400
1.007386
1.018455
1.022786
1.029382
1.023257
1.035027
1.026096
1.037163
1.044958
1.038371
1.04447
1.039069
1.044259
1.0394
1.043647
1.039676
1.032107
1.034568
0.0001
13
2,867,200
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1.030189
1.029096
1.03619
1.03452
1.029353
1.036428
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1.037579
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1.038293
1.038598
1.038602
1.042043
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0.0001
14
3,072,000
1.020701
1.017279
1.031113
1.028761
1.033717
1.033542
1.041487
1.034864
1.035951
1.035813
1.037582
1.036517
1.030433
1.036859
1.033581
1.037096
1.033071
1.032591
0.0001
15
3,276,800
1.015371
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1.037518
1.028127
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1.026159
1.032189
1.041019
1.033188
1.040798
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1.038197
1.034199
1.039677
1.034432
1.032807
1.030494
0.0001
16
3,481,600
1.012878
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1.038282
1.026908
1.032942
1.027699
1.020731
1.027812
1.026818
1.028555
1.029841
1.029151
1.039506
1.029408
1.023031
1.029572
1.028004
1.02682
0.0001
17
3,686,400
1.014875
1.014355
1.010468
1.026363
1.01369
1.023472
1.025395
1.023179
1.033959
1.024199
1.028318
1.024999
1.035722
1.025309
1.024598
1.025417
1.023378
1.023412
0.0001
18
3,891,200
1.012429
1.01337
1.030494
1.021385
1.024797
1.01988
1.013989
1.020272
1.019769
1.02135
1.02907
1.022243
1.022836
1.0225
1.01664
1.022511
1.021253
1.020439
0.0001
19
4,096,000
1.016924
1.012683
1.02352
1.019289
1.024598
1.017472
1.021067
1.018321
1.007755
1.020236
1.02927
1.021203
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1.020874
1.020865
1.018901
0.0001
20
4,300,800
1.021292
1.011151
1.017415
1.014914
1.023737
1.015216
1.017271
1.016614
1.014507
1.017798
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1.018443
1.01372
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1.014543
1.018832
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1.016451
0.0001
21
4,505,600
1.010438
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1.013549
1.010805
1.013849
1.015015
1.01496
1.010747
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1.014969
0.0001
22
4,710,400
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1.013033
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1.01401
0.0001
23
4,915,200
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1.01
1.011559
1.012021
1.014458
1.01323
1.007674
1.014335
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1.014355
1.015232
1.012266
1.012885
0.0001
24
5,120,000
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1.007409
1.009732
1.008617
1.002989
1.011381
1.009756
1.012697
1.014649
1.013615
1.016511
1.014183
1.022166
1.014432
1.015852
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1.012212
1.012121
0.0001
25
5,324,800
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1.006773
1.015175
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1.010854
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1.006492
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1.025069
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1.013699
1.011619
0.0001
26
5,529,600
1.012384
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1.007285
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1.010532
1.014504
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1.004169
1.012986
1.017888
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1.013775
1.02286
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1.011248
0.0001
27
5,734,400
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1.005424
1.008684
1.006651
1.020196
1.010226
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0.0001
28
5,939,200
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0.0001
29
6,144,000
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0.0001
30
6,348,800
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0.0001
31
6,553,600
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0.0001
32
6,758,400
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0.0001
33
6,963,200
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34
7,168,000
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0.0001
35
7,372,800
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36
7,577,600
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0.0001
37
7,782,400
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38
7,987,200
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0.0001
39
8,192,000
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0.0001
40
8,396,800
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0.0001
41
8,601,600
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0.0001
42
8,806,400
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0.0001
43
