bxiong commited on
Commit
56419c1
·
verified ·
1 Parent(s): c0d8b34

Add files using upload-large-folder tool

Browse files
This view is limited to 50 files because it contains too many changes.   See raw diff
Files changed (50) hide show
  1. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-480/trainer_state.json +753 -0
  2. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-490/README.md +202 -0
  3. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-490/adapter_config.json +31 -0
  4. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-490/trainer_state.json +768 -0
  5. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-500/README.md +202 -0
  6. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-500/adapter_config.json +31 -0
  7. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-500/trainer_state.json +783 -0
  8. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-510/README.md +202 -0
  9. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-510/adapter_config.json +31 -0
  10. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-510/trainer_state.json +798 -0
  11. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-520/README.md +202 -0
  12. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-520/adapter_config.json +31 -0
  13. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-520/trainer_state.json +813 -0
  14. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-530/README.md +202 -0
  15. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-530/adapter_config.json +31 -0
  16. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-530/trainer_state.json +828 -0
  17. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-540/README.md +202 -0
  18. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-540/adapter_config.json +31 -0
  19. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-540/trainer_state.json +843 -0
  20. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-550/README.md +202 -0
  21. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-550/adapter_config.json +31 -0
  22. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-550/trainer_state.json +858 -0
  23. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-560/README.md +202 -0
  24. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-560/adapter_config.json +31 -0
  25. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-560/trainer_state.json +873 -0
  26. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-570/README.md +202 -0
  27. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-570/adapter_config.json +31 -0
  28. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-570/trainer_state.json +888 -0
  29. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-580/README.md +202 -0
  30. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-580/adapter_config.json +31 -0
  31. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-580/trainer_state.json +903 -0
  32. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-590/README.md +202 -0
  33. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-590/adapter_config.json +31 -0
  34. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-590/trainer_state.json +918 -0
  35. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-600/README.md +202 -0
  36. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-600/adapter_config.json +31 -0
  37. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-600/trainer_state.json +933 -0
  38. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-610/README.md +202 -0
  39. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-610/adapter_config.json +31 -0
  40. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-610/trainer_state.json +948 -0
  41. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-620/README.md +202 -0
  42. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-620/adapter_config.json +31 -0
  43. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-620/trainer_state.json +963 -0
  44. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-630/README.md +202 -0
  45. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-630/adapter_config.json +31 -0
  46. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-630/trainer_state.json +978 -0
  47. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-640/README.md +202 -0
  48. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-640/adapter_config.json +31 -0
  49. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-640/trainer_state.json +993 -0
  50. output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-650/README.md +202 -0
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-480/trainer_state.json ADDED
@@ -0,0 +1,753 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 2.535032033920288,
3
+ "best_model_checkpoint": "./output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-150",
4
+ "epoch": 6.4,
5
+ "eval_steps": 10,
6
+ "global_step": 480,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.13333333333333333,
13
+ "grad_norm": 0.36938729882240295,
14
+ "learning_rate": 7.881481481481482e-05,
15
+ "loss": 2.519,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.13333333333333333,
20
+ "eval_loss": 2.579638957977295,
21
+ "eval_runtime": 43.8215,
22
+ "eval_samples_per_second": 22.82,
23
+ "eval_steps_per_second": 2.852,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.26666666666666666,
28
+ "grad_norm": 0.39850670099258423,
29
+ "learning_rate": 7.762962962962963e-05,
30
+ "loss": 2.5224,
31
+ "step": 20
32
+ },
33
+ {
34
+ "epoch": 0.26666666666666666,
35
+ "eval_loss": 2.5729691982269287,
36
+ "eval_runtime": 43.8179,
37
+ "eval_samples_per_second": 22.822,
38
+ "eval_steps_per_second": 2.853,
39
+ "step": 20
40
+ },
41
+ {
42
+ "epoch": 0.4,
43
+ "grad_norm": 0.40211933851242065,
44
+ "learning_rate": 7.644444444444445e-05,
45
+ "loss": 2.5169,
46
+ "step": 30
47
+ },
48
+ {
49
+ "epoch": 0.4,
50
+ "eval_loss": 2.567735433578491,
51
+ "eval_runtime": 43.8366,
52
+ "eval_samples_per_second": 22.812,
53
+ "eval_steps_per_second": 2.851,
54
+ "step": 30
55
+ },
56
+ {
57
+ "epoch": 0.5333333333333333,
58
+ "grad_norm": 0.6892333030700684,
59
+ "learning_rate": 7.525925925925926e-05,
60
+ "loss": 2.5784,
61
+ "step": 40
62
+ },
63
+ {
64
+ "epoch": 0.5333333333333333,
65
+ "eval_loss": 2.562650442123413,
66
+ "eval_runtime": 43.8377,
67
+ "eval_samples_per_second": 22.811,
68
+ "eval_steps_per_second": 2.851,
69
+ "step": 40
70
+ },
71
+ {
72
+ "epoch": 0.6666666666666666,
73
+ "grad_norm": 0.442343533039093,
74
+ "learning_rate": 7.407407407407409e-05,
75
+ "loss": 2.5431,
76
+ "step": 50
77
+ },
78
+ {
79
+ "epoch": 0.6666666666666666,
80
+ "eval_loss": 2.556513786315918,
81
+ "eval_runtime": 43.8656,
82
+ "eval_samples_per_second": 22.797,
83
+ "eval_steps_per_second": 2.85,
84
+ "step": 50
85
+ },
86
+ {
87
+ "epoch": 0.8,
88
+ "grad_norm": 0.4059845805168152,
89
+ "learning_rate": 7.28888888888889e-05,
90
+ "loss": 2.4936,
91
+ "step": 60
92
+ },
93
+ {
94
+ "epoch": 0.8,
95
+ "eval_loss": 2.552133798599243,
96
+ "eval_runtime": 43.8403,
97
+ "eval_samples_per_second": 22.81,
98
+ "eval_steps_per_second": 2.851,
99
+ "step": 60
100
+ },
101
+ {
102
+ "epoch": 0.9333333333333333,
103
+ "grad_norm": 0.48126307129859924,
104
+ "learning_rate": 7.170370370370371e-05,
105
+ "loss": 2.4901,
106
+ "step": 70
107
+ },
108
+ {
109
+ "epoch": 0.9333333333333333,
110
+ "eval_loss": 2.5477023124694824,
111
+ "eval_runtime": 43.8351,
112
+ "eval_samples_per_second": 22.813,
113
+ "eval_steps_per_second": 2.852,
114
+ "step": 70
115
+ },
116
+ {
117
+ "epoch": 1.0666666666666667,
118
+ "grad_norm": 0.48629865050315857,
119
+ "learning_rate": 7.051851851851853e-05,
120
+ "loss": 2.5114,
121
+ "step": 80
122
+ },
123
+ {
124
+ "epoch": 1.0666666666666667,
125
+ "eval_loss": 2.543431043624878,
126
+ "eval_runtime": 43.8432,
127
+ "eval_samples_per_second": 22.809,
128
+ "eval_steps_per_second": 2.851,
129
+ "step": 80
130
+ },
131
+ {
132
+ "epoch": 1.2,
133
+ "grad_norm": 0.5880796313285828,
134
+ "learning_rate": 6.933333333333334e-05,
135
+ "loss": 2.4446,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 1.2,
140
+ "eval_loss": 2.544339418411255,
141
+ "eval_runtime": 43.8437,
142
+ "eval_samples_per_second": 22.808,
143
+ "eval_steps_per_second": 2.851,
144
+ "step": 90
145
+ },
146
+ {
147
+ "epoch": 1.3333333333333333,
148
+ "grad_norm": 0.6746829748153687,
149
+ "learning_rate": 6.814814814814815e-05,
150
+ "loss": 2.4477,
151
+ "step": 100
152
+ },
153
+ {
154
+ "epoch": 1.3333333333333333,
155
+ "eval_loss": 2.544358968734741,
156
+ "eval_runtime": 43.8613,
157
+ "eval_samples_per_second": 22.799,
158
+ "eval_steps_per_second": 2.85,
159
+ "step": 100
160
+ },
161
+ {
162
+ "epoch": 1.4666666666666668,
163
+ "grad_norm": 0.8208937048912048,
164
+ "learning_rate": 6.696296296296296e-05,
165
+ "loss": 2.4004,
166
+ "step": 110
167
+ },
168
+ {
169
+ "epoch": 1.4666666666666668,
170
+ "eval_loss": 2.54068660736084,
171
+ "eval_runtime": 43.8426,
172
+ "eval_samples_per_second": 22.809,
173
+ "eval_steps_per_second": 2.851,
174
+ "step": 110
175
+ },
176
+ {
177
+ "epoch": 1.6,
178
+ "grad_norm": 0.925931453704834,
179
+ "learning_rate": 6.577777777777777e-05,
180
+ "loss": 2.3889,
181
+ "step": 120
182
+ },
183
+ {
184
+ "epoch": 1.6,
185
+ "eval_loss": 2.5393033027648926,
186
+ "eval_runtime": 43.8383,
187
+ "eval_samples_per_second": 22.811,
188
+ "eval_steps_per_second": 2.851,
189
+ "step": 120
190
+ },
191
+ {
192
+ "epoch": 1.7333333333333334,
193
+ "grad_norm": 0.8785662055015564,
194
+ "learning_rate": 6.45925925925926e-05,
195
+ "loss": 2.3959,
196
+ "step": 130
197
+ },
198
+ {
199
+ "epoch": 1.7333333333333334,
200
+ "eval_loss": 2.5367038249969482,
201
+ "eval_runtime": 43.8508,
202
+ "eval_samples_per_second": 22.805,
203
+ "eval_steps_per_second": 2.851,
204
+ "step": 130
205
+ },
206
+ {
207
+ "epoch": 1.8666666666666667,
208
+ "grad_norm": 0.941368818283081,
209
+ "learning_rate": 6.340740740740741e-05,
210
+ "loss": 2.3924,
211
+ "step": 140
212
+ },
213
+ {
214
+ "epoch": 1.8666666666666667,
215
+ "eval_loss": 2.535139560699463,
216
+ "eval_runtime": 43.8588,
217
+ "eval_samples_per_second": 22.8,
218
+ "eval_steps_per_second": 2.85,
219
+ "step": 140
220
+ },
221
+ {
222
+ "epoch": 2.0,
223
+ "grad_norm": 0.9578835368156433,
224
+ "learning_rate": 6.222222222222223e-05,
225
+ "loss": 2.4278,
226
+ "step": 150
227
+ },
228
+ {
229
+ "epoch": 2.0,
230
+ "eval_loss": 2.535032033920288,
231
+ "eval_runtime": 43.8484,
232
+ "eval_samples_per_second": 22.806,
233
+ "eval_steps_per_second": 2.851,
234
+ "step": 150
235
+ },
236
+ {
237
+ "epoch": 2.1333333333333333,
238
+ "grad_norm": 1.1541856527328491,
239
+ "learning_rate": 6.103703703703704e-05,
240
+ "loss": 2.2895,
241
+ "step": 160
242
+ },
243
+ {
244
+ "epoch": 2.1333333333333333,
245
+ "eval_loss": 2.564768075942993,
246
+ "eval_runtime": 43.8568,
247
+ "eval_samples_per_second": 22.801,
248
+ "eval_steps_per_second": 2.85,
249
+ "step": 160
250
+ },
251
+ {
252
+ "epoch": 2.2666666666666666,
253
+ "grad_norm": 1.4076604843139648,
254
+ "learning_rate": 5.9851851851851855e-05,
255
+ "loss": 2.2107,
256
+ "step": 170
257
+ },
258
+ {
259
+ "epoch": 2.2666666666666666,
260
+ "eval_loss": 2.5832314491271973,
261
+ "eval_runtime": 43.8455,
262
+ "eval_samples_per_second": 22.807,
263
+ "eval_steps_per_second": 2.851,
264
+ "step": 170
265
+ },
266
+ {
267
+ "epoch": 2.4,
268
+ "grad_norm": 1.4847813844680786,
269
+ "learning_rate": 5.8666666666666665e-05,
270
+ "loss": 2.2588,
271
+ "step": 180
272
+ },
273
+ {
274
+ "epoch": 2.4,
275
+ "eval_loss": 2.5781586170196533,
276
+ "eval_runtime": 43.8578,
277
+ "eval_samples_per_second": 22.801,
278
+ "eval_steps_per_second": 2.85,
279
+ "step": 180
280
+ },
281
+ {
282
+ "epoch": 2.533333333333333,
283
+ "grad_norm": 1.5135377645492554,
284
+ "learning_rate": 5.748148148148149e-05,
285
+ "loss": 2.2099,
286
+ "step": 190
287
+ },
288
+ {
289
+ "epoch": 2.533333333333333,
290
+ "eval_loss": 2.5752007961273193,
291
+ "eval_runtime": 43.8521,
292
+ "eval_samples_per_second": 22.804,
293
+ "eval_steps_per_second": 2.85,
294
+ "step": 190
295
+ },
296
+ {
297
+ "epoch": 2.6666666666666665,
298
+ "grad_norm": 1.5297592878341675,
299
+ "learning_rate": 5.62962962962963e-05,
300
+ "loss": 2.2965,
301
+ "step": 200
302
+ },
303
+ {
304
+ "epoch": 2.6666666666666665,
305
+ "eval_loss": 2.579918622970581,
306
+ "eval_runtime": 43.8661,
307
+ "eval_samples_per_second": 22.797,
308
+ "eval_steps_per_second": 2.85,
309
+ "step": 200
310
+ },
311
+ {
312
+ "epoch": 2.8,
313
+ "grad_norm": 1.6282892227172852,
314
+ "learning_rate": 5.511111111111112e-05,
315
+ "loss": 2.2487,
316
+ "step": 210
317
+ },
318
+ {
319
+ "epoch": 2.8,
320
+ "eval_loss": 2.5760037899017334,
321
+ "eval_runtime": 43.8379,
322
+ "eval_samples_per_second": 22.811,
323
+ "eval_steps_per_second": 2.851,
324
+ "step": 210
325
+ },
326
+ {
327
+ "epoch": 2.9333333333333336,
328
+ "grad_norm": 1.74424409866333,
329
+ "learning_rate": 5.392592592592593e-05,
330
+ "loss": 2.2049,
331
+ "step": 220
332
+ },
333
+ {
334
+ "epoch": 2.9333333333333336,
335
+ "eval_loss": 2.576190233230591,
336
+ "eval_runtime": 43.8491,
337
+ "eval_samples_per_second": 22.805,
338
+ "eval_steps_per_second": 2.851,
339
+ "step": 220
340
+ },
341
+ {
342
+ "epoch": 3.066666666666667,
343
+ "grad_norm": 1.654069423675537,
344
+ "learning_rate": 5.274074074074074e-05,
345
+ "loss": 2.1188,
346
+ "step": 230
347
+ },
348
+ {
349
+ "epoch": 3.066666666666667,
350
+ "eval_loss": 2.5971405506134033,
351
+ "eval_runtime": 43.855,
352
+ "eval_samples_per_second": 22.802,
353
+ "eval_steps_per_second": 2.85,
354
+ "step": 230
355
+ },
356
+ {
357
+ "epoch": 3.2,
358
+ "grad_norm": 2.541767120361328,
359
+ "learning_rate": 5.155555555555556e-05,
360
+ "loss": 2.0788,
361
+ "step": 240
362
+ },
363
+ {
364
+ "epoch": 3.2,
365
+ "eval_loss": 2.6767666339874268,
366
+ "eval_runtime": 43.8368,
367
+ "eval_samples_per_second": 22.812,
368
+ "eval_steps_per_second": 2.851,
369
+ "step": 240
370
+ },
371
+ {
372
+ "epoch": 3.3333333333333335,
373
+ "grad_norm": 2.0508077144622803,
374
+ "learning_rate": 5.037037037037037e-05,
375
+ "loss": 2.0784,
376
+ "step": 250
377
+ },
378
+ {
379
+ "epoch": 3.3333333333333335,
380
+ "eval_loss": 2.6486454010009766,
381
+ "eval_runtime": 43.8529,
382
+ "eval_samples_per_second": 22.803,
383
+ "eval_steps_per_second": 2.85,
384
+ "step": 250
385
+ },
386
+ {
387
+ "epoch": 3.466666666666667,
388
+ "grad_norm": 2.1096036434173584,
389
+ "learning_rate": 4.918518518518519e-05,
390
+ "loss": 2.0633,
391
+ "step": 260
392
+ },
393
+ {
394
+ "epoch": 3.466666666666667,
395
+ "eval_loss": 2.6501405239105225,
396
+ "eval_runtime": 43.8632,
397
+ "eval_samples_per_second": 22.798,
398
+ "eval_steps_per_second": 2.85,
399
+ "step": 260
400
+ },
401
+ {
402
+ "epoch": 3.6,
403
+ "grad_norm": 2.3028736114501953,
404
+ "learning_rate": 4.8e-05,
405
+ "loss": 2.0722,
406
+ "step": 270
407
+ },
408
+ {
409
+ "epoch": 3.6,
410
+ "eval_loss": 2.657053232192993,
411
+ "eval_runtime": 43.8423,
412
+ "eval_samples_per_second": 22.809,
413
+ "eval_steps_per_second": 2.851,
414
+ "step": 270
415
+ },
416
+ {
417
+ "epoch": 3.7333333333333334,
418
+ "grad_norm": 2.1536757946014404,
419
+ "learning_rate": 4.681481481481481e-05,
420
+ "loss": 2.0155,
421
+ "step": 280
422
+ },
423
+ {
424
+ "epoch": 3.7333333333333334,
425
+ "eval_loss": 2.648275375366211,
426
+ "eval_runtime": 43.8328,
427
+ "eval_samples_per_second": 22.814,
428
+ "eval_steps_per_second": 2.852,
429
+ "step": 280
430
+ },
431
+ {
432
+ "epoch": 3.8666666666666667,
433
+ "grad_norm": 2.4079270362854004,
434
+ "learning_rate": 4.5629629629629636e-05,
435
+ "loss": 2.1111,
436
+ "step": 290
437
+ },
438
+ {
439
+ "epoch": 3.8666666666666667,
440
+ "eval_loss": 2.650322675704956,
441
+ "eval_runtime": 43.835,
442
+ "eval_samples_per_second": 22.813,
443
+ "eval_steps_per_second": 2.852,
444
+ "step": 290
445
+ },
446
+ {
447
+ "epoch": 4.0,
448
+ "grad_norm": 2.426234722137451,
449
+ "learning_rate": 4.444444444444445e-05,
450
+ "loss": 2.041,
451
+ "step": 300
452
+ },
453
+ {
454
+ "epoch": 4.0,
455
+ "eval_loss": 2.6490862369537354,
456
+ "eval_runtime": 43.845,
457
+ "eval_samples_per_second": 22.808,
458
+ "eval_steps_per_second": 2.851,
459
+ "step": 300
460
+ },
461
+ {
462
+ "epoch": 4.133333333333334,
463
+ "grad_norm": 2.8063745498657227,
464
+ "learning_rate": 4.3259259259259264e-05,
465
+ "loss": 1.9316,
466
+ "step": 310
467
+ },
468
+ {
469
+ "epoch": 4.133333333333334,
470
+ "eval_loss": 2.7609620094299316,
471
+ "eval_runtime": 43.8481,
472
+ "eval_samples_per_second": 22.806,
473
+ "eval_steps_per_second": 2.851,
474
+ "step": 310
475
+ },
476
+ {
477
+ "epoch": 4.266666666666667,
478
+ "grad_norm": 2.96854305267334,
479
+ "learning_rate": 4.2074074074074075e-05,
480
+ "loss": 1.8889,
481
+ "step": 320
482
+ },
483
+ {
484
+ "epoch": 4.266666666666667,
485
+ "eval_loss": 2.736968994140625,
486
+ "eval_runtime": 43.8633,
487
+ "eval_samples_per_second": 22.798,
488
+ "eval_steps_per_second": 2.85,
489
+ "step": 320
490
+ },
491
+ {
492
+ "epoch": 4.4,
493
+ "grad_norm": 2.637695789337158,
494
+ "learning_rate": 4.088888888888889e-05,
495
+ "loss": 1.9187,
496
+ "step": 330
497
+ },
498
+ {
499
+ "epoch": 4.4,
500
+ "eval_loss": 2.7382876873016357,
501
+ "eval_runtime": 43.8486,
502
+ "eval_samples_per_second": 22.806,
503
+ "eval_steps_per_second": 2.851,
504
+ "step": 330
505
+ },
506
+ {
507
+ "epoch": 4.533333333333333,
508
+ "grad_norm": 2.9106290340423584,
509
+ "learning_rate": 3.970370370370371e-05,
510
+ "loss": 1.9002,
511
+ "step": 340
512
+ },
513
+ {
514
+ "epoch": 4.533333333333333,
515
+ "eval_loss": 2.734544515609741,
516
+ "eval_runtime": 43.8491,
517
+ "eval_samples_per_second": 22.805,
518
+ "eval_steps_per_second": 2.851,
519
+ "step": 340
520
+ },
521
+ {
522
+ "epoch": 4.666666666666667,
523
+ "grad_norm": 2.769315481185913,
524
+ "learning_rate": 3.851851851851852e-05,
525
+ "loss": 1.9251,
526
+ "step": 350
527
+ },
528
+ {
529
+ "epoch": 4.666666666666667,
530
+ "eval_loss": 2.734708070755005,
531
+ "eval_runtime": 43.8534,
532
+ "eval_samples_per_second": 22.803,
533
+ "eval_steps_per_second": 2.85,
534
+ "step": 350
535
+ },
536
+ {
537
+ "epoch": 4.8,
538
+ "grad_norm": 2.940281867980957,
539
+ "learning_rate": 3.733333333333334e-05,
540
+ "loss": 1.9319,
541
+ "step": 360
542
+ },
543
+ {
544
+ "epoch": 4.8,
545
+ "eval_loss": 2.7300503253936768,
546
+ "eval_runtime": 43.9017,
547
+ "eval_samples_per_second": 22.778,
548
+ "eval_steps_per_second": 2.847,
549
+ "step": 360
550
+ },
551
+ {
552
+ "epoch": 4.933333333333334,
553
+ "grad_norm": 2.8305609226226807,
554
+ "learning_rate": 3.614814814814815e-05,
555
+ "loss": 1.9332,
556
+ "step": 370
557
+ },
558
+ {
559
+ "epoch": 4.933333333333334,
560
+ "eval_loss": 2.7309281826019287,
561
+ "eval_runtime": 43.8842,
562
+ "eval_samples_per_second": 22.787,
563
+ "eval_steps_per_second": 2.848,
564
+ "step": 370
565
+ },
566
+ {
567
+ "epoch": 5.066666666666666,
568
+ "grad_norm": 2.8739213943481445,
569
+ "learning_rate": 3.4962962962962965e-05,
570
+ "loss": 1.8846,
571
+ "step": 380
572
+ },
573
+ {
574
+ "epoch": 5.066666666666666,
575
+ "eval_loss": 2.76513671875,
576
+ "eval_runtime": 43.906,
577
+ "eval_samples_per_second": 22.776,
578
+ "eval_steps_per_second": 2.847,
579
+ "step": 380
580
+ },
581
+ {
582
+ "epoch": 5.2,
583
+ "grad_norm": 3.9025838375091553,
584
+ "learning_rate": 3.377777777777778e-05,
585
+ "loss": 1.7575,
586
+ "step": 390
587
+ },
588
+ {
589
+ "epoch": 5.2,
590
+ "eval_loss": 2.847782611846924,
591
+ "eval_runtime": 43.8665,
592
+ "eval_samples_per_second": 22.796,
593
+ "eval_steps_per_second": 2.85,
594
+ "step": 390
595
+ },
596
+ {
597
+ "epoch": 5.333333333333333,
598
+ "grad_norm": 3.299649715423584,
599
+ "learning_rate": 3.259259259259259e-05,
600
+ "loss": 1.7713,
601
+ "step": 400
602
+ },
603
+ {
604
+ "epoch": 5.333333333333333,
605
+ "eval_loss": 2.8094286918640137,
606
+ "eval_runtime": 43.8629,
607
+ "eval_samples_per_second": 22.798,
608
+ "eval_steps_per_second": 2.85,
609
+ "step": 400
610
+ },
611
+ {
612
+ "epoch": 5.466666666666667,
613
+ "grad_norm": 3.4474265575408936,
614
+ "learning_rate": 3.140740740740741e-05,
615
+ "loss": 1.7983,
616
+ "step": 410
617
+ },
618
+ {
619
+ "epoch": 5.466666666666667,
620
+ "eval_loss": 2.827517509460449,
621
+ "eval_runtime": 43.8611,
622
+ "eval_samples_per_second": 22.799,
623
+ "eval_steps_per_second": 2.85,
624
+ "step": 410
625
+ },
626
+ {
627
+ "epoch": 5.6,
628
+ "grad_norm": 3.1924540996551514,
629
+ "learning_rate": 3.0222222222222225e-05,
630
+ "loss": 1.8091,
631
+ "step": 420
632
+ },
633
+ {
634
+ "epoch": 5.6,
635
+ "eval_loss": 2.81618332862854,
636
+ "eval_runtime": 43.8544,
637
+ "eval_samples_per_second": 22.803,
638
+ "eval_steps_per_second": 2.85,
639
+ "step": 420
640
+ },
641
+ {
642
+ "epoch": 5.733333333333333,
643
+ "grad_norm": 3.5224015712738037,
644
+ "learning_rate": 2.9037037037037042e-05,
645
+ "loss": 1.8253,
646
+ "step": 430
647
+ },
648
+ {
649
+ "epoch": 5.733333333333333,
650
+ "eval_loss": 2.816711187362671,
651
+ "eval_runtime": 43.8685,
652
+ "eval_samples_per_second": 22.795,
653
+ "eval_steps_per_second": 2.849,
654
+ "step": 430
655
+ },
656
+ {
657
+ "epoch": 5.866666666666667,
658
+ "grad_norm": 3.60918927192688,
659
+ "learning_rate": 2.7851851851851856e-05,
660
+ "loss": 1.8013,
661
+ "step": 440
662
+ },
663
+ {
664
+ "epoch": 5.866666666666667,
665
+ "eval_loss": 2.8146169185638428,
666
+ "eval_runtime": 43.8516,
667
+ "eval_samples_per_second": 22.804,
668
+ "eval_steps_per_second": 2.851,
669
+ "step": 440
670
+ },
671
+ {
672
+ "epoch": 6.0,
673
+ "grad_norm": 3.5798070430755615,
674
+ "learning_rate": 2.6666666666666667e-05,
675
+ "loss": 1.8258,
676
+ "step": 450
677
+ },
678
+ {
679
+ "epoch": 6.0,
680
+ "eval_loss": 2.8134233951568604,
681
+ "eval_runtime": 43.8442,
682
+ "eval_samples_per_second": 22.808,
683
+ "eval_steps_per_second": 2.851,
684
+ "step": 450
685
+ },
686
+ {
687
+ "epoch": 6.133333333333334,
688
+ "grad_norm": 5.563477993011475,
689
+ "learning_rate": 2.5481481481481484e-05,
690
+ "loss": 1.6649,
691
+ "step": 460
692
+ },
693
+ {
694
+ "epoch": 6.133333333333334,
695
+ "eval_loss": 2.9189789295196533,
696
+ "eval_runtime": 43.8602,
697
+ "eval_samples_per_second": 22.8,
698
+ "eval_steps_per_second": 2.85,
699
+ "step": 460
700
+ },
701
+ {
702
+ "epoch": 6.266666666666667,
703
+ "grad_norm": 4.192393779754639,
704
+ "learning_rate": 2.4296296296296298e-05,
705
+ "loss": 1.7443,
706
+ "step": 470
707
+ },
708
+ {
709
+ "epoch": 6.266666666666667,
710
+ "eval_loss": 2.893780469894409,
711
+ "eval_runtime": 43.8434,
712
+ "eval_samples_per_second": 22.808,
713
+ "eval_steps_per_second": 2.851,
714
+ "step": 470
715
+ },
716
+ {
717
+ "epoch": 6.4,
718
+ "grad_norm": 4.8650593757629395,
719
+ "learning_rate": 2.3111111111111112e-05,
720
+ "loss": 1.6961,
721
+ "step": 480
722
+ },
723
+ {
724
+ "epoch": 6.4,
725
+ "eval_loss": 2.8861398696899414,
726
+ "eval_runtime": 43.8417,
727
+ "eval_samples_per_second": 22.809,
728
+ "eval_steps_per_second": 2.851,
729
+ "step": 480
730
+ }
731
+ ],
732
+ "logging_steps": 10,
733
+ "max_steps": 675,
734
+ "num_input_tokens_seen": 0,
735
+ "num_train_epochs": 9,
736
+ "save_steps": 10,
737
+ "stateful_callbacks": {
738
+ "TrainerControl": {
739
+ "args": {
740
+ "should_epoch_stop": false,
741
+ "should_evaluate": false,
742
+ "should_log": false,
743
+ "should_save": true,
744
+ "should_training_stop": false
745
+ },
746
+ "attributes": {}
747
+ }
748
+ },
749
+ "total_flos": 7.86531455336448e+16,
750
+ "train_batch_size": 8,
751
+ "trial_name": null,
752
+ "trial_params": null
753
+ }
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-490/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/pythia-6_9b
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-490/adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/workspace/pythia-6_9b",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.1,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 8,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "dense_h_to_4h",
24
+ "query_key_value",
25
+ "dense",
26
+ "dense_4h_to_h"
27
+ ],
28
+ "task_type": "CAUSAL_LM",
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-490/trainer_state.json ADDED
@@ -0,0 +1,768 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 2.535032033920288,
3
+ "best_model_checkpoint": "./output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-150",
4
+ "epoch": 6.533333333333333,
5
+ "eval_steps": 10,
6
+ "global_step": 490,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.13333333333333333,
13
+ "grad_norm": 0.36938729882240295,
14
+ "learning_rate": 7.881481481481482e-05,
15
+ "loss": 2.519,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.13333333333333333,
20
+ "eval_loss": 2.579638957977295,
21
+ "eval_runtime": 43.8215,
22
+ "eval_samples_per_second": 22.82,
23
+ "eval_steps_per_second": 2.852,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.26666666666666666,
28
+ "grad_norm": 0.39850670099258423,
29
+ "learning_rate": 7.762962962962963e-05,
30
+ "loss": 2.5224,
31
+ "step": 20
32
+ },
33
+ {
34
+ "epoch": 0.26666666666666666,
35
+ "eval_loss": 2.5729691982269287,
36
+ "eval_runtime": 43.8179,
37
+ "eval_samples_per_second": 22.822,
38
+ "eval_steps_per_second": 2.853,
39
+ "step": 20
40
+ },
41
+ {
42
+ "epoch": 0.4,
43
+ "grad_norm": 0.40211933851242065,
44
+ "learning_rate": 7.644444444444445e-05,
45
+ "loss": 2.5169,
46
+ "step": 30
47
+ },
48
+ {
49
+ "epoch": 0.4,
50
+ "eval_loss": 2.567735433578491,
51
+ "eval_runtime": 43.8366,
52
+ "eval_samples_per_second": 22.812,
53
+ "eval_steps_per_second": 2.851,
54
+ "step": 30
55
+ },
56
+ {
57
+ "epoch": 0.5333333333333333,
58
+ "grad_norm": 0.6892333030700684,
59
+ "learning_rate": 7.525925925925926e-05,
60
+ "loss": 2.5784,
61
+ "step": 40
62
+ },
63
+ {
64
+ "epoch": 0.5333333333333333,
65
+ "eval_loss": 2.562650442123413,
66
+ "eval_runtime": 43.8377,
67
+ "eval_samples_per_second": 22.811,
68
+ "eval_steps_per_second": 2.851,
69
+ "step": 40
70
+ },
71
+ {
72
+ "epoch": 0.6666666666666666,
73
+ "grad_norm": 0.442343533039093,
74
+ "learning_rate": 7.407407407407409e-05,
75
+ "loss": 2.5431,
76
+ "step": 50
77
+ },
78
+ {