9,011,200
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0.0001
44
9,216,000
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0.0001
45
9,420,800
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46
9,625,600
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0.0001
47
9,830,400
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0.0001
48
10,035,200
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0.0001
49
10,240,000
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0.0001
50
10,444,800
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1.009092
0.0001
51
10,649,600
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1.010038
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1.011698
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0.0001
52
10,854,400
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1.004241
1.004293
1.009017
1.0075
1.010862
1.008719
1.012225
1.010739
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0.0001
53
11,059,200
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1.008371
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1.011694
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1.020821
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0.0001
54
11,264,000
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1.008433
1.0228
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1.008829
0.0001
55
11,468,800
0.999141
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1.015631
1.008303
1.006472
1.009932
1.00447
1.010957
1.026978
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1.006727
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1.013045
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1.008734
0.0001
56
11,673,600
1.005692
1.001423
1.006163
1.003781
1.008433
1.00844
1.007036
1.010111
1.019441
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1.016982
1.01181
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1.012098
1.016862
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0.0001
57
11,878,400
1.007534
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0.997952
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0.98787
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1.012746
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1.009076
0.0001
58
12,083,200
1.005167
1.001498
1.000782
1.003864
1.011234
1.008121
1.001155
1.009701
1.013518
1.010751
1.01386
1.011366
1.00906
1.011624
1.020568
1.011825
1.009418
1.008594
0.0001
59
12,288,000
0.994744
1.001342
1.006335
1.0036
1.015003
1.008105
1.01078
1.009718
1.018624
1.010739
1.009438
1.011344
1.003942
1.011583
1.004083
1.011743
1.007869
1.008522
0.0001
60
12,492,800
0.998768
1.00132
0.989634
1.003775
1.014675
1.008002
1.018142
1.009587
1.025874
1.010653
1.000899
1.011291
1.013593
1.011556
1.016153
1.011734
1.009717
1.00849
0.0001
61
12,697,600
0.996695
1.001302
1.001304
1.003532
1.014521
1.008022
1.005077
1.009563
1.004527
1.010585
1.011964
1.011186
1.018062
1.011427
0.998916
1.011603
1.006383
1.008403
0.0001
62
12,902,400
1.005103
1.001381
0.995789
1.004124
1.013783
1.008047
1.006473
1.009621
1.018921
1.010731
1.022521
1.011421
1.000099
1.011704
1.021875
1.011857
1.01057
1.008611
0.0001
63
13,107,200
0.999106
1.001388
0.997415
1.003403
1.007726
1.008001
1.008814
1.009523
1.007548
1.010501
1.009311
1.011108
1.021789
1.011348
0.999744
1.011498
1.006432
1.008346
0.0001
64
13,312,000
0.990411
1.001253
1.001554
1.003568
1.013725
1.008209
1.011898
1.009616
1.013408
1.010517
0.998553
1.011068
1.004502
1.01128
1.013332
1.011428
1.005923
1.008367
0.0001
65
13,516,800
1.00432
1.001503
1.000546
1.003443
1.012067
1.007716
1.012172
1.009239
1.002525
1.010294
1.021696
1.010888
1.015941
1.011122
1.00922
1.011297
1.009811
1.008188
0.0001
66
13,721,600
1.004289
1.001248
1.007915
1.003338
1.00177
1.00759
1.006649
1.009095
1.014518
1.010147
1.014423
1.010758
1.012845
1.011009
1.008456
1.011178
1.008858
1.008045
0.0001
67
13,926,400
1.000277
1.001197
0.998891
1.003235
1.006825
1.007517
1.007723
1.009012
1.028311
1.010015
1.005356
1.010606
1.015348
1.010856
1.018745
1.011041
1.010184
1.007935
0.0001
68
14,131,200
0.999583
1.001177
1.002445
1.003117
1.003322
1.007397
1.014891
1.008835
1.014795
1.009829
1.01063
1.010411
1.016423
1.010645
1.005458
1.010819
1.008443
1.007779
0.0001
69
14,336,000
1.002689
1.001294
1.007002
1.003454
1.000422
1.008018
1.017326
1.009552
1.013438
1.010654
1.002189
1.011244
1.008769
1.011581
1.007498
1.011976
1.007417
1.008472
0.0001
70
14,540,800
1.003473
1.001117
1.01017
1.003099
0.999108
1.007146
0.992251
1.008529
1.014676
1.009502
1.013376
1.0101
1.020222
1.010378
1.015475
1.010587
1.008594
1.007557
0.0001
71
14,745,600
1.000165
1.001166
1.007858
1.002961
1.001434
1.007118
1.030339
1.008482
1.009045
1.009439
1.015653
1.010083
1.01674
1.010361
1.019284
1.01054
1.012565
1.007519
0.0001
72
14,950,400
1.01238
1.001891
0.996653
1.003106