79
+ "epoch": 0.6666666666666666,
80
+ "eval_loss": 2.556513786315918,
81
+ "eval_runtime": 43.8656,
82
+ "eval_samples_per_second": 22.797,
83
+ "eval_steps_per_second": 2.85,
84
+ "step": 50
85
+ },
86
+ {
87
+ "epoch": 0.8,
88
+ "grad_norm": 0.4059845805168152,
89
+ "learning_rate": 7.28888888888889e-05,
90
+ "loss": 2.4936,
91
+ "step": 60
92
+ },
93
+ {
94
+ "epoch": 0.8,
95
+ "eval_loss": 2.552133798599243,
96
+ "eval_runtime": 43.8403,
97
+ "eval_samples_per_second": 22.81,
98
+ "eval_steps_per_second": 2.851,
99
+ "step": 60
100
+ },
101
+ {
102
+ "epoch": 0.9333333333333333,
103
+ "grad_norm": 0.48126307129859924,
104
+ "learning_rate": 7.170370370370371e-05,
105
+ "loss": 2.4901,
106
+ "step": 70
107
+ },
108
+ {
109
+ "epoch": 0.9333333333333333,
110
+ "eval_loss": 2.5477023124694824,
111
+ "eval_runtime": 43.8351,
112
+ "eval_samples_per_second": 22.813,
113
+ "eval_steps_per_second": 2.852,
114
+ "step": 70
115
+ },
116
+ {
117
+ "epoch": 1.0666666666666667,
118
+ "grad_norm": 0.48629865050315857,
119
+ "learning_rate": 7.051851851851853e-05,
120
+ "loss": 2.5114,
121
+ "step": 80
122
+ },
123
+ {
124
+ "epoch": 1.0666666666666667,
125
+ "eval_loss": 2.543431043624878,
126
+ "eval_runtime": 43.8432,
127
+ "eval_samples_per_second": 22.809,
128
+ "eval_steps_per_second": 2.851,
129
+ "step": 80
130
+ },
131
+ {
132
+ "epoch": 1.2,
133
+ "grad_norm": 0.5880796313285828,
134
+ "learning_rate": 6.933333333333334e-05,
135
+ "loss": 2.4446,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 1.2,
140
+ "eval_loss": 2.544339418411255,
141
+ "eval_runtime": 43.8437,
142
+ "eval_samples_per_second": 22.808,
143
+ "eval_steps_per_second": 2.851,
144
+ "step": 90
145
+ },
146
+ {
147
+ "epoch": 1.3333333333333333,
148
+ "grad_norm": 0.6746829748153687,
149
+ "learning_rate": 6.814814814814815e-05,
150
+ "loss": 2.4477,
151
+ "step": 100
152
+ },
153
+ {
154
+ "epoch": 1.3333333333333333,
155
+ "eval_loss": 2.544358968734741,
156
+ "eval_runtime": 43.8613,
157
+ "eval_samples_per_second": 22.799,
158
+ "eval_steps_per_second": 2.85,
159
+ "step": 100
160
+ },
161
+ {
162
+ "epoch": 1.4666666666666668,
163
+ "grad_norm": 0.8208937048912048,
164
+ "learning_rate": 6.696296296296296e-05,
165
+ "loss": 2.4004,
166
+ "step": 110
167
+ },
168
+ {
169
+ "epoch": 1.4666666666666668,
170
+ "eval_loss": 2.54068660736084,
171
+ "eval_runtime": 43.8426,
172
+ "eval_samples_per_second": 22.809,
173
+ "eval_steps_per_second": 2.851,
174
+ "step": 110
175
+ },
176
+ {
177
+ "epoch": 1.6,
178
+ "grad_norm": 0.925931453704834,
179
+ "learning_rate": 6.577777777777777e-05,
180
+ "loss": 2.3889,
181
+ "step": 120
182
+ },
183
+ {
184
+ "epoch": 1.6,
185
+ "eval_loss": 2.5393033027648926,
186
+ "eval_runtime": 43.8383,
187
+ "eval_samples_per_second": 22.811,
188
+ "eval_steps_per_second": 2.851,
189
+ "step": 120
190
+ },
191
+ {
192
+ "epoch": 1.7333333333333334,
193
+ "grad_norm": 0.8785662055015564,
194
+ "learning_rate": 6.45925925925926e-05,
195
+ "loss": 2.3959,
196
+ "step": 130
197
+ },
198
+ {
199
+ "epoch": 1.7333333333333334,
200
+ "eval_loss": 2.5367038249969482,
201
+ "eval_runtime": 43.8508,
202
+ "eval_samples_per_second": 22.805,
203
+ "eval_steps_per_second": 2.851,
204
+ "step": 130
205
+ },
206
+ {
207
+ "epoch": 1.8666666666666667,
208
+ "grad_norm": 0.941368818283081,
209
+ "learning_rate": 6.340740740740741e-05,
210
+ "loss": 2.3924,
211
+ "step": 140
212
+ },
213
+ {
214
+ "epoch": 1.8666666666666667,
215
+ "eval_loss": 2.535139560699463,
216
+ "eval_runtime": 43.8588,
217
+ "eval_samples_per_second": 22.8,
218
+ "eval_steps_per_second": 2.85,
219
+ "step": 140
220
+ },
221
+ {
222
+ "epoch": 2.0,
223
+ "grad_norm": 0.9578835368156433,
224
+ "learning_rate": 6.222222222222223e-05,
225
+ "loss": 2.4278,
226
+ "step": 150
227
+ },
228
+ {
229
+ "epoch": 2.0,
230
+ "eval_loss": 2.535032033920288,
231
+ "eval_runtime": 43.8484,
232
+ "eval_samples_per_second": 22.806,
233
+ "eval_steps_per_second": 2.851,
234
+ "step": 150
235
+ },
236
+ {
237
+ "epoch": 2.1333333333333333,
238
+ "grad_norm": 1.1541856527328491,
239
+ "learning_rate": 6.103703703703704e-05,
240
+ "loss": 2.2895,
241
+ "step": 160
242
+ },
243
+ {
244
+ "epoch": 2.1333333333333333,
245
+ "eval_loss": 2.564768075942993,
246
+ "eval_runtime": 43.8568,
247
+ "eval_samples_per_second": 22.801,
248
+ "eval_steps_per_second": 2.85,
249
+ "step": 160
250
+ },
251
+ {
252
+ "epoch": 2.2666666666666666,
253
+ "grad_norm": 1.4076604843139648,
254
+ "learning_rate": 5.9851851851851855e-05,
255
+ "loss": 2.2107,
256
+ "step": 170
257
+ },
258
+ {
259
+ "epoch": 2.2666666666666666,
260
+ "eval_loss": 2.5832314491271973,
261
+ "eval_runtime": 43.8455,
262
+ "eval_samples_per_second": 22.807,
263
+ "eval_steps_per_second": 2.851,
264
+ "step": 170
265
+ },
266
+ {
267
+ "epoch": 2.4,
268
+ "grad_norm": 1.4847813844680786,
269
+ "learning_rate": 5.8666666666666665e-05,
270
+ "loss": 2.2588,
271
+ "step": 180
272
+ },
273
+ {
274
+ "epoch": 2.4,
275
+ "eval_loss": 2.5781586170196533,
276
+ "eval_runtime": 43.8578,
277
+ "eval_samples_per_second": 22.801,
278
+ "eval_steps_per_second": 2.85,
279
+ "step": 180
280
+ },
281
+ {
282
+ "epoch": 2.533333333333333,
283
+ "grad_norm": 1.5135377645492554,
284
+ "learning_rate": 5.748148148148149e-05,
285
+ "loss": 2.2099,
286
+ "step": 190
287
+ },
288
+ {
289
+ "epoch": 2.533333333333333,
290
+ "eval_loss": 2.5752007961273193,
291
+ "eval_runtime": 43.8521,
292
+ "eval_samples_per_second": 22.804,
293
+ "eval_steps_per_second": 2.85,
294
+ "step": 190
295
+ },
296
+ {
297
+ "epoch": 2.6666666666666665,
298
+ "grad_norm": 1.5297592878341675,
299
+ "learning_rate": 5.62962962962963e-05,
300
+ "loss": 2.2965,
301
+ "step": 200
302
+ },
303
+ {
304
+ "epoch": 2.6666666666666665,
305
+ "eval_loss": 2.579918622970581,
306
+ "eval_runtime": 43.8661,
307
+ "eval_samples_per_second": 22.797,
308
+ "eval_steps_per_second": 2.85,
309
+ "step": 200
310
+ },
311
+ {
312
+ "epoch": 2.8,
313
+ "grad_norm": 1.6282892227172852,
314
+ "learning_rate": 5.511111111111112e-05,
315
+ "loss": 2.2487,
316
+ "step": 210
317
+ },
318
+ {
319
+ "epoch": 2.8,
320
+ "eval_loss": 2.5760037899017334,
321
+ "eval_runtime": 43.8379,
322
+ "eval_samples_per_second": 22.811,
323
+ "eval_steps_per_second": 2.851,
324
+ "step": 210
325
+ },
326
+ {
327
+ "epoch": 2.9333333333333336,
328
+ "grad_norm": 1.74424409866333,
329
+ "learning_rate": 5.392592592592593e-05,
330
+ "loss": 2.2049,
331
+ "step": 220
332
+ },
333
+ {
334
+ "epoch": 2.9333333333333336,
335
+ "eval_loss": 2.576190233230591,
336
+ "eval_runtime": 43.8491,
337
+ "eval_samples_per_second": 22.805,
338
+ "eval_steps_per_second": 2.851,
339
+ "step": 220
340
+ },
341
+ {
342
+ "epoch": 3.066666666666667,
343
+ "grad_norm": 1.654069423675537,
344
+ "learning_rate": 5.274074074074074e-05,
345
+ "loss": 2.1188,
346
+ "step": 230
347
+ },
348
+ {
349
+ "epoch": 3.066666666666667,
350
+ "eval_loss": 2.5971405506134033,
351
+ "eval_runtime": 43.855,
352
+ "eval_samples_per_second": 22.802,
353
+ "eval_steps_per_second": 2.85,
354
+ "step": 230
355
+ },
356
+ {
357
+ "epoch": 3.2,
358
+ "grad_norm": 2.541767120361328,
359
+ "learning_rate": 5.155555555555556e-05,
360
+ "loss": 2.0788,
361
+ "step": 240
362
+ },
363
+ {
364
+ "epoch": 3.2,
365
+ "eval_loss": 2.6767666339874268,
366
+ "eval_runtime": 43.8368,
367
+ "eval_samples_per_second": 22.812,
368
+ "eval_steps_per_second": 2.851,
369
+ "step": 240
370
+ },
371
+ {
372
+ "epoch": 3.3333333333333335,
373
+ "grad_norm": 2.0508077144622803,
374
+ "learning_rate": 5.037037037037037e-05,
375
+ "loss": 2.0784,
376
+ "step": 250
377
+ },
378
+ {
379
+ "epoch": 3.3333333333333335,
380
+ "eval_loss": 2.6486454010009766,
381
+ "eval_runtime": 43.8529,
382
+ "eval_samples_per_second": 22.803,
383
+ "eval_steps_per_second": 2.85,
384
+ "step": 250
385
+ },
386
+ {
387
+ "epoch": 3.466666666666667,
388
+ "grad_norm": 2.1096036434173584,
389
+ "learning_rate": 4.918518518518519e-05,
390
+ "loss": 2.0633,
391
+ "step": 260
392
+ },
393
+ {
394
+ "epoch": 3.466666666666667,
395
+ "eval_loss": 2.6501405239105225,
396
+ "eval_runtime": 43.8632,
397
+ "eval_samples_per_second": 22.798,
398
+ "eval_steps_per_second": 2.85,
399
+ "step": 260
400
+ },
401
+ {
402
+ "epoch": 3.6,
403
+ "grad_norm": 2.3028736114501953,
404
+ "learning_rate": 4.8e-05,
405
+ "loss": 2.0722,
406
+ "step": 270
407
+ },
408
+ {
409
+ "epoch": 3.6,
410
+ "eval_loss": 2.657053232192993,
411
+ "eval_runtime": 43.8423,
412
+ "eval_samples_per_second": 22.809,
413
+ "eval_steps_per_second": 2.851,
414
+ "step": 270
415
+ },
416
+ {
417
+ "epoch": 3.7333333333333334,
418
+ "grad_norm": 2.1536757946014404,
419
+ "learning_rate": 4.681481481481481e-05,
420
+ "loss": 2.0155,
421
+ "step": 280
422
+ },
423
+ {
424
+ "epoch": 3.7333333333333334,
425
+ "eval_loss": 2.648275375366211,
426
+ "eval_runtime": 43.8328,
427
+ "eval_samples_per_second": 22.814,
428
+ "eval_steps_per_second": 2.852,
429
+ "step": 280
430
+ },
431
+ {
432
+ "epoch": 3.8666666666666667,
433
+ "grad_norm": 2.4079270362854004,
434
+ "learning_rate": 4.5629629629629636e-05,
435
+ "loss": 2.1111,
436
+ "step": 290
437
+ },
438
+ {
439
+ "epoch": 3.8666666666666667,
440
+ "eval_loss": 2.650322675704956,
441
+ "eval_runtime": 43.835,
442
+ "eval_samples_per_second": 22.813,
443
+ "eval_steps_per_second": 2.852,
444
+ "step": 290
445
+ },
446
+ {
447
+ "epoch": 4.0,
448
+ "grad_norm": 2.426234722137451,
449
+ "learning_rate": 4.444444444444445e-05,
450
+ "loss": 2.041,
451
+ "step": 300
452
+ },
453
+ {
454
+ "epoch": 4.0,
455
+ "eval_loss": 2.6490862369537354,
456
+ "eval_runtime": 43.845,
457
+ "eval_samples_per_second": 22.808,
458
+ "eval_steps_per_second": 2.851,
459
+ "step": 300
460
+ },
461
+ {
462
+ "epoch": 4.133333333333334,
463
+ "grad_norm": 2.8063745498657227,
464
+ "learning_rate": 4.3259259259259264e-05,
465
+ "loss": 1.9316,
466
+ "step": 310
467
+ },
468
+ {
469
+ "epoch": 4.133333333333334,
470
+ "eval_loss": 2.7609620094299316,
471
+ "eval_runtime": 43.8481,
472
+ "eval_samples_per_second": 22.806,
473
+ "eval_steps_per_second": 2.851,
474
+ "step": 310
475
+ },
476
+ {
477
+ "epoch": 4.266666666666667,
478
+ "grad_norm": 2.96854305267334,
479
+ "learning_rate": 4.2074074074074075e-05,
480
+ "loss": 1.8889,
481
+ "step": 320
482
+ },
483
+ {
484
+ "epoch": 4.266666666666667,
485
+ "eval_loss": 2.736968994140625,
486
+ "eval_runtime": 43.8633,
487
+ "eval_samples_per_second": 22.798,
488
+ "eval_steps_per_second": 2.85,
489
+ "step": 320
490
+ },
491
+ {
492
+ "epoch": 4.4,
493
+ "grad_norm": 2.637695789337158,
494
+ "learning_rate": 4.088888888888889e-05,
495
+ "loss": 1.9187,
496
+ "step": 330
497
+ },
498
+ {
499
+ "epoch": 4.4,
500
+ "eval_loss": 2.7382876873016357,
501
+ "eval_runtime": 43.8486,
502
+ "eval_samples_per_second": 22.806,
503
+ "eval_steps_per_second": 2.851,
504
+ "step": 330
505
+ },
506
+ {
507
+ "epoch": 4.533333333333333,
508
+ "grad_norm": 2.9106290340423584,
509
+ "learning_rate": 3.970370370370371e-05,
510
+ "loss": 1.9002,
511
+ "step": 340
512
+ },
513
+ {
514
+ "epoch": 4.533333333333333,
515
+ "eval_loss": 2.734544515609741,
516
+ "eval_runtime": 43.8491,
517
+ "eval_samples_per_second": 22.805,
518
+ "eval_steps_per_second": 2.851,
519
+ "step": 340
520
+ },
521
+ {
522
+ "epoch": 4.666666666666667,
523
+ "grad_norm": 2.769315481185913,
524
+ "learning_rate": 3.851851851851852e-05,
525
+ "loss": 1.9251,
526
+ "step": 350
527
+ },
528
+ {
529
+ "epoch": 4.666666666666667,
530
+ "eval_loss": 2.734708070755005,
531
+ "eval_runtime": 43.8534,
532
+ "eval_samples_per_second": 22.803,
533
+ "eval_steps_per_second": 2.85,
534
+ "step": 350
535
+ },
536
+ {
537
+ "epoch": 4.8,
538
+ "grad_norm": 2.940281867980957,
539
+ "learning_rate": 3.733333333333334e-05,
540
+ "loss": 1.9319,
541
+ "step": 360
542
+ },
543
+ {
544
+ "epoch": 4.8,
545
+ "eval_loss": 2.7300503253936768,
546
+ "eval_runtime": 43.9017,
547
+ "eval_samples_per_second": 22.778,
548
+ "eval_steps_per_second": 2.847,
549
+ "step": 360
550
+ },
551
+ {
552
+ "epoch": 4.933333333333334,
553
+ "grad_norm": 2.8305609226226807,
554
+ "learning_rate": 3.614814814814815e-05,
555
+ "loss": 1.9332,
556
+ "step": 370
557
+ },
558
+ {
559
+ "epoch": 4.933333333333334,
560
+ "eval_loss": 2.7309281826019287,
561
+ "eval_runtime": 43.8842,
562
+ "eval_samples_per_second": 22.787,
563
+ "eval_steps_per_second": 2.848,
564
+ "step": 370
565
+ },
566
+ {
567
+ "epoch": 5.066666666666666,
568
+ "grad_norm": 2.8739213943481445,
569
+ "learning_rate": 3.4962962962962965e-05,
570
+ "loss": 1.8846,
571
+ "step": 380
572
+ },
573
+ {
574
+ "epoch": 5.066666666666666,
575
+ "eval_loss": 2.76513671875,
576
+ "eval_runtime": 43.906,
577
+ "eval_samples_per_second": 22.776,
578
+ "eval_steps_per_second": 2.847,
579
+ "step": 380
580
+ },
581
+ {
582
+ "epoch": 5.2,
583
+ "grad_norm": 3.9025838375091553,
584
+ "learning_rate": 3.377777777777778e-05,
585
+ "loss": 1.7575,
586
+ "step": 390
587
+ },
588
+ {
589
+ "epoch": 5.2,
590
+ "eval_loss": 2.847782611846924,
591
+ "eval_runtime": 43.8665,
592
+ "eval_samples_per_second": 22.796,
593
+ "eval_steps_per_second": 2.85,
594
+ "step": 390
595
+ },
596
+ {
597
+ "epoch": 5.333333333333333,
598
+ "grad_norm": 3.299649715423584,
599
+ "learning_rate": 3.259259259259259e-05,
600
+ "loss": 1.7713,
601
+ "step": 400
602
+ },
603
+ {
604
+ "epoch": 5.333333333333333,
605
+ "eval_loss": 2.8094286918640137,
606
+ "eval_runtime": 43.8629,
607
+ "eval_samples_per_second": 22.798,
608
+ "eval_steps_per_second": 2.85,
609
+ "step": 400
610
+ },
611
+ {
612
+ "epoch": 5.466666666666667,
613
+ "grad_norm": 3.4474265575408936,
614
+ "learning_rate": 3.140740740740741e-05,
615
+ "loss": 1.7983,
616
+ "step": 410
617
+ },
618
+ {
619
+ "epoch": 5.466666666666667,
620
+ "eval_loss": 2.827517509460449,
621
+ "eval_runtime": 43.8611,
622
+ "eval_samples_per_second": 22.799,
623
+ "eval_steps_per_second": 2.85,
624
+ "step": 410
625
+ },
626
+ {
627
+ "epoch": 5.6,
628
+ "grad_norm": 3.1924540996551514,
629
+ "learning_rate": 3.0222222222222225e-05,
630
+ "loss": 1.8091,
631
+ "step": 420
632
+ },
633
+ {
634
+ "epoch": 5.6,
635
+ "eval_loss": 2.81618332862854,
636
+ "eval_runtime": 43.8544,
637
+ "eval_samples_per_second": 22.803,
638
+ "eval_steps_per_second": 2.85,
639
+ "step": 420
640
+ },
641
+ {
642
+ "epoch": 5.733333333333333,
643
+ "grad_norm": 3.5224015712738037,
644
+ "learning_rate": 2.9037037037037042e-05,
645
+ "loss": 1.8253,
646
+ "step": 430
647
+ },
648
+ {
649
+ "epoch": 5.733333333333333,
650
+ "eval_loss": 2.816711187362671,
651
+ "eval_runtime": 43.8685,
652
+ "eval_samples_per_second": 22.795,
653
+ "eval_steps_per_second": 2.849,
654
+ "step": 430
655
+ },
656
+ {
657
+ "epoch": 5.866666666666667,
658
+ "grad_norm": 3.60918927192688,
659
+ "learning_rate": 2.7851851851851856e-05,
660
+ "loss": 1.8013,
661
+ "step": 440
662
+ },
663
+ {
664
+ "epoch": 5.866666666666667,
665
+ "eval_loss": 2.8146169185638428,
666
+ "eval_runtime": 43.8516,
667
+ "eval_samples_per_second": 22.804,
668
+ "eval_steps_per_second": 2.851,
669
+ "step": 440
670
+ },
671
+ {
672
+ "epoch": 6.0,
673
+ "grad_norm": 3.5798070430755615,
674
+ "learning_rate": 2.6666666666666667e-05,
675
+ "loss": 1.8258,
676
+ "step": 450
677
+ },
678
+ {
679
+ "epoch": 6.0,
680
+ "eval_loss": 2.8134233951568604,
681
+ "eval_runtime": 43.8442,
682
+ "eval_samples_per_second": 22.808,
683
+ "eval_steps_per_second": 2.851,
684
+ "step": 450
685
+ },
686
+ {
687
+ "epoch": 6.133333333333334,
688
+ "grad_norm": 5.563477993011475,
689
+ "learning_rate": 2.5481481481481484e-05,
690
+ "loss": 1.6649,
691
+ "step": 460
692
+ },
693
+ {
694
+ "epoch": 6.133333333333334,
695
+ "eval_loss": 2.9189789295196533,
696
+ "eval_runtime": 43.8602,
697
+ "eval_samples_per_second": 22.8,
698
+ "eval_steps_per_second": 2.85,
699
+ "step": 460
700
+ },
701
+ {
702
+ "epoch": 6.266666666666667,
703
+ "grad_norm": 4.192393779754639,
704
+ "learning_rate": 2.4296296296296298e-05,
705
+ "loss": 1.7443,
706
+ "step": 470
707
+ },
708
+ {
709
+ "epoch": 6.266666666666667,
710
+ "eval_loss": 2.893780469894409,
711
+ "eval_runtime": 43.8434,
712
+ "eval_samples_per_second": 22.808,
713
+ "eval_steps_per_second": 2.851,
714
+ "step": 470
715
+ },
716
+ {
717
+ "epoch": 6.4,
718
+ "grad_norm": 4.8650593757629395,
719
+ "learning_rate": 2.3111111111111112e-05,
720
+ "loss": 1.6961,
721
+ "step": 480
722
+ },
723
+ {
724
+ "epoch": 6.4,
725
+ "eval_loss": 2.8861398696899414,
726
+ "eval_runtime": 43.8417,
727
+ "eval_samples_per_second": 22.809,
728
+ "eval_steps_per_second": 2.851,
729
+ "step": 480
730
+ },
731
+ {
732
+ "epoch": 6.533333333333333,
733
+ "grad_norm": 3.844482660293579,
734
+ "learning_rate": 2.192592592592593e-05,
735
+ "loss": 1.6868,
736
+ "step": 490
737
+ },
738
+ {
739
+ "epoch": 6.533333333333333,
740
+ "eval_loss": 2.900317907333374,
741
+ "eval_runtime": 43.8557,
742
+ "eval_samples_per_second": 22.802,
743
+ "eval_steps_per_second": 2.85,
744
+ "step": 490
745
+ }
746
+ ],
747
+ "logging_steps": 10,
748
+ "max_steps": 675,
749
+ "num_input_tokens_seen": 0,
750
+ "num_train_epochs": 9,
751
+ "save_steps": 10,
752
+ "stateful_callbacks": {
753
+ "TrainerControl": {
754
+ "args": {
755
+ "should_epoch_stop": false,
756
+ "should_evaluate": false,
757
+ "should_log": false,
758
+ "should_save": true,
759
+ "should_training_stop": false
760
+ },
761
+ "attributes": {}
762
+ }
763
+ },
764
+ "total_flos": 8.02917527322624e+16,
765
+ "train_batch_size": 8,
766
+ "trial_name": null,
767
+ "trial_params": null
768
+ }
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-500/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/pythia-6_9b
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-500/adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/workspace/pythia-6_9b",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.1,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 8,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "dense_h_to_4h",
24
+ "query_key_value",
25
+ "dense",
26
+ "dense_4h_to_h"
27
+ ],
28
+ "task_type": "CAUSAL_LM",
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-500/trainer_state.json ADDED
@@ -0,0 +1,783 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 2.535032033920288,
3
+ "best_model_checkpoint": "./output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-150",
4
+ "epoch": 6.666666666666667,
5
+ "eval_steps": 10,
6
+ "global_step": 500,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.13333333333333333,
13
+ "grad_norm": 0.36938729882240295,
14
+ "learning_rate": 7.881481481481482e-05,
15
+ "loss": 2.519,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.13333333333333333,
20
+ "eval_loss": 2.579638957977295,
21
+ "eval_runtime": 43.8215,
22
+ "eval_samples_per_second": 22.82,
23
+ "eval_steps_per_second": 2.852,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.26666666666666666,
28
+ "grad_norm": 0.39850670099258423,
29
+ "learning_rate": 7.762962962962963e-05,
30
+ "loss": 2.5224,
31
+ "step": 20
32
+ },
33
+ {
34
+ "epoch": 0.26666666666666666,
35
+ "eval_loss": 2.5729691982269287,
36
+ "eval_runtime": 43.8179,
37
+ "eval_samples_per_second": 22.822,
38
+ "eval_steps_per_second": 2.853,
39
+ "step": 20
40
+ },
41
+ {
42
+ "epoch": 0.4,
43
+ "grad_norm": 0.40211933851242065,
44
+ "learning_rate": 7.644444444444445e-05,
45
+ "loss": 2.5169,
46
+ "step": 30
47
+ },
48
+ {
49
+ "epoch": 0.4,
50
+ "eval_loss": 2.567735433578491,
51
+ "eval_runtime": 43.8366,
52
+ "eval_samples_per_second": 22.812,
53
+ "eval_steps_per_second": 2.851,
54
+ "step": 30
55
+ },
56
+ {
57
+ "epoch": 0.5333333333333333,
58
+ "grad_norm": 0.6892333030700684,
59
+ "learning_rate": 7.525925925925926e-05,
60
+ "loss": 2.5784,
61
+ "step": 40
62
+ },
63
+ {
64
+ "epoch": 0.5333333333333333,
65
+ "eval_loss": 2.562650442123413,
66
+ "eval_runtime": 43.8377,
67
+ "eval_samples_per_second": 22.811,
68
+ "eval_steps_per_second": 2.851,
69
+ "step": 40
70
+ },
71
+ {
72
+ "epoch": 0.6666666666666666,
73
+ "grad_norm": 0.442343533039093,
74
+ "learning_rate": 7.407407407407409e-05,
75
+ "loss": 2.5431,
76
+ "step": 50
77
+ },
78
+ {
79
+ "epoch": 0.6666666666666666,
80
+ "eval_loss": 2.556513786315918,
81
+ "eval_runtime": 43.8656,
82
+ "eval_samples_per_second": 22.797,
83
+ "eval_steps_per_second": 2.85,
84
+ "step": 50
85
+ },
86
+ {
87
+ "epoch": 0.8,
88
+ "grad_norm": 0.4059845805168152,
89
+ "learning_rate": 7.28888888888889e-05,
90
+ "loss": 2.4936,
91
+ "step": 60
92
+ },
93
+ {
94
+ "epoch": 0.8,
95
+ "eval_loss": 2.552133798599243,
96
+ "eval_runtime": 43.8403,
97
+ "eval_samples_per_second": 22.81,
98
+ "eval_steps_per_second": 2.851,
99
+ "step": 60
100
+ },
101
+ {
102
+ "epoch": 0.9333333333333333,
103
+ "grad_norm": 0.48126307129859924,
104
+ "learning_rate": 7.170370370370371e-05,
105
+ "loss": 2.4901,
106
+ "step": 70
107
+ },
108
+ {
109
+ "epoch": 0.9333333333333333,
110
+ "eval_loss": 2.5477023124694824,
111
+ "eval_runtime": 43.8351,
112
+ "eval_samples_per_second": 22.813,
113
+ "eval_steps_per_second": 2.852,
114
+ "step": 70
115
+ },
116
+ {
117
+ "epoch": 1.0666666666666667,
118
+ "grad_norm": 0.48629865050315857,
119
+ "learning_rate": 7.051851851851853e-05,
120
+ "loss": 2.5114,
121
+ "step": 80
122
+ },
123
+ {
124
+ "epoch": 1.0666666666666667,
125
+ "eval_loss": 2.543431043624878,
126
+ "eval_runtime": 43.8432,
127
+ "eval_samples_per_second": 22.809,
128
+ "eval_steps_per_second": 2.851,
129
+ "step": 80
130
+ },
131
+ {
132
+ "epoch": 1.2,
133
+ "grad_norm": 0.5880796313285828,
134
+ "learning_rate": 6.933333333333334e-05,
135
+ "loss": 2.4446,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 1.2,
140
+ "eval_loss": 2.544339418411255,
141
+ "eval_runtime": 43.8437,
142
+ "eval_samples_per_second": 22.808,
143
+ "eval_steps_per_second": 2.851,
144
+ "step": 90
145
+ },
146
+ {
147
+ "epoch": 1.3333333333333333,
148
+ "grad_norm": 0.6746829748153687,
149
+ "learning_rate": 6.814814814814815e-05,
150
+ "loss": 2.4477,
151
+ "step": 100
152
+ },
153
+ {
154
+ "epoch": 1.3333333333333333,
155
+ "eval_loss": 2.544358968734741,
156
+ "eval_runtime": 43.8613,
157
+ "eval_samples_per_second": 22.799,
158
+ "eval_steps_per_second": 2.85,
159
+ "step": 100
160
+ },
161
+ {
162
+ "epoch": 1.4666666666666668,
163
+ "grad_norm": 0.8208937048912048,
164
+ "learning_rate": 6.696296296296296e-05,
165
+ "loss": 2.4004,
166
+ "step": 110
167
+ },
168
+ {
169
+ "epoch": 1.4666666666666668,
170
+ "eval_loss": 2.54068660736084,
171
+ "eval_runtime": 43.8426,
172
+ "eval_samples_per_second": 22.809,
173
+ "eval_steps_per_second": 2.851,
174
+ "step": 110
175
+ },
176
+ {
177
+ "epoch": 1.6,
178
+ "grad_norm": 0.925931453704834,
179
+ "learning_rate": 6.577777777777777e-05,
180
+ "loss": 2.3889,
181
+ "step": 120
182
+ },
183
+ {
184
+ "epoch": 1.6,
185
+ "eval_loss": 2.5393033027648926,
186
+ "eval_runtime": 43.8383,
187
+ "eval_samples_per_second": 22.811,
188
+ "eval_steps_per_second": 2.851,
189
+ "step": 120
190
+ },
191
+ {
192
+ "epoch": 1.7333333333333334,
193
+ "grad_norm": 0.8785662055015564,
194
+ "learning_rate": 6.45925925925926e-05,
195
+ "loss": 2.3959,
196
+ "step": 130
197
+ },
198
+ {
199
+ "epoch": 1.7333333333333334,
200
+ "eval_loss": 2.5367038249969482,
201
+ "eval_runtime": 43.8508,
202
+ "eval_samples_per_second": 22.805,
203
+ "eval_steps_per_second": 2.851,
204
+ "step": 130
205
+ },
206
+ {
207
+ "epoch": 1.8666666666666667,
208
+ "grad_norm": 0.941368818283081,
209
+ "learning_rate": 6.340740740740741e-05,
210
+ "loss": 2.3924,
211
+ "step": 140
212
+ },
213
+ {
214
+ "epoch": 1.8666666666666667,
215
+ "eval_loss": 2.535139560699463,
216
+ "eval_runtime": 43.8588,
217
+ "eval_samples_per_second": 22.8,
218
+ "eval_steps_per_second": 2.85,
219
+ "step": 140
220
+ },
221
+ {
222
+ "epoch": 2.0,
223
+ "grad_norm": 0.9578835368156433,
224
+ "learning_rate": 6.222222222222223e-05,
225
+ "loss": 2.4278,
226
+ "step": 150
227
+ },
228
+ {
229
+ "epoch": 2.0,
230
+ "eval_loss": 2.535032033920288,
231
+ "eval_runtime": 43.8484,
232
+ "eval_samples_per_second": 22.806,
233
+ "eval_steps_per_second": 2.851,
234
+ "step": 150
235
+ },
236
+ {
237
+ "epoch": 2.1333333333333333,
238
+ "grad_norm": 1.1541856527328491,
239
+ "learning_rate": 6.103703703703704e-05,
240
+ "loss": 2.2895,
241
+ "step": 160
242
+ },
243
+ {
244
+ "epoch": 2.1333333333333333,
245
+ "eval_loss": 2.564768075942993,
246
+ "eval_runtime": 43.8568,
247
+ "eval_samples_per_second": 22.801,
248
+ "eval_steps_per_second": 2.85,
249
+ "step": 160
250
+ },
251
+ {
252
+ "epoch": 2.2666666666666666,
253
+ "grad_norm": 1.4076604843139648,
254
+ "learning_rate": 5.9851851851851855e-05,
255
+ "loss": 2.2107,
256
+ "step": 170
257
+ },
258
+ {
259
+ "epoch": 2.2666666666666666,
260
+ "eval_loss": 2.5832314491271973,
261
+ "eval_runtime": 43.8455,
262
+ "eval_samples_per_second": 22.807,
263
+ "eval_steps_per_second": 2.851,
264
+ "step": 170
265
+ },
266
+ {
267
+ "epoch": 2.4,
268
+ "grad_norm": 1.4847813844680786,
269
+ "learning_rate": 5.8666666666666665e-05,
270
+ "loss": 2.2588,
271
+ "step": 180
272
+ },
273
+ {
274
+ "epoch": 2.4,
275
+ "eval_loss": 2.5781586170196533,
276
+ "eval_runtime": 43.8578,
277
+ "eval_samples_per_second": 22.801,
278
+ "eval_steps_per_second": 2.85,
279
+ "step": 180
280
+ },
281
+ {
282
+ "epoch": 2.533333333333333,
283
+ "grad_norm": 1.5135377645492554,
284
+ "learning_rate": 5.748148148148149e-05,
285
+ "loss": 2.2099,
286
+ "step": 190
287
+ },
288
+ {
289
+ "epoch": 2.533333333333333,
290
+ "eval_loss": 2.5752007961273193,
291
+ "eval_runtime": 43.8521,
292
+ "eval_samples_per_second": 22.804,
293
+ "eval_steps_per_second": 2.85,
294
+ "step": 190
295
+ },
296
+ {
297
+ "epoch": 2.6666666666666665,
298
+ "grad_norm": 1.5297592878341675,
299
+ "learning_rate": 5.62962962962963e-05,
300
+ "loss": 2.2965,
301
+ "step": 200
302
+ },
303
+ {
304
+ "epoch": 2.6666666666666665,
305
+ "eval_loss": 2.579918622970581,
306
+ "eval_runtime": 43.8661,
307
+ "eval_samples_per_second": 22.797,
308
+ "eval_steps_per_second": 2.85,
309
+ "step": 200
310
+ },
311
+ {
312
+ "epoch": 2.8,
313
+ "grad_norm": 1.6282892227172852,
314
+ "learning_rate": 5.511111111111112e-05,
315
+ "loss": 2.2487,
316
+ "step": 210
317
+ },
318
+ {
319
+ "epoch": 2.8,
320
+ "eval_loss": 2.5760037899017334,
321
+ "eval_runtime": 43.8379,
322