0.995696
1.007069
1.013049
1.008287
1.011603
1.009171
1.014513
1.009737
1.014665
1.009976
1.01398
1.010158
1.009067
1.007424
0.0001
73
15,155,200
0.998548
1.001075
1.006159
1.002805
1.014543
1.007016
0.999633
1.008315
1.01658
1.009144
1.016081
1.009749
1.007047
1.010027
1.007733
1.01023
1.00829
1.007295
0.0001
74
15,360,000
0.996526
1.001088
0.999034
1.002778
0.997041
1.006868
0.997143
1.008238
1.007482
1.009391
1.005933
1.010302
1.014129
1.010787
1.027444
1.011077
1.005592
1.007566
0.0001
75
15,564,800
1.007319
1.0011
0.995332
1.002679
1.005043
1.006412
1.011994
1.007553
1.015703
1.008577
1.01559
1.009308
1.007344
1.009634
1.007072
1.009814
1.008175
1.006885
0.0001
76
15,769,600
0.990028
1.001134
1.002292
1.00237
1.005035
1.006109
1.016026
1.007327
0.999983
1.008266
1.021516
1.008834
1.016755
1.009088
1.012318
1.009319
1.007994
1.006556
0.0001
77
15,974,400
0.99202
1.001017
0.998532
1.002504
1.011204
1.006198
1.004505
1.007111
1.010876
1.007985
1.002271
1.008571
1.009565
1.008795
1.010046
1.008952
1.004877
1.006391
0.0001
78
16,179,200
1.007835
1.001204
1.012535
1.002932
1.003824
1.006104
1.010355
1.007031
1.001948
1.007867
1.001954
1.008433
1.007053
1.00875
1.014017
1.009081
1.00744
1.006425
0.0001
79
16,384,000
1.016439
1.001369
1.002543
1.002179
1.006939
1.005565
1.015008
1.006526
1.013538
1.007407
1.011132
1.007985
1.005088
1.008255
1.00558
1.008496
1.009533
1.005973
0.0001
80
16,588,800
0.99641
1.001092
0.997696
1.00275
1.007505
1.006245
1.008156
1.007243
1.020059
1.008253
1.016306
1.008874
0.994489
1.009265
1.000118
1.009708
1.005092
1.006679
0.0001
81
16,793,600
1.0062
1.000967
0.999124
1.002046
1.007406
1.005114
1.018812
1.005993
1.005279
1.006872
1.010616
1.007472
1.02415
1.007736
0.999962
1.00795
1.008943
1.005519
0.0001
82
16,998,400
0.990507
1.000947
1.008273
1.001735
0.996279
1.004999
1.011257
1.005784
1.005051
1.006628
1.010672
1.007183
1.002224
1.007434
1.004166
1.00767
1.003554
1.005298
0.0001
83
17,203,200
1.013479
1.00099
1.001859
1.001717
1.005536
1.004752
1.00613
1.005524
1.00878
1.006354
0.996286
1.006895
1.005725
1.00719
1.015098
1.007517
1.006612
1.005117
0.0001
84
17,408,000
1.003217
1.001003
0.996893
1.001434
0.998463
1.004271
1.02311
1.005287
1.010496
1.006078
1.012151
1.006611
1.011528
1.006841
1.018918
1.007051
1.009347
1.004822
0.0001
85
17,612,800
1.000348
1.000963
1.009461
1.001395
1.008117
1.00402
1.008571
1.004766
0.999956
1.00559
1.003391
1.006087
1.00471
1.006294
1.007991
1.006497
1.005318
1.004451
0.0001
86
17,817,600
1.010518
1.000889
1.001097
1.001571
0.989483
1.003987
1.007893
1.004214
1.004008
1.004815
1.005957
1.005288
1.011102
1.005555
0.999552
1.005827
1.003701
1.004018
0.0001
87
18,022,400
0.996658
1.000941
1.010125
1.001157
1.002264
1.003025
1.003955
1.003582
1.005846
1.004166
1.011291
1.004613
1.002633
1.004865
1.011942
1.005134
1.005589
1.003435
0.0001
88
18,227,200
0.996095
1.001536
1.004512
1.001617
1.000971
1.003477
0.993569
1.00371
0.994631
1.004253
1.010041
1.004658
1.002576
1.004876
1.00736
1.005116
1.001219
1.003655
0.0001
89
18,432,000
0.994205
1.000883
1.006544
1.000963
1.010335
1.002606
0.997277
1.003035
0.99777
1.003582
1.007605
1.004021
1.006035
1.004236
1.010733
1.004455
1.003813
1.002973
0.0001
90
18,636,800
0.992533
1.000881
0.998571
1.001
1.009464
1.002266
0.995479
1.002609
0.996069
1.003134
0.998817
1.003552
1.00494
1.003804
1.007354
1.00408
1.000403
1.002666
0.0001
91
18,841,600
1.021639
1.000814
1.003785
1.001084
1.004757
1.002282
0.998617
1.002583
0.999576
1.00312
1.002707
1.003576
1.002952
1.003857
1.00764
1.004158
1.005209
1.002684
0.0001
92
19,046,400
1.011244
1.000925
1.007521
1.001074
0.995833
1.00205
1.006157
1.002211
0.998918
1.002691
1.001783
1.003096
1.009807
1.003343
1.000064
1.003616
1.003916
1.002376
0.0001
93
19,251,200
1.011152
1.000733
1.004261
1.000914
1.009482
1.001801
0.987969
1.001845
1.006477
1.002241
0.994011
1.002624
1.005222
1.002817
1.008234
1.003015
1.003351
1.001999
0.0001
94
19,456,000
0.990539
1.000689
1.009382
1.001032
1.007647
1.001695
1.001419
1.001864
1.006753
1.002342
0.998934
1.002714
0.99166
1.002907
1.012508
1.003117
1.002355
1.002045
0.0001
95
19,660,800
0.984241
1.000998
1.008866
1.000807
1.001731
1.00156
1.002615
1.001444
1.001826
1.001759
1.002415
1.002143
1.002772
1.002405
1.008693
1.002684
1.001645
1.001725
0.0001
96
19,865,600
1.011041
1.000667
1.006304
1.000999
1.005141
1.001692
1.01007
1.001526
1.00565
1.001828
1.002699
1.002164
0.999506
1.002347
1.005158
1.002543
1.005696
1.001721
0.0001
97
20,070,400
1.001043
1.000678
1.012583
1.000818
0.981583
1.001366
0.994352
1.001268
0.992302
1.001554
1.002264
1.001844
0.99576
1.002015
0.998049
1.00222
0.997242
1.00147
0.0001
98
20,275,200
0.996965
1.000613
1.00071
1.001283
1.009496
1.001375
1.003687
1.001221
0.999965
1.001419
1.006416
1.001691
0.997098
1.001862
0.999987
1.002057
1.001791
1.00144
0.0001
End of preview. Expand in Data Studio