+ "eval_samples_per_second": 22.811,
323
+ "eval_steps_per_second": 2.851,
324
+ "step": 210
325
+ },
326
+ {
327
+ "epoch": 2.9333333333333336,
328
+ "grad_norm": 1.74424409866333,
329
+ "learning_rate": 5.392592592592593e-05,
330
+ "loss": 2.2049,
331
+ "step": 220
332
+ },
333
+ {
334
+ "epoch": 2.9333333333333336,
335
+ "eval_loss": 2.576190233230591,
336
+ "eval_runtime": 43.8491,
337
+ "eval_samples_per_second": 22.805,
338
+ "eval_steps_per_second": 2.851,
339
+ "step": 220
340
+ },
341
+ {
342
+ "epoch": 3.066666666666667,
343
+ "grad_norm": 1.654069423675537,
344
+ "learning_rate": 5.274074074074074e-05,
345
+ "loss": 2.1188,
346
+ "step": 230
347
+ },
348
+ {
349
+ "epoch": 3.066666666666667,
350
+ "eval_loss": 2.5971405506134033,
351
+ "eval_runtime": 43.855,
352
+ "eval_samples_per_second": 22.802,
353
+ "eval_steps_per_second": 2.85,
354
+ "step": 230
355
+ },
356
+ {
357
+ "epoch": 3.2,
358
+ "grad_norm": 2.541767120361328,
359
+ "learning_rate": 5.155555555555556e-05,
360
+ "loss": 2.0788,
361
+ "step": 240
362
+ },
363
+ {
364
+ "epoch": 3.2,
365
+ "eval_loss": 2.6767666339874268,
366
+ "eval_runtime": 43.8368,
367
+ "eval_samples_per_second": 22.812,
368
+ "eval_steps_per_second": 2.851,
369
+ "step": 240
370
+ },
371
+ {
372
+ "epoch": 3.3333333333333335,
373
+ "grad_norm": 2.0508077144622803,
374
+ "learning_rate": 5.037037037037037e-05,
375
+ "loss": 2.0784,
376
+ "step": 250
377
+ },
378
+ {
379
+ "epoch": 3.3333333333333335,
380
+ "eval_loss": 2.6486454010009766,
381
+ "eval_runtime": 43.8529,
382
+ "eval_samples_per_second": 22.803,
383
+ "eval_steps_per_second": 2.85,
384
+ "step": 250
385
+ },
386
+ {
387
+ "epoch": 3.466666666666667,
388
+ "grad_norm": 2.1096036434173584,
389
+ "learning_rate": 4.918518518518519e-05,
390
+ "loss": 2.0633,
391
+ "step": 260
392
+ },
393
+ {
394
+ "epoch": 3.466666666666667,
395
+ "eval_loss": 2.6501405239105225,
396
+ "eval_runtime": 43.8632,
397
+ "eval_samples_per_second": 22.798,
398
+ "eval_steps_per_second": 2.85,
399
+ "step": 260
400
+ },
401
+ {
402
+ "epoch": 3.6,
403
+ "grad_norm": 2.3028736114501953,
404
+ "learning_rate": 4.8e-05,
405
+ "loss": 2.0722,
406
+ "step": 270
407
+ },
408
+ {
409
+ "epoch": 3.6,
410
+ "eval_loss": 2.657053232192993,
411
+ "eval_runtime": 43.8423,
412
+ "eval_samples_per_second": 22.809,
413
+ "eval_steps_per_second": 2.851,
414
+ "step": 270
415
+ },
416
+ {
417
+ "epoch": 3.7333333333333334,
418
+ "grad_norm": 2.1536757946014404,
419
+ "learning_rate": 4.681481481481481e-05,
420
+ "loss": 2.0155,
421
+ "step": 280
422
+ },
423
+ {
424
+ "epoch": 3.7333333333333334,
425
+ "eval_loss": 2.648275375366211,
426
+ "eval_runtime": 43.8328,
427
+ "eval_samples_per_second": 22.814,
428
+ "eval_steps_per_second": 2.852,
429
+ "step": 280
430
+ },
431
+ {
432
+ "epoch": 3.8666666666666667,
433
+ "grad_norm": 2.4079270362854004,
434
+ "learning_rate": 4.5629629629629636e-05,
435
+ "loss": 2.1111,
436
+ "step": 290
437
+ },
438
+ {
439
+ "epoch": 3.8666666666666667,
440
+ "eval_loss": 2.650322675704956,
441
+ "eval_runtime": 43.835,
442
+ "eval_samples_per_second": 22.813,
443
+ "eval_steps_per_second": 2.852,
444
+ "step": 290
445
+ },
446
+ {
447
+ "epoch": 4.0,
448
+ "grad_norm": 2.426234722137451,
449
+ "learning_rate": 4.444444444444445e-05,
450
+ "loss": 2.041,
451
+ "step": 300
452
+ },
453
+ {
454
+ "epoch": 4.0,
455
+ "eval_loss": 2.6490862369537354,
456
+ "eval_runtime": 43.845,
457
+ "eval_samples_per_second": 22.808,
458
+ "eval_steps_per_second": 2.851,
459
+ "step": 300
460
+ },
461
+ {
462
+ "epoch": 4.133333333333334,
463
+ "grad_norm": 2.8063745498657227,
464
+ "learning_rate": 4.3259259259259264e-05,
465
+ "loss": 1.9316,
466
+ "step": 310
467
+ },
468
+ {
469
+ "epoch": 4.133333333333334,
470
+ "eval_loss": 2.7609620094299316,
471
+ "eval_runtime": 43.8481,
472
+ "eval_samples_per_second": 22.806,
473
+ "eval_steps_per_second": 2.851,
474
+ "step": 310
475
+ },
476
+ {
477
+ "epoch": 4.266666666666667,
478
+ "grad_norm": 2.96854305267334,
479
+ "learning_rate": 4.2074074074074075e-05,
480
+ "loss": 1.8889,
481
+ "step": 320
482
+ },
483
+ {
484
+ "epoch": 4.266666666666667,
485
+ "eval_loss": 2.736968994140625,
486
+ "eval_runtime": 43.8633,
487
+ "eval_samples_per_second": 22.798,
488
+ "eval_steps_per_second": 2.85,
489
+ "step": 320
490
+ },
491
+ {
492
+ "epoch": 4.4,
493
+ "grad_norm": 2.637695789337158,
494
+ "learning_rate": 4.088888888888889e-05,
495
+ "loss": 1.9187,
496
+ "step": 330
497
+ },
498
+ {
499
+ "epoch": 4.4,
500
+ "eval_loss": 2.7382876873016357,
501
+ "eval_runtime": 43.8486,
502
+ "eval_samples_per_second": 22.806,
503
+ "eval_steps_per_second": 2.851,
504
+ "step": 330
505
+ },
506
+ {
507
+ "epoch": 4.533333333333333,
508
+ "grad_norm": 2.9106290340423584,
509
+ "learning_rate": 3.970370370370371e-05,
510
+ "loss": 1.9002,
511
+ "step": 340
512
+ },
513
+ {
514
+ "epoch": 4.533333333333333,
515
+ "eval_loss": 2.734544515609741,
516
+ "eval_runtime": 43.8491,
517
+ "eval_samples_per_second": 22.805,
518
+ "eval_steps_per_second": 2.851,
519
+ "step": 340
520
+ },
521
+ {
522
+ "epoch": 4.666666666666667,
523
+ "grad_norm": 2.769315481185913,
524
+ "learning_rate": 3.851851851851852e-05,
525
+ "loss": 1.9251,
526
+ "step": 350
527
+ },
528
+ {
529
+ "epoch": 4.666666666666667,
530
+ "eval_loss": 2.734708070755005,
531
+ "eval_runtime": 43.8534,
532
+ "eval_samples_per_second": 22.803,
533
+ "eval_steps_per_second": 2.85,
534
+ "step": 350
535
+ },
536
+ {
537
+ "epoch": 4.8,
538
+ "grad_norm": 2.940281867980957,
539
+ "learning_rate": 3.733333333333334e-05,
540
+ "loss": 1.9319,
541
+ "step": 360
542
+ },
543
+ {
544
+ "epoch": 4.8,
545
+ "eval_loss": 2.7300503253936768,
546
+ "eval_runtime": 43.9017,
547
+ "eval_samples_per_second": 22.778,
548
+ "eval_steps_per_second": 2.847,
549
+ "step": 360
550
+ },
551
+ {
552
+ "epoch": 4.933333333333334,
553
+ "grad_norm": 2.8305609226226807,
554
+ "learning_rate": 3.614814814814815e-05,
555
+ "loss": 1.9332,
556
+ "step": 370
557
+ },
558
+ {
559
+ "epoch": 4.933333333333334,
560
+ "eval_loss": 2.7309281826019287,
561
+ "eval_runtime": 43.8842,
562
+ "eval_samples_per_second": 22.787,
563
+ "eval_steps_per_second": 2.848,
564
+ "step": 370
565
+ },
566
+ {
567
+ "epoch": 5.066666666666666,
568
+ "grad_norm": 2.8739213943481445,
569
+ "learning_rate": 3.4962962962962965e-05,
570
+ "loss": 1.8846,
571
+ "step": 380
572
+ },
573
+ {
574
+ "epoch": 5.066666666666666,
575
+ "eval_loss": 2.76513671875,
576
+ "eval_runtime": 43.906,
577
+ "eval_samples_per_second": 22.776,
578
+ "eval_steps_per_second": 2.847,
579
+ "step": 380
580
+ },
581
+ {
582
+ "epoch": 5.2,
583
+ "grad_norm": 3.9025838375091553,
584
+ "learning_rate": 3.377777777777778e-05,
585
+ "loss": 1.7575,
586
+ "step": 390
587
+ },
588
+ {
589
+ "epoch": 5.2,
590
+ "eval_loss": 2.847782611846924,
591
+ "eval_runtime": 43.8665,
592
+ "eval_samples_per_second": 22.796,
593
+ "eval_steps_per_second": 2.85,
594
+ "step": 390
595
+ },
596
+ {
597
+ "epoch": 5.333333333333333,
598
+ "grad_norm": 3.299649715423584,
599
+ "learning_rate": 3.259259259259259e-05,
600
+ "loss": 1.7713,
601
+ "step": 400
602
+ },
603
+ {
604
+ "epoch": 5.333333333333333,
605
+ "eval_loss": 2.8094286918640137,
606
+ "eval_runtime": 43.8629,
607
+ "eval_samples_per_second": 22.798,
608
+ "eval_steps_per_second": 2.85,
609
+ "step": 400
610
+ },
611
+ {
612
+ "epoch": 5.466666666666667,
613
+ "grad_norm": 3.4474265575408936,
614
+ "learning_rate": 3.140740740740741e-05,
615
+ "loss": 1.7983,
616
+ "step": 410
617
+ },
618
+ {
619
+ "epoch": 5.466666666666667,
620
+ "eval_loss": 2.827517509460449,
621
+ "eval_runtime": 43.8611,
622
+ "eval_samples_per_second": 22.799,
623
+ "eval_steps_per_second": 2.85,
624
+ "step": 410
625
+ },
626
+ {
627
+ "epoch": 5.6,
628
+ "grad_norm": 3.1924540996551514,
629
+ "learning_rate": 3.0222222222222225e-05,
630
+ "loss": 1.8091,
631
+ "step": 420
632
+ },
633
+ {
634
+ "epoch": 5.6,
635
+ "eval_loss": 2.81618332862854,
636
+ "eval_runtime": 43.8544,
637
+ "eval_samples_per_second": 22.803,
638
+ "eval_steps_per_second": 2.85,
639
+ "step": 420
640
+ },
641
+ {
642
+ "epoch": 5.733333333333333,
643
+ "grad_norm": 3.5224015712738037,
644
+ "learning_rate": 2.9037037037037042e-05,
645
+ "loss": 1.8253,
646
+ "step": 430
647
+ },
648
+ {
649
+ "epoch": 5.733333333333333,
650
+ "eval_loss": 2.816711187362671,
651
+ "eval_runtime": 43.8685,
652
+ "eval_samples_per_second": 22.795,
653
+ "eval_steps_per_second": 2.849,
654
+ "step": 430
655
+ },
656
+ {
657
+ "epoch": 5.866666666666667,
658
+ "grad_norm": 3.60918927192688,
659
+ "learning_rate": 2.7851851851851856e-05,
660
+ "loss": 1.8013,
661
+ "step": 440
662
+ },
663
+ {
664
+ "epoch": 5.866666666666667,
665
+ "eval_loss": 2.8146169185638428,
666
+ "eval_runtime": 43.8516,
667
+ "eval_samples_per_second": 22.804,
668
+ "eval_steps_per_second": 2.851,
669
+ "step": 440
670
+ },
671
+ {
672
+ "epoch": 6.0,
673
+ "grad_norm": 3.5798070430755615,
674
+ "learning_rate": 2.6666666666666667e-05,
675
+ "loss": 1.8258,
676
+ "step": 450
677
+ },
678
+ {
679
+ "epoch": 6.0,
680
+ "eval_loss": 2.8134233951568604,
681
+ "eval_runtime": 43.8442,
682
+ "eval_samples_per_second": 22.808,
683
+ "eval_steps_per_second": 2.851,
684
+ "step": 450
685
+ },
686
+ {
687
+ "epoch": 6.133333333333334,
688
+ "grad_norm": 5.563477993011475,
689
+ "learning_rate": 2.5481481481481484e-05,
690
+ "loss": 1.6649,
691
+ "step": 460
692
+ },
693
+ {
694
+ "epoch": 6.133333333333334,
695
+ "eval_loss": 2.9189789295196533,
696
+ "eval_runtime": 43.8602,
697
+ "eval_samples_per_second": 22.8,
698
+ "eval_steps_per_second": 2.85,
699
+ "step": 460
700
+ },
701
+ {
702
+ "epoch": 6.266666666666667,
703
+ "grad_norm": 4.192393779754639,
704
+ "learning_rate": 2.4296296296296298e-05,
705
+ "loss": 1.7443,
706
+ "step": 470
707
+ },
708
+ {
709
+ "epoch": 6.266666666666667,
710
+ "eval_loss": 2.893780469894409,
711
+ "eval_runtime": 43.8434,
712
+ "eval_samples_per_second": 22.808,
713
+ "eval_steps_per_second": 2.851,
714
+ "step": 470
715
+ },
716
+ {
717
+ "epoch": 6.4,
718
+ "grad_norm": 4.8650593757629395,
719
+ "learning_rate": 2.3111111111111112e-05,
720
+ "loss": 1.6961,
721
+ "step": 480
722
+ },
723
+ {
724
+ "epoch": 6.4,
725
+ "eval_loss": 2.8861398696899414,
726
+ "eval_runtime": 43.8417,
727
+ "eval_samples_per_second": 22.809,
728
+ "eval_steps_per_second": 2.851,
729
+ "step": 480
730
+ },
731
+ {
732
+ "epoch": 6.533333333333333,
733
+ "grad_norm": 3.844482660293579,
734
+ "learning_rate": 2.192592592592593e-05,
735
+ "loss": 1.6868,
736
+ "step": 490
737
+ },
738
+ {
739
+ "epoch": 6.533333333333333,
740
+ "eval_loss": 2.900317907333374,
741
+ "eval_runtime": 43.8557,
742
+ "eval_samples_per_second": 22.802,
743
+ "eval_steps_per_second": 2.85,
744
+ "step": 490
745
+ },
746
+ {
747
+ "epoch": 6.666666666666667,
748
+ "grad_norm": 4.230032920837402,
749
+ "learning_rate": 2.074074074074074e-05,
750
+ "loss": 1.6593,
751
+ "step": 500
752
+ },
753
+ {
754
+ "epoch": 6.666666666666667,
755
+ "eval_loss": 2.892076253890991,
756
+ "eval_runtime": 43.8479,
757
+ "eval_samples_per_second": 22.806,
758
+ "eval_steps_per_second": 2.851,
759
+ "step": 500
760
+ }
761
+ ],
762
+ "logging_steps": 10,
763
+ "max_steps": 675,
764
+ "num_input_tokens_seen": 0,
765
+ "num_train_epochs": 9,
766
+ "save_steps": 10,
767
+ "stateful_callbacks": {
768
+ "TrainerControl": {
769
+ "args": {
770
+ "should_epoch_stop": false,
771
+ "should_evaluate": false,
772
+ "should_log": false,
773
+ "should_save": true,
774
+ "should_training_stop": false
775
+ },
776
+ "attributes": {}
777
+ }
778
+ },
779
+ "total_flos": 8.193035993088e+16,
780
+ "train_batch_size": 8,
781
+ "trial_name": null,
782
+ "trial_params": null
783
+ }
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-510/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/pythia-6_9b
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-510/adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/workspace/pythia-6_9b",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.1,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 8,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "dense_h_to_4h",
24
+ "query_key_value",
25
+ "dense",
26
+ "dense_4h_to_h"
27
+ ],
28
+ "task_type": "CAUSAL_LM",
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-510/trainer_state.json ADDED
@@ -0,0 +1,798 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 2.535032033920288,
3
+ "best_model_checkpoint": "./output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-150",
4
+ "epoch": 6.8,
5
+ "eval_steps": 10,
6
+ "global_step": 510,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.13333333333333333,
13
+ "grad_norm": 0.36938729882240295,
14
+ "learning_rate": 7.881481481481482e-05,
15
+ "loss": 2.519,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.13333333333333333,
20
+ "eval_loss": 2.579638957977295,
21
+ "eval_runtime": 43.8215,
22
+ "eval_samples_per_second": 22.82,
23
+ "eval_steps_per_second": 2.852,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.26666666666666666,
28
+ "grad_norm": 0.39850670099258423,
29
+ "learning_rate": 7.762962962962963e-05,
30
+ "loss": 2.5224,
31
+ "step": 20
32
+ },
33
+ {
34
+ "epoch": 0.26666666666666666,
35
+ "eval_loss": 2.5729691982269287,
36
+ "eval_runtime": 43.8179,
37
+ "eval_samples_per_second": 22.822,
38
+ "eval_steps_per_second": 2.853,
39
+ "step": 20
40
+ },
41
+ {
42
+ "epoch": 0.4,
43
+ "grad_norm": 0.40211933851242065,
44
+ "learning_rate": 7.644444444444445e-05,
45
+ "loss": 2.5169,
46
+ "step": 30
47
+ },
48
+ {
49
+ "epoch": 0.4,
50
+ "eval_loss": 2.567735433578491,
51
+ "eval_runtime": 43.8366,
52
+ "eval_samples_per_second": 22.812,
53
+ "eval_steps_per_second": 2.851,
54
+ "step": 30
55
+ },
56
+ {
57
+ "epoch": 0.5333333333333333,
58
+ "grad_norm": 0.6892333030700684,
59
+ "learning_rate": 7.525925925925926e-05,
60
+ "loss": 2.5784,
61
+ "step": 40
62
+ },
63
+ {
64
+ "epoch": 0.5333333333333333,
65
+ "eval_loss": 2.562650442123413,
66
+ "eval_runtime": 43.8377,
67
+ "eval_samples_per_second": 22.811,
68
+ "eval_steps_per_second": 2.851,
69
+ "step": 40
70
+ },
71
+ {
72
+ "epoch": 0.6666666666666666,
73
+ "grad_norm": 0.442343533039093,
74
+ "learning_rate": 7.407407407407409e-05,
75
+ "loss": 2.5431,
76
+ "step": 50
77
+ },
78
+ {
79
+ "epoch": 0.6666666666666666,
80
+ "eval_loss": 2.556513786315918,
81
+ "eval_runtime": 43.8656,
82
+ "eval_samples_per_second": 22.797,
83
+ "eval_steps_per_second": 2.85,
84
+ "step": 50
85
+ },
86
+ {
87
+ "epoch": 0.8,
88
+ "grad_norm": 0.4059845805168152,
89
+ "learning_rate": 7.28888888888889e-05,
90
+ "loss": 2.4936,
91
+ "step": 60
92
+ },
93
+ {
94
+ "epoch": 0.8,
95
+ "eval_loss": 2.552133798599243,
96
+ "eval_runtime": 43.8403,
97
+ "eval_samples_per_second": 22.81,
98
+ "eval_steps_per_second": 2.851,
99
+ "step": 60
100
+ },
101
+ {
102
+ "epoch": 0.9333333333333333,
103
+ "grad_norm": 0.48126307129859924,
104
+ "learning_rate": 7.170370370370371e-05,
105
+ "loss": 2.4901,
106
+ "step": 70
107
+ },
108
+ {
109
+ "epoch": 0.9333333333333333,
110
+ "eval_loss": 2.5477023124694824,
111
+ "eval_runtime": 43.8351,
112
+ "eval_samples_per_second": 22.813,
113
+ "eval_steps_per_second": 2.852,
114
+ "step": 70
115
+ },
116
+ {
117
+ "epoch": 1.0666666666666667,
118
+ "grad_norm": 0.48629865050315857,
119
+ "learning_rate": 7.051851851851853e-05,
120
+ "loss": 2.5114,
121
+ "step": 80
122
+ },
123
+ {
124
+ "epoch": 1.0666666666666667,
125
+ "eval_loss": 2.543431043624878,
126
+ "eval_runtime": 43.8432,
127
+ "eval_samples_per_second": 22.809,
128
+ "eval_steps_per_second": 2.851,
129
+ "step": 80
130
+ },
131
+ {
132
+ "epoch": 1.2,
133
+ "grad_norm": 0.5880796313285828,
134
+ "learning_rate": 6.933333333333334e-05,
135
+ "loss": 2.4446,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 1.2,
140
+ "eval_loss": 2.544339418411255,
141
+ "eval_runtime": 43.8437,
142
+ "eval_samples_per_second": 22.808,
143
+ "eval_steps_per_second": 2.851,
144
+ "step": 90
145
+ },
146
+ {
147
+ "epoch": 1.3333333333333333,
148
+ "grad_norm": 0.6746829748153687,
149
+ "learning_rate": 6.814814814814815e-05,
150
+ "loss": 2.4477,
151
+ "step": 100
152
+ },
153
+ {
154
+ "epoch": 1.3333333333333333,
155
+ "eval_loss": 2.544358968734741,
156
+ "eval_runtime": 43.8613,
157
+ "eval_samples_per_second": 22.799,
158
+ "eval_steps_per_second": 2.85,
159
+ "step": 100
160
+ },
161
+ {
162
+ "epoch": 1.4666666666666668,
163
+ "grad_norm": 0.8208937048912048,
164
+ "learning_rate": 6.696296296296296e-05,
165
+ "loss": 2.4004,
166
+ "step": 110
167
+ },
168
+ {
169
+ "epoch": 1.4666666666666668,
170
+ "eval_loss": 2.54068660736084,
171
+ "eval_runtime": 43.8426,
172
+ "eval_samples_per_second": 22.809,
173
+ "eval_steps_per_second": 2.851,
174
+ "step": 110
175
+ },
176
+ {
177
+ "epoch": 1.6,
178
+ "grad_norm": 0.925931453704834,
179
+ "learning_rate": 6.577777777777777e-05,
180
+ "loss": 2.3889,
181
+ "step": 120
182
+ },
183
+ {
184
+ "epoch": 1.6,
185
+ "eval_loss": 2.5393033027648926,
186
+ "eval_runtime": 43.8383,
187
+ "eval_samples_per_second": 22.811,
188
+ "eval_steps_per_second": 2.851,
189
+ "step": 120
190
+ },
191
+ {
192
+ "epoch": 1.7333333333333334,
193
+ "grad_norm": 0.8785662055015564,
194
+ "learning_rate": 6.45925925925926e-05,
195
+ "loss": 2.3959,
196
+ "step": 130
197
+ },
198
+ {
199
+ "epoch": 1.7333333333333334,
200
+ "eval_loss": 2.5367038249969482,
201
+ "eval_runtime": 43.8508,
202
+ "eval_samples_per_second": 22.805,
203
+ "eval_steps_per_second": 2.851,
204
+ "step": 130
205
+ },
206
+ {
207
+ "epoch": 1.8666666666666667,
208
+ "grad_norm": 0.941368818283081,
209
+ "learning_rate": 6.340740740740741e-05,
210
+ "loss": 2.3924,
211
+ "step": 140
212
+ },
213
+ {
214
+ "epoch": 1.8666666666666667,
215
+ "eval_loss": 2.535139560699463,
216
+ "eval_runtime": 43.8588,
217
+ "eval_samples_per_second": 22.8,
218
+ "eval_steps_per_second": 2.85,
219
+ "step": 140
220
+ },
221
+ {
222
+ "epoch": 2.0,
223
+ "grad_norm": 0.9578835368156433,
224
+ "learning_rate": 6.222222222222223e-05,
225
+ "loss": 2.4278,
226
+ "step": 150
227
+ },
228
+ {
229
+ "epoch": 2.0,
230
+ "eval_loss": 2.535032033920288,
231
+ "eval_runtime": 43.8484,
232
+ "eval_samples_per_second": 22.806,
233
+ "eval_steps_per_second": 2.851,
234
+ "step": 150
235
+ },
236
+ {
237
+ "epoch": 2.1333333333333333,
238
+ "grad_norm": 1.1541856527328491,
239
+ "learning_rate": 6.103703703703704e-05,
240
+ "loss": 2.2895,
241
+ "step": 160
242
+ },
243
+ {
244
+ "epoch": 2.1333333333333333,
245
+ "eval_loss": 2.564768075942993,
246
+ "eval_runtime": 43.8568,
247
+ "eval_samples_per_second": 22.801,
248
+ "eval_steps_per_second": 2.85,
249
+ "step": 160
250
+ },
251
+ {
252
+ "epoch": 2.2666666666666666,
253
+ "grad_norm": 1.4076604843139648,
254
+ "learning_rate": 5.9851851851851855e-05,
255
+ "loss": 2.2107,
256
+ "step": 170
257
+ },
258
+ {
259
+ "epoch": 2.2666666666666666,
260
+ "eval_loss": 2.5832314491271973,
261
+ "eval_runtime": 43.8455,
262
+ "eval_samples_per_second": 22.807,
263
+ "eval_steps_per_second": 2.851,
264
+ "step": 170
265
+ },
266
+ {
267
+ "epoch": 2.4,
268
+ "grad_norm": 1.4847813844680786,
269
+ "learning_rate": 5.8666666666666665e-05,
270
+ "loss": 2.2588,
271
+ "step": 180
272
+ },
273
+ {
274
+ "epoch": 2.4,
275
+ "eval_loss": 2.5781586170196533,
276
+ "eval_runtime": 43.8578,
277
+ "eval_samples_per_second": 22.801,
278
+ "eval_steps_per_second": 2.85,
279
+ "step": 180
280
+ },
281
+ {
282
+ "epoch": 2.533333333333333,
283
+ "grad_norm": 1.5135377645492554,
284
+ "learning_rate": 5.748148148148149e-05,
285
+ "loss": 2.2099,
286
+ "step": 190
287
+ },
288
+ {
289
+ "epoch": 2.533333333333333,
290
+ "eval_loss": 2.5752007961273193,
291
+ "eval_runtime": 43.8521,
292
+ "eval_samples_per_second": 22.804,
293
+ "eval_steps_per_second": 2.85,
294
+ "step": 190
295
+ },
296
+ {
297
+ "epoch": 2.6666666666666665,
298
+ "grad_norm": 1.5297592878341675,
299
+ "learning_rate": 5.62962962962963e-05,
300
+ "loss": 2.2965,
301
+ "step": 200
302
+ },
303
+ {
304
+ "epoch": 2.6666666666666665,
305
+ "eval_loss": 2.579918622970581,
306
+ "eval_runtime": 43.8661,
307
+ "eval_samples_per_second": 22.797,
308
+ "eval_steps_per_second": 2.85,
309
+ "step": 200
310
+ },
311
+ {
312
+ "epoch": 2.8,
313
+ "grad_norm": 1.6282892227172852,
314
+ "learning_rate": 5.511111111111112e-05,
315
+ "loss": 2.2487,
316
+ "step": 210
317
+ },
318
+ {
319
+ "epoch": 2.8,
320
+ "eval_loss": 2.5760037899017334,
321
+ "eval_runtime": 43.8379,
322
+ "eval_samples_per_second": 22.811,
323
+ "eval_steps_per_second": 2.851,
324
+ "step": 210
325
+ },
326
+ {
327
+ "epoch": 2.9333333333333336,
328
+ "grad_norm": 1.74424409866333,
329
+ "learning_rate": 5.392592592592593e-05,
330
+ "loss": 2.2049,
331
+ "step": 220
332
+ },
333
+ {
334
+ "epoch": 2.9333333333333336,
335
+ "eval_loss": 2.576190233230591,
336
+ "eval_runtime": 43.8491,
337
+ "eval_samples_per_second": 22.805,
338
+ "eval_steps_per_second": 2.851,
339
+ "step": 220
340
+ },
341
+ {
342
+ "epoch": 3.066666666666667,
343
+ "grad_norm": 1.654069423675537,
344
+ "learning_rate": 5.274074074074074e-05,
345
+ "loss": 2.1188,
346
+ "step": 230
347
+ },
348
+ {
349
+ "epoch": 3.066666666666667,
350
+ "eval_loss": 2.5971405506134033,
351
+ "eval_runtime": 43.855,
352
+ "eval_samples_per_second": 22.802,
353
+ "eval_steps_per_second": 2.85,
354
+ "step": 230
355
+ },
356
+ {
357
+ "epoch": 3.2,
358
+ "grad_norm": 2.541767120361328,
359
+ "learning_rate": 5.155555555555556e-05,
360
+ "loss": 2.0788,
361
+ "step": 240
362
+ },
363
+ {
364
+ "epoch": 3.2,
365
+ "eval_loss": 2.6767666339874268,
366
+ "eval_runtime": 43.8368,
367
+ "eval_samples_per_second": 22.812,
368
+ "eval_steps_per_second": 2.851,
369
+ "step": 240
370
+ },
371
+ {
372
+ "epoch": 3.3333333333333335,
373
+ "grad_norm": 2.0508077144622803,
374
+ "learning_rate": 5.037037037037037e-05,
375
+ "loss": 2.0784,
376
+ "step": 250
377
+ },
378
+ {
379
+ "epoch": 3.3333333333333335,
380
+ "eval_loss": 2.6486454010009766,
381
+ "eval_runtime": 43.8529,
382
+ "eval_samples_per_second": 22.803,
383
+ "eval_steps_per_second": 2.85,
384
+ "step": 250
385
+ },
386
+ {
387
+ "epoch": 3.466666666666667,
388
+ "grad_norm": 2.1096036434173584,
389
+ "learning_rate": 4.918518518518519e-05,
390
+ "loss": 2.0633,
391
+ "step": 260
392
+ },
393
+ {
394
+ "epoch": 3.466666666666667,
395
+ "eval_loss": 2.6501405239105225,
396
+ "eval_runtime": 43.8632,
397
+ "eval_samples_per_second": 22.798,
398
+ "eval_steps_per_second": 2.85,
399
+ "step": 260
400
+ },
401
+ {
402
+ "epoch": 3.6,
403
+ "grad_norm": 2.3028736114501953,
404
+ "learning_rate": 4.8e-05,
405
+ "loss": 2.0722,
406
+ "step": 270
407
+ },
408
+ {
409
+ "epoch": 3.6,
410
+ "eval_loss": 2.657053232192993,
411
+ "eval_runtime": 43.8423,
412
+ "eval_samples_per_second": 22.809,
413
+ "eval_steps_per_second": 2.851,
414
+ "step": 270
415
+ },
416
+ {
417
+ "epoch": 3.7333333333333334,
418
+ "grad_norm": 2.1536757946014404,
419
+ "learning_rate": 4.681481481481481e-05,
420
+ "loss": 2.0155,
421
+ "step": 280
422
+ },
423
+ {
424
+ "epoch": 3.7333333333333334,
425
+ "eval_loss": 2.648275375366211,
426
+ "eval_runtime": 43.8328,
427
+ "eval_samples_per_second": 22.814,
428
+ "eval_steps_per_second": 2.852,
429
+ "step": 280
430
+ },
431
+ {
432
+ "epoch": 3.8666666666666667,
433
+ "grad_norm": 2.4079270362854004,
434
+ "learning_rate": 4.5629629629629636e-05,
435
+ "loss": 2.1111,
436
+ "step": 290
437
+ },
438
+ {
439
+ "epoch": 3.8666666666666667,
440
+ "eval_loss": 2.650322675704956,
441
+ "eval_runtime": 43.835,
442
+ "eval_samples_per_second": 22.813,
443
+ "eval_steps_per_second": 2.852,
444
+ "step": 290
445
+ },
446
+ {
447
+ "epoch": 4.0,
448
+ "grad_norm": 2.426234722137451,
449
+ "learning_rate": 4.444444444444445e-05,
450
+ "loss": 2.041,
451
+ "step": 300
452
+ },
453
+ {
454
+ "epoch": 4.0,
455
+ "eval_loss": 2.6490862369537354,
456
+ "eval_runtime": 43.845,
457
+ "eval_samples_per_second": 22.808,
458
+ "eval_steps_per_second": 2.851,
459
+ "step": 300
460
+ },
461
+ {
462
+ "epoch": 4.133333333333334,
463
+ "grad_norm": 2.8063745498657227,
464
+ "learning_rate": 4.3259259259259264e-05,
465
+ "loss": 1.9316,
466
+ "step": 310
467
+ },
468
+ {
469
+ "epoch": 4.133333333333334,
470
+ "eval_loss": 2.7609620094299316,
471
+ "eval_runtime": 43.8481,
472
+ "eval_samples_per_second": 22.806,
473
+ "eval_steps_per_second": 2.851,
474
+ "step": 310
475
+ },
476
+ {
477
+ "epoch": 4.266666666666667,
478
+ "grad_norm": 2.96854305267334,
479
+ "learning_rate": 4.2074074074074075e-05,
480
+ "loss": 1.8889,
481
+ "step": 320
482
+ },
483
+ {
484
+ "epoch": 4.266666666666667,
485
+ "eval_loss": 2.736968994140625,
486
+ "eval_runtime": 43.8633,
487
+ "eval_samples_per_second": 22.798,
488
+ "eval_steps_per_second": 2.85,
489
+ "step": 320
490
+ },
491
+ {
492
+ "epoch": 4.4,
493
+ "grad_norm": 2.637695789337158,
494
+ "learning_rate": 4.088888888888889e-05,
495
+ "loss": 1.9187,
496
+ "step": 330
497
+ },
498
+ {
499
+ "epoch": 4.4,
500
+ "eval_loss": 2.7382876873016357,
501
+ "eval_runtime": 43.8486,
502
+ "eval_samples_per_second": 22.806,
503
+ "eval_steps_per_second": 2.851,
504
+ "step": 330
505
+ },
506
+ {
507
+ "epoch": 4.533333333333333,
508
+ "grad_norm": 2.9106290340423584,
509
+ "learning_rate": 3.970370370370371e-05,
510
+ "loss": 1.9002,
511
+ "step": 340
512
+ },
513
+ {
514
+ "epoch": 4.533333333333333,
515
+ "eval_loss": 2.734544515609741,
516
+ "eval_runtime": 43.8491,
517
+ "eval_samples_per_second": 22.805,
518
+ "eval_steps_per_second": 2.851,
519
+ "step": 340
520
+ },
521
+ {
522
+ "epoch": 4.666666666666667,
523
+ "grad_norm": 2.769315481185913,
524
+ "learning_rate": 3.851851851851852e-05,
525
+ "loss": 1.9251,
526
+ "step": 350
527
+ },
528
+ {
529
+ "epoch": 4.666666666666667,
530
+ "eval_loss": 2.734708070755005,
531
+ "eval_runtime": 43.8534,
532
+ "eval_samples_per_second": 22.803,
533
+ "eval_steps_per_second": 2.85,
534
+ "step": 350
535
+ },
536
+ {
537
+ "epoch": 4.8,
538
+ "grad_norm": 2.940281867980957,
539
+ "learning_rate": 3.733333333333334e-05,
540
+ "loss": 1.9319,
541
+ "step": 360
542
+ },
543
+ {
544
+ "epoch": 4.8,
545
+ "eval_loss": 2.7300503253936768,
546
+ "eval_runtime": 43.9017,
547
+ "eval_samples_per_second": 22.778,
548
+ "eval_steps_per_second": 2.847,
549
+ "step": 360
550
+ },
551
+ {
552
+ "epoch": 4.933333333333334,