Epsilon-Transformers Belief Analysis Dataset

This dataset contains trained neural network models and their corresponding belief state regression analysis from the Epsilon-Transformers project. The models were trained on four different stochastic processes and analyzed for their ability to learn and represent belief states. See https://github.com/adamimos/epsilon-transformers/tree/quantum-public for codebase which generated this data.

Dataset Structure

epsilon-transformers-belief-analysis/
β”œβ”€β”€ README.md
β”œβ”€β”€ models/          # Model checkpoints and configurations from S3
β”‚   β”œβ”€β”€ {sweep_id}_{run_id}/
β”‚   β”‚   β”œβ”€β”€ 0.pt                    # Initial checkpoint
β”‚   β”‚   β”œβ”€β”€ {final}.pt              # Final checkpoint
β”‚   β”‚   β”œβ”€β”€ run_config.yaml         # Training configuration
β”‚   β”‚   └── loss.csv                # Training loss data
β”‚   └── ...
└── analysis/        # Belief state regression analysis results
    β”œβ”€β”€ {sweep_id}_{run_id}/
    β”‚   β”œβ”€β”€ checkpoint_0.joblib              # Initial checkpoint analysis
    β”‚   β”œβ”€β”€ checkpoint_{final}.joblib        # Final checkpoint analysis
    β”‚   β”œβ”€β”€ ground_truth_data.joblib         # Neural network ground truth
    β”‚   β”œβ”€β”€ markov3_checkpoint_*.joblib      # Classical Markov comparisons
    β”‚   └── markov3_ground_truth_data.joblib # Classical ground truth
    └── ...

Model Mappings

Sweep ID Run ID Architecture Process Description
20241121152808 48 LSTM Moon Process LSTM trained on Moon Process
20241121152808 49 LSTM Bloch Walk LSTM trained on Bloch Walk
20241121152808 53 LSTM FRDN LSTM trained on FRDN
20241121152808 55 LSTM Mess3 LSTM trained on Mess3
20241121152808 56 GRU Moon Process GRU trained on Moon Process
20241121152808 57 GRU Bloch Walk GRU trained on Bloch Walk
20241121152808 61 GRU FRDN GRU trained on FRDN
20241121152808 63 GRU Mess3 GRU trained on Mess3
20241121152808 64 RNN Moon Process RNN trained on Moon Process
20241121152808 65 RNN Bloch Walk RNN trained on Bloch Walk
20241121152808 69 RNN FRDN RNN trained on FRDN
20241121152808 71 RNN Mess3 RNN trained on Mess3
20241205175736 17 Transformer Bloch Walk Transformer trained on Bloch Walk
20241205175736 23 Transformer Mess3 Transformer trained on Mess3
20250421221507 0 Transformer Moon Process Transformer trained on Moon Process
20250422023003 1 Transformer FRDN Transformer trained on FRDN

File Formats

Model Files (.pt)

Transformerlens (for transformers) or Pytorch (for RNNs) model checkpoints containing trained model weights and optimizer states.

Analysis Files (.joblib)

Joblib-serialized files containing:

  • checkpoint_*.joblib: Regression analysis results mapping activations to belief states
  • ground_truth_data.joblib: True belief states and probabilities for the neural network data
  • markov3_*.joblib: Classical Markov model comparisons and baselines
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