553
+ "grad_norm": 2.8305609226226807,
554
+ "learning_rate": 3.614814814814815e-05,
555
+ "loss": 1.9332,
556
+ "step": 370
557
+ },
558
+ {
559
+ "epoch": 4.933333333333334,
560
+ "eval_loss": 2.7309281826019287,
561
+ "eval_runtime": 43.8842,
562
+ "eval_samples_per_second": 22.787,
563
+ "eval_steps_per_second": 2.848,
564
+ "step": 370
565
+ },
566
+ {
567
+ "epoch": 5.066666666666666,
568
+ "grad_norm": 2.8739213943481445,
569
+ "learning_rate": 3.4962962962962965e-05,
570
+ "loss": 1.8846,
571
+ "step": 380
572
+ },
573
+ {
574
+ "epoch": 5.066666666666666,
575
+ "eval_loss": 2.76513671875,
576
+ "eval_runtime": 43.906,
577
+ "eval_samples_per_second": 22.776,
578
+ "eval_steps_per_second": 2.847,
579
+ "step": 380
580
+ },
581
+ {
582
+ "epoch": 5.2,
583
+ "grad_norm": 3.9025838375091553,
584
+ "learning_rate": 3.377777777777778e-05,
585
+ "loss": 1.7575,
586
+ "step": 390
587
+ },
588
+ {
589
+ "epoch": 5.2,
590
+ "eval_loss": 2.847782611846924,
591
+ "eval_runtime": 43.8665,
592
+ "eval_samples_per_second": 22.796,
593
+ "eval_steps_per_second": 2.85,
594
+ "step": 390
595
+ },
596
+ {
597
+ "epoch": 5.333333333333333,
598
+ "grad_norm": 3.299649715423584,
599
+ "learning_rate": 3.259259259259259e-05,
600
+ "loss": 1.7713,
601
+ "step": 400
602
+ },
603
+ {
604
+ "epoch": 5.333333333333333,
605
+ "eval_loss": 2.8094286918640137,
606
+ "eval_runtime": 43.8629,
607
+ "eval_samples_per_second": 22.798,
608
+ "eval_steps_per_second": 2.85,
609
+ "step": 400
610
+ },
611
+ {
612
+ "epoch": 5.466666666666667,
613
+ "grad_norm": 3.4474265575408936,
614
+ "learning_rate": 3.140740740740741e-05,
615
+ "loss": 1.7983,
616
+ "step": 410
617
+ },
618
+ {
619
+ "epoch": 5.466666666666667,
620
+ "eval_loss": 2.827517509460449,
621
+ "eval_runtime": 43.8611,
622
+ "eval_samples_per_second": 22.799,
623
+ "eval_steps_per_second": 2.85,
624
+ "step": 410
625
+ },
626
+ {
627
+ "epoch": 5.6,
628
+ "grad_norm": 3.1924540996551514,
629
+ "learning_rate": 3.0222222222222225e-05,
630
+ "loss": 1.8091,
631
+ "step": 420
632
+ },
633
+ {
634
+ "epoch": 5.6,
635
+ "eval_loss": 2.81618332862854,
636
+ "eval_runtime": 43.8544,
637
+ "eval_samples_per_second": 22.803,
638
+ "eval_steps_per_second": 2.85,
639
+ "step": 420
640
+ },
641
+ {
642
+ "epoch": 5.733333333333333,
643
+ "grad_norm": 3.5224015712738037,
644
+ "learning_rate": 2.9037037037037042e-05,
645
+ "loss": 1.8253,
646
+ "step": 430
647
+ },
648
+ {
649
+ "epoch": 5.733333333333333,
650
+ "eval_loss": 2.816711187362671,
651
+ "eval_runtime": 43.8685,
652
+ "eval_samples_per_second": 22.795,
653
+ "eval_steps_per_second": 2.849,
654
+ "step": 430
655
+ },
656
+ {
657
+ "epoch": 5.866666666666667,
658
+ "grad_norm": 3.60918927192688,
659
+ "learning_rate": 2.7851851851851856e-05,
660
+ "loss": 1.8013,
661
+ "step": 440
662
+ },
663
+ {
664
+ "epoch": 5.866666666666667,
665
+ "eval_loss": 2.8146169185638428,
666
+ "eval_runtime": 43.8516,
667
+ "eval_samples_per_second": 22.804,
668
+ "eval_steps_per_second": 2.851,
669
+ "step": 440
670
+ },
671
+ {
672
+ "epoch": 6.0,
673
+ "grad_norm": 3.5798070430755615,
674
+ "learning_rate": 2.6666666666666667e-05,
675
+ "loss": 1.8258,
676
+ "step": 450
677
+ },
678
+ {
679
+ "epoch": 6.0,
680
+ "eval_loss": 2.8134233951568604,
681
+ "eval_runtime": 43.8442,
682
+ "eval_samples_per_second": 22.808,
683
+ "eval_steps_per_second": 2.851,
684
+ "step": 450
685
+ },
686
+ {
687
+ "epoch": 6.133333333333334,
688
+ "grad_norm": 5.563477993011475,
689
+ "learning_rate": 2.5481481481481484e-05,
690
+ "loss": 1.6649,
691
+ "step": 460
692
+ },
693
+ {
694
+ "epoch": 6.133333333333334,
695
+ "eval_loss": 2.9189789295196533,
696
+ "eval_runtime": 43.8602,
697
+ "eval_samples_per_second": 22.8,
698
+ "eval_steps_per_second": 2.85,
699
+ "step": 460
700
+ },
701
+ {
702
+ "epoch": 6.266666666666667,
703
+ "grad_norm": 4.192393779754639,
704
+ "learning_rate": 2.4296296296296298e-05,
705
+ "loss": 1.7443,
706
+ "step": 470
707
+ },
708
+ {
709
+ "epoch": 6.266666666666667,
710
+ "eval_loss": 2.893780469894409,
711
+ "eval_runtime": 43.8434,
712
+ "eval_samples_per_second": 22.808,
713
+ "eval_steps_per_second": 2.851,
714
+ "step": 470
715
+ },
716
+ {
717
+ "epoch": 6.4,
718
+ "grad_norm": 4.8650593757629395,
719
+ "learning_rate": 2.3111111111111112e-05,
720
+ "loss": 1.6961,
721
+ "step": 480
722
+ },
723
+ {
724
+ "epoch": 6.4,
725
+ "eval_loss": 2.8861398696899414,
726
+ "eval_runtime": 43.8417,
727
+ "eval_samples_per_second": 22.809,
728
+ "eval_steps_per_second": 2.851,
729
+ "step": 480
730
+ },
731
+ {
732
+ "epoch": 6.533333333333333,
733
+ "grad_norm": 3.844482660293579,
734
+ "learning_rate": 2.192592592592593e-05,
735
+ "loss": 1.6868,
736
+ "step": 490
737
+ },
738
+ {
739
+ "epoch": 6.533333333333333,
740
+ "eval_loss": 2.900317907333374,
741
+ "eval_runtime": 43.8557,
742
+ "eval_samples_per_second": 22.802,
743
+ "eval_steps_per_second": 2.85,
744
+ "step": 490
745
+ },
746
+ {
747
+ "epoch": 6.666666666666667,
748
+ "grad_norm": 4.230032920837402,
749
+ "learning_rate": 2.074074074074074e-05,
750
+ "loss": 1.6593,
751
+ "step": 500
752
+ },
753
+ {
754
+ "epoch": 6.666666666666667,
755
+ "eval_loss": 2.892076253890991,
756
+ "eval_runtime": 43.8479,
757
+ "eval_samples_per_second": 22.806,
758
+ "eval_steps_per_second": 2.851,
759
+ "step": 500
760
+ },
761
+ {
762
+ "epoch": 6.8,
763
+ "grad_norm": 4.427380561828613,
764
+ "learning_rate": 1.9555555555555557e-05,
765
+ "loss": 1.6777,
766
+ "step": 510
767
+ },
768
+ {
769
+ "epoch": 6.8,
770
+ "eval_loss": 2.8877696990966797,
771
+ "eval_runtime": 43.8489,
772
+ "eval_samples_per_second": 22.806,
773
+ "eval_steps_per_second": 2.851,
774
+ "step": 510
775
+ }
776
+ ],
777
+ "logging_steps": 10,
778
+ "max_steps": 675,
779
+ "num_input_tokens_seen": 0,
780
+ "num_train_epochs": 9,
781
+ "save_steps": 10,
782
+ "stateful_callbacks": {
783
+ "TrainerControl": {
784
+ "args": {
785
+ "should_epoch_stop": false,
786
+ "should_evaluate": false,
787
+ "should_log": false,
788
+ "should_save": true,
789
+ "should_training_stop": false
790
+ },
791
+ "attributes": {}
792
+ }
793
+ },
794
+ "total_flos": 8.35689671294976e+16,
795
+ "train_batch_size": 8,
796
+ "trial_name": null,
797
+ "trial_params": null
798
+ }
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-520/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/pythia-6_9b
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-520/adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/workspace/pythia-6_9b",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.1,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 8,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "dense_h_to_4h",
24
+ "query_key_value",
25
+ "dense",
26
+ "dense_4h_to_h"
27
+ ],
28
+ "task_type": "CAUSAL_LM",
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-520/trainer_state.json ADDED
@@ -0,0 +1,813 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 2.535032033920288,
3
+ "best_model_checkpoint": "./output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-150",
4
+ "epoch": 6.933333333333334,
5
+ "eval_steps": 10,
6
+ "global_step": 520,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.13333333333333333,
13
+ "grad_norm": 0.36938729882240295,
14
+ "learning_rate": 7.881481481481482e-05,
15
+ "loss": 2.519,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.13333333333333333,
20
+ "eval_loss": 2.579638957977295,
21
+ "eval_runtime": 43.8215,
22
+ "eval_samples_per_second": 22.82,
23
+ "eval_steps_per_second": 2.852,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.26666666666666666,
28
+ "grad_norm": 0.39850670099258423,
29
+ "learning_rate": 7.762962962962963e-05,
30
+ "loss": 2.5224,
31
+ "step": 20
32
+ },
33
+ {
34
+ "epoch": 0.26666666666666666,
35
+ "eval_loss": 2.5729691982269287,
36
+ "eval_runtime": 43.8179,
37
+ "eval_samples_per_second": 22.822,
38
+ "eval_steps_per_second": 2.853,
39
+ "step": 20
40
+ },
41
+ {
42
+ "epoch": 0.4,
43
+ "grad_norm": 0.40211933851242065,
44
+ "learning_rate": 7.644444444444445e-05,
45
+ "loss": 2.5169,
46
+ "step": 30
47
+ },
48
+ {
49
+ "epoch": 0.4,
50
+ "eval_loss": 2.567735433578491,
51
+ "eval_runtime": 43.8366,
52
+ "eval_samples_per_second": 22.812,
53
+ "eval_steps_per_second": 2.851,
54
+ "step": 30
55
+ },
56
+ {
57
+ "epoch": 0.5333333333333333,
58
+ "grad_norm": 0.6892333030700684,
59
+ "learning_rate": 7.525925925925926e-05,
60
+ "loss": 2.5784,
61
+ "step": 40
62
+ },
63
+ {
64
+ "epoch": 0.5333333333333333,
65
+ "eval_loss": 2.562650442123413,
66
+ "eval_runtime": 43.8377,
67
+ "eval_samples_per_second": 22.811,
68
+ "eval_steps_per_second": 2.851,
69
+ "step": 40
70
+ },
71
+ {
72
+ "epoch": 0.6666666666666666,
73
+ "grad_norm": 0.442343533039093,
74
+ "learning_rate": 7.407407407407409e-05,
75
+ "loss": 2.5431,
76
+ "step": 50
77
+ },
78
+ {
79
+ "epoch": 0.6666666666666666,
80
+ "eval_loss": 2.556513786315918,
81
+ "eval_runtime": 43.8656,
82
+ "eval_samples_per_second": 22.797,
83
+ "eval_steps_per_second": 2.85,
84
+ "step": 50
85
+ },
86
+ {
87
+ "epoch": 0.8,
88
+ "grad_norm": 0.4059845805168152,
89
+ "learning_rate": 7.28888888888889e-05,
90
+ "loss": 2.4936,
91
+ "step": 60
92
+ },
93
+ {
94
+ "epoch": 0.8,
95
+ "eval_loss": 2.552133798599243,
96
+ "eval_runtime": 43.8403,
97
+ "eval_samples_per_second": 22.81,
98
+ "eval_steps_per_second": 2.851,
99
+ "step": 60
100
+ },
101
+ {
102
+ "epoch": 0.9333333333333333,
103
+ "grad_norm": 0.48126307129859924,
104
+ "learning_rate": 7.170370370370371e-05,
105
+ "loss": 2.4901,
106
+ "step": 70
107
+ },
108
+ {
109
+ "epoch": 0.9333333333333333,
110
+ "eval_loss": 2.5477023124694824,
111
+ "eval_runtime": 43.8351,
112
+ "eval_samples_per_second": 22.813,
113
+ "eval_steps_per_second": 2.852,
114
+ "step": 70
115
+ },
116
+ {
117
+ "epoch": 1.0666666666666667,
118
+ "grad_norm": 0.48629865050315857,
119
+ "learning_rate": 7.051851851851853e-05,
120
+ "loss": 2.5114,
121
+ "step": 80
122
+ },
123
+ {
124
+ "epoch": 1.0666666666666667,
125
+ "eval_loss": 2.543431043624878,
126
+ "eval_runtime": 43.8432,
127
+ "eval_samples_per_second": 22.809,
128
+ "eval_steps_per_second": 2.851,
129
+ "step": 80
130
+ },
131
+ {
132
+ "epoch": 1.2,
133
+ "grad_norm": 0.5880796313285828,
134
+ "learning_rate": 6.933333333333334e-05,
135
+ "loss": 2.4446,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 1.2,
140
+ "eval_loss": 2.544339418411255,
141
+ "eval_runtime": 43.8437,
142
+ "eval_samples_per_second": 22.808,
143
+ "eval_steps_per_second": 2.851,
144
+ "step": 90
145
+ },
146
+ {
147
+ "epoch": 1.3333333333333333,
148
+ "grad_norm": 0.6746829748153687,
149
+ "learning_rate": 6.814814814814815e-05,
150
+ "loss": 2.4477,
151
+ "step": 100
152
+ },
153
+ {
154
+ "epoch": 1.3333333333333333,
155
+ "eval_loss": 2.544358968734741,
156
+ "eval_runtime": 43.8613,
157
+ "eval_samples_per_second": 22.799,
158
+ "eval_steps_per_second": 2.85,
159
+ "step": 100
160
+ },
161
+ {
162
+ "epoch": 1.4666666666666668,
163
+ "grad_norm": 0.8208937048912048,
164
+ "learning_rate": 6.696296296296296e-05,
165
+ "loss": 2.4004,
166
+ "step": 110
167
+ },
168
+ {
169
+ "epoch": 1.4666666666666668,
170
+ "eval_loss": 2.54068660736084,
171
+ "eval_runtime": 43.8426,
172
+ "eval_samples_per_second": 22.809,
173
+ "eval_steps_per_second": 2.851,
174
+ "step": 110
175
+ },
176
+ {
177
+ "epoch": 1.6,
178
+ "grad_norm": 0.925931453704834,
179
+ "learning_rate": 6.577777777777777e-05,
180
+ "loss": 2.3889,
181
+ "step": 120
182
+ },
183
+ {
184
+ "epoch": 1.6,
185
+ "eval_loss": 2.5393033027648926,
186
+ "eval_runtime": 43.8383,
187
+ "eval_samples_per_second": 22.811,
188
+ "eval_steps_per_second": 2.851,
189
+ "step": 120
190
+ },
191
+ {
192
+ "epoch": 1.7333333333333334,
193
+ "grad_norm": 0.8785662055015564,
194
+ "learning_rate": 6.45925925925926e-05,
195
+ "loss": 2.3959,
196
+ "step": 130
197
+ },
198
+ {
199
+ "epoch": 1.7333333333333334,
200
+ "eval_loss": 2.5367038249969482,
201
+ "eval_runtime": 43.8508,
202
+ "eval_samples_per_second": 22.805,
203
+ "eval_steps_per_second": 2.851,
204
+ "step": 130
205
+ },
206
+ {
207
+ "epoch": 1.8666666666666667,
208
+ "grad_norm": 0.941368818283081,
209
+ "learning_rate": 6.340740740740741e-05,
210
+ "loss": 2.3924,
211
+ "step": 140
212
+ },
213
+ {
214
+ "epoch": 1.8666666666666667,
215
+ "eval_loss": 2.535139560699463,
216
+ "eval_runtime": 43.8588,
217
+ "eval_samples_per_second": 22.8,
218
+ "eval_steps_per_second": 2.85,
219
+ "step": 140
220
+ },
221
+ {
222
+ "epoch": 2.0,
223
+ "grad_norm": 0.9578835368156433,
224
+ "learning_rate": 6.222222222222223e-05,
225
+ "loss": 2.4278,
226
+ "step": 150
227
+ },
228
+ {
229
+ "epoch": 2.0,
230
+ "eval_loss": 2.535032033920288,
231
+ "eval_runtime": 43.8484,
232
+ "eval_samples_per_second": 22.806,
233
+ "eval_steps_per_second": 2.851,
234
+ "step": 150
235
+ },
236
+ {
237
+ "epoch": 2.1333333333333333,
238
+ "grad_norm": 1.1541856527328491,
239
+ "learning_rate": 6.103703703703704e-05,
240
+ "loss": 2.2895,
241
+ "step": 160
242
+ },
243
+ {
244
+ "epoch": 2.1333333333333333,
245
+ "eval_loss": 2.564768075942993,
246
+ "eval_runtime": 43.8568,
247
+ "eval_samples_per_second": 22.801,
248
+ "eval_steps_per_second": 2.85,
249
+ "step": 160
250
+ },
251
+ {
252
+ "epoch": 2.2666666666666666,
253
+ "grad_norm": 1.4076604843139648,
254
+ "learning_rate": 5.9851851851851855e-05,
255
+ "loss": 2.2107,
256
+ "step": 170
257
+ },
258
+ {
259
+ "epoch": 2.2666666666666666,
260
+ "eval_loss": 2.5832314491271973,
261
+ "eval_runtime": 43.8455,
262
+ "eval_samples_per_second": 22.807,
263
+ "eval_steps_per_second": 2.851,
264
+ "step": 170
265
+ },
266
+ {
267
+ "epoch": 2.4,
268
+ "grad_norm": 1.4847813844680786,
269
+ "learning_rate": 5.8666666666666665e-05,
270
+ "loss": 2.2588,
271
+ "step": 180
272
+ },
273
+ {
274
+ "epoch": 2.4,
275
+ "eval_loss": 2.5781586170196533,
276
+ "eval_runtime": 43.8578,
277
+ "eval_samples_per_second": 22.801,
278
+ "eval_steps_per_second": 2.85,
279
+ "step": 180
280
+ },
281
+ {
282
+ "epoch": 2.533333333333333,
283
+ "grad_norm": 1.5135377645492554,
284
+ "learning_rate": 5.748148148148149e-05,
285
+ "loss": 2.2099,
286
+ "step": 190
287
+ },
288
+ {
289
+ "epoch": 2.533333333333333,
290
+ "eval_loss": 2.5752007961273193,
291
+ "eval_runtime": 43.8521,
292
+ "eval_samples_per_second": 22.804,
293
+ "eval_steps_per_second": 2.85,
294
+ "step": 190
295
+ },
296
+ {
297
+ "epoch": 2.6666666666666665,
298
+ "grad_norm": 1.5297592878341675,
299
+ "learning_rate": 5.62962962962963e-05,
300
+ "loss": 2.2965,
301
+ "step": 200
302
+ },
303
+ {
304
+ "epoch": 2.6666666666666665,
305
+ "eval_loss": 2.579918622970581,
306
+ "eval_runtime": 43.8661,
307
+ "eval_samples_per_second": 22.797,
308
+ "eval_steps_per_second": 2.85,
309
+ "step": 200
310
+ },
311
+ {
312
+ "epoch": 2.8,
313
+ "grad_norm": 1.6282892227172852,
314
+ "learning_rate": 5.511111111111112e-05,
315
+ "loss": 2.2487,
316
+ "step": 210
317
+ },
318
+ {
319
+ "epoch": 2.8,
320
+ "eval_loss": 2.5760037899017334,
321
+ "eval_runtime": 43.8379,
322
+ "eval_samples_per_second": 22.811,
323
+ "eval_steps_per_second": 2.851,
324
+ "step": 210
325
+ },
326
+ {
327
+ "epoch": 2.9333333333333336,
328
+ "grad_norm": 1.74424409866333,
329
+ "learning_rate": 5.392592592592593e-05,
330
+ "loss": 2.2049,
331
+ "step": 220
332
+ },
333
+ {
334
+ "epoch": 2.9333333333333336,
335
+ "eval_loss": 2.576190233230591,
336
+ "eval_runtime": 43.8491,
337
+ "eval_samples_per_second": 22.805,
338
+ "eval_steps_per_second": 2.851,
339
+ "step": 220
340
+ },
341
+ {
342
+ "epoch": 3.066666666666667,
343
+ "grad_norm": 1.654069423675537,
344
+ "learning_rate": 5.274074074074074e-05,
345
+ "loss": 2.1188,
346
+ "step": 230
347
+ },
348
+ {
349
+ "epoch": 3.066666666666667,
350
+ "eval_loss": 2.5971405506134033,
351
+ "eval_runtime": 43.855,
352
+ "eval_samples_per_second": 22.802,
353
+ "eval_steps_per_second": 2.85,
354
+ "step": 230
355
+ },
356
+ {
357
+ "epoch": 3.2,
358
+ "grad_norm": 2.541767120361328,
359
+ "learning_rate": 5.155555555555556e-05,
360
+ "loss": 2.0788,
361
+ "step": 240
362
+ },
363
+ {
364
+ "epoch": 3.2,
365
+ "eval_loss": 2.6767666339874268,
366
+ "eval_runtime": 43.8368,
367
+ "eval_samples_per_second": 22.812,
368
+ "eval_steps_per_second": 2.851,
369
+ "step": 240
370
+ },
371
+ {
372
+ "epoch": 3.3333333333333335,
373
+ "grad_norm": 2.0508077144622803,
374
+ "learning_rate": 5.037037037037037e-05,
375
+ "loss": 2.0784,
376
+ "step": 250
377
+ },
378
+ {
379
+ "epoch": 3.3333333333333335,
380
+ "eval_loss": 2.6486454010009766,
381
+ "eval_runtime": 43.8529,
382
+ "eval_samples_per_second": 22.803,
383
+ "eval_steps_per_second": 2.85,
384
+ "step": 250
385
+ },
386
+ {
387
+ "epoch": 3.466666666666667,
388
+ "grad_norm": 2.1096036434173584,
389
+ "learning_rate": 4.918518518518519e-05,
390
+ "loss": 2.0633,
391
+ "step": 260
392
+ },
393
+ {
394
+ "epoch": 3.466666666666667,
395
+ "eval_loss": 2.6501405239105225,
396
+ "eval_runtime": 43.8632,
397
+ "eval_samples_per_second": 22.798,
398
+ "eval_steps_per_second": 2.85,
399
+ "step": 260
400
+ },
401
+ {
402
+ "epoch": 3.6,
403
+ "grad_norm": 2.3028736114501953,
404
+ "learning_rate": 4.8e-05,
405
+ "loss": 2.0722,
406
+ "step": 270
407
+ },
408
+ {
409
+ "epoch": 3.6,
410
+ "eval_loss": 2.657053232192993,
411
+ "eval_runtime": 43.8423,
412
+ "eval_samples_per_second": 22.809,
413
+ "eval_steps_per_second": 2.851,
414
+ "step": 270
415
+ },
416
+ {
417
+ "epoch": 3.7333333333333334,
418
+ "grad_norm": 2.1536757946014404,
419
+ "learning_rate": 4.681481481481481e-05,
420
+ "loss": 2.0155,
421
+ "step": 280
422
+ },
423
+ {
424
+ "epoch": 3.7333333333333334,
425
+ "eval_loss": 2.648275375366211,
426
+ "eval_runtime": 43.8328,
427
+ "eval_samples_per_second": 22.814,
428
+ "eval_steps_per_second": 2.852,
429
+ "step": 280
430
+ },
431
+ {
432
+ "epoch": 3.8666666666666667,
433
+ "grad_norm": 2.4079270362854004,
434
+ "learning_rate": 4.5629629629629636e-05,
435
+ "loss": 2.1111,
436
+ "step": 290
437
+ },
438
+ {
439
+ "epoch": 3.8666666666666667,
440
+ "eval_loss": 2.650322675704956,
441
+ "eval_runtime": 43.835,
442
+ "eval_samples_per_second": 22.813,
443
+ "eval_steps_per_second": 2.852,
444
+ "step": 290
445
+ },
446
+ {
447
+ "epoch": 4.0,
448
+ "grad_norm": 2.426234722137451,
449
+ "learning_rate": 4.444444444444445e-05,
450
+ "loss": 2.041,
451
+ "step": 300
452
+ },
453
+ {
454
+ "epoch": 4.0,
455
+ "eval_loss": 2.6490862369537354,
456
+ "eval_runtime": 43.845,
457
+ "eval_samples_per_second": 22.808,
458
+ "eval_steps_per_second": 2.851,
459
+ "step": 300
460
+ },
461
+ {
462
+ "epoch": 4.133333333333334,
463
+ "grad_norm": 2.8063745498657227,
464
+ "learning_rate": 4.3259259259259264e-05,
465
+ "loss": 1.9316,
466
+ "step": 310
467
+ },
468
+ {
469
+ "epoch": 4.133333333333334,
470
+ "eval_loss": 2.7609620094299316,
471
+ "eval_runtime": 43.8481,
472
+ "eval_samples_per_second": 22.806,
473
+ "eval_steps_per_second": 2.851,
474
+ "step": 310
475
+ },
476
+ {
477
+ "epoch": 4.266666666666667,
478
+ "grad_norm": 2.96854305267334,
479
+ "learning_rate": 4.2074074074074075e-05,
480
+ "loss": 1.8889,
481
+ "step": 320
482
+ },
483
+ {
484
+ "epoch": 4.266666666666667,
485
+ "eval_loss": 2.736968994140625,
486
+ "eval_runtime": 43.8633,
487
+ "eval_samples_per_second": 22.798,
488
+ "eval_steps_per_second": 2.85,
489
+ "step": 320
490
+ },
491
+ {
492
+ "epoch": 4.4,
493
+ "grad_norm": 2.637695789337158,
494
+ "learning_rate": 4.088888888888889e-05,
495
+ "loss": 1.9187,
496
+ "step": 330
497
+ },
498
+ {
499
+ "epoch": 4.4,
500
+ "eval_loss": 2.7382876873016357,
501
+ "eval_runtime": 43.8486,
502
+ "eval_samples_per_second": 22.806,
503
+ "eval_steps_per_second": 2.851,
504
+ "step": 330
505
+ },
506
+ {
507
+ "epoch": 4.533333333333333,
508
+ "grad_norm": 2.9106290340423584,
509
+ "learning_rate": 3.970370370370371e-05,
510
+ "loss": 1.9002,
511
+ "step": 340
512
+ },
513
+ {
514
+ "epoch": 4.533333333333333,
515
+ "eval_loss": 2.734544515609741,
516
+ "eval_runtime": 43.8491,
517
+ "eval_samples_per_second": 22.805,
518
+ "eval_steps_per_second": 2.851,
519
+ "step": 340
520
+ },
521
+ {
522
+ "epoch": 4.666666666666667,
523
+ "grad_norm": 2.769315481185913,
524
+ "learning_rate": 3.851851851851852e-05,
525
+ "loss": 1.9251,
526
+ "step": 350
527
+ },
528
+ {
529
+ "epoch": 4.666666666666667,
530
+ "eval_loss": 2.734708070755005,
531
+ "eval_runtime": 43.8534,
532
+ "eval_samples_per_second": 22.803,
533
+ "eval_steps_per_second": 2.85,
534
+ "step": 350
535
+ },
536
+ {
537
+ "epoch": 4.8,
538
+ "grad_norm": 2.940281867980957,
539
+ "learning_rate": 3.733333333333334e-05,
540
+ "loss": 1.9319,
541
+ "step": 360
542
+ },
543
+ {
544
+ "epoch": 4.8,
545
+ "eval_loss": 2.7300503253936768,
546
+ "eval_runtime": 43.9017,
547
+ "eval_samples_per_second": 22.778,
548
+ "eval_steps_per_second": 2.847,
549
+ "step": 360
550
+ },
551
+ {
552
+ "epoch": 4.933333333333334,
553
+ "grad_norm": 2.8305609226226807,
554
+ "learning_rate": 3.614814814814815e-05,
555
+ "loss": 1.9332,
556
+ "step": 370
557
+ },
558
+ {
559
+ "epoch": 4.933333333333334,
560
+ "eval_loss": 2.7309281826019287,
561
+ "eval_runtime": 43.8842,
562
+ "eval_samples_per_second": 22.787,
563
+ "eval_steps_per_second": 2.848,
564
+ "step": 370
565
+ },
566
+ {
567
+ "epoch": 5.066666666666666,
568
+ "grad_norm": 2.8739213943481445,
569
+ "learning_rate": 3.4962962962962965e-05,
570
+ "loss": 1.8846,
571
+ "step": 380
572
+ },
573
+ {
574
+ "epoch": 5.066666666666666,
575
+ "eval_loss": 2.76513671875,
576
+ "eval_runtime": 43.906,
577
+ "eval_samples_per_second": 22.776,
578
+ "eval_steps_per_second": 2.847,
579
+ "step": 380
580
+ },
581
+ {
582
+ "epoch": 5.2,
583
+ "grad_norm": 3.9025838375091553,
584
+ "learning_rate": 3.377777777777778e-05,
585
+ "loss": 1.7575,
586
+ "step": 390
587
+ },
588
+ {
589
+ "epoch": 5.2,
590
+ "eval_loss": 2.847782611846924,
591
+ "eval_runtime": 43.8665,
592
+ "eval_samples_per_second": 22.796,
593
+ "eval_steps_per_second": 2.85,
594
+ "step": 390
595
+ },
596
+ {
597
+ "epoch": 5.333333333333333,
598
+ "grad_norm": 3.299649715423584,
599
+ "learning_rate": 3.259259259259259e-05,
600
+ "loss": 1.7713,
601
+ "step": 400
602
+ },
603
+ {
604
+ "epoch": 5.333333333333333,
605
+ "eval_loss": 2.8094286918640137,
606
+ "eval_runtime": 43.8629,
607
+ "eval_samples_per_second": 22.798,
608
+ "eval_steps_per_second": 2.85,
609
+ "step": 400
610
+ },
611
+ {
612
+ "epoch": 5.466666666666667,
613
+ "grad_norm": 3.4474265575408936,
614
+ "learning_rate": 3.140740740740741e-05,
615
+ "loss": 1.7983,
616
+ "step": 410
617
+ },
618
+ {
619
+ "epoch": 5.466666666666667,
620
+ "eval_loss": 2.827517509460449,
621
+ "eval_runtime": 43.8611,
622
+ "eval_samples_per_second": 22.799,
623
+ "eval_steps_per_second": 2.85,
624
+ "step": 410
625
+ },
626
+ {
627
+ "epoch": 5.6,
628
+ "grad_norm": 3.1924540996551514,
629
+ "learning_rate": 3.0222222222222225e-05,
630
+ "loss": 1.8091,
631
+ "step": 420
632
+ },
633
+ {
634
+ "epoch": 5.6,
635
+ "eval_loss": 2.81618332862854,
636
+ "eval_runtime": 43.8544,
637
+ "eval_samples_per_second": 22.803,
638
+ "eval_steps_per_second": 2.85,
639
+ "step": 420
640
+ },
641
+ {
642
+ "epoch": 5.733333333333333,
643
+ "grad_norm": 3.5224015712738037,
644
+ "learning_rate": 2.9037037037037042e-05,
645
+ "loss": 1.8253,
646
+ "step": 430
647
+ },
648
+ {
649
+ "epoch": 5.733333333333333,
650
+ "eval_loss": 2.816711187362671,
651
+ "eval_runtime": 43.8685,
652
+ "eval_samples_per_second": 22.795,
653
+ "eval_steps_per_second": 2.849,
654
+ "step": 430
655
+ },
656
+ {
657
+ "epoch": 5.866666666666667,
658
+ "grad_norm": 3.60918927192688,
659
+ "learning_rate": 2.7851851851851856e-05,
660
+ "loss": 1.8013,
661
+ "step": 440
662
+ },
663
+ {
664
+ "epoch": 5.866666666666667,
665
+ "eval_loss": 2.8146169185638428,
666
+ "eval_runtime": 43.8516,
667
+ "eval_samples_per_second": 22.804,
668
+ "eval_steps_per_second": 2.851,
669
+ "step": 440
670
+ },
671
+ {
672
+ "epoch": 6.0,
673
+ "grad_norm": 3.5798070430755615,
674
+ "learning_rate": 2.6666666666666667e-05,
675
+ "loss": 1.8258,
676
+ "step": 450
677
+ },
678
+ {
679
+ "epoch": 6.0,
680
+ "eval_loss": 2.8134233951568604,
681
+ "eval_runtime": 43.8442,
682
+ "eval_samples_per_second": 22.808,
683
+ "eval_steps_per_second": 2.851,
684
+ "step": 450
685
+ },
686
+ {
687
+ "epoch": 6.133333333333334,
688
+ "grad_norm": 5.563477993011475,
689
+ "learning_rate": 2.5481481481481484e-05,
690
+ "loss": 1.6649,
691
+ "step": 460
692
+ },
693
+ {
694
+ "epoch": 6.133333333333334,
695
+ "eval_loss": 2.9189789295196533,
696
+ "eval_runtime": 43.8602,
697
+ "eval_samples_per_second": 22.8,
698
+ "eval_steps_per_second": 2.85,
699
+ "step": 460
700
+ },
701
+ {
702
+ "epoch": 6.266666666666667,
703
+ "grad_norm": 4.192393779754639,
704
+ "learning_rate": 2.4296296296296298e-05,
705
+ "loss": 1.7443,
706
+ "step": 470
707
+ },
708
+ {
709
+ "epoch": 6.266666666666667,
710
+ "eval_loss": 2.893780469894409,
711
+ "eval_runtime": 43.8434,
712
+ "eval_samples_per_second": 22.808,
713
+ "eval_steps_per_second": 2.851,
714
+ "step": 470
715
+ },
716
+ {
717
+ "epoch": 6.4,
718
+ "grad_norm": 4.8650593757629395,
719
+ "learning_rate": 2.3111111111111112e-05,
720
+ "loss": 1.6961,
721
+ "step": 480
722
+ },
723
+ {
724
+ "epoch": 6.4,
725
+ "eval_loss": 2.8861398696899414,
726
+ "eval_runtime": 43.8417,
727
+ "eval_samples_per_second": 22.809,
728
+ "eval_steps_per_second": 2.851,
729
+ "step": 480
730
+ },
731
+ {
732
+ "epoch": 6.533333333333333,
733
+ "grad_norm": 3.844482660293579,
734
+ "learning_rate": 2.192592592592593e-05,
735
+ "loss": 1.6868,
736
+ "step": 490
737
+ },
738
+ {
739
+ "epoch": 6.533333333333333,
740
+ "eval_loss": 2.900317907333374,
741
+ "eval_runtime": 43.8557,
742
+ "eval_samples_per_second": 22.802,
743
+ "eval_steps_per_second": 2.85,
744
+ "step": 490
745
+ },
746
+ {
747
+ "epoch": 6.666666666666667,
748
+ "grad_norm": 4.230032920837402,
749
+ "learning_rate": 2.074074074074074e-05,
750
+ "loss": 1.6593,
751
+ "step": 500
752
+ },
753
+ {
754
+ "epoch": 6.666666666666667,
755
+ "eval_loss": 2.892076253890991,
756
+ "eval_runtime": 43.8479,
757
+ "eval_samples_per_second": 22.806,
758
+ "eval_steps_per_second": 2.851,
759
+ "step": 500
760
+ },
761
+ {
762
+ "epoch": 6.8,
763
+ "grad_norm": 4.427380561828613,
764
+ "learning_rate": 1.9555555555555557e-05,
765
+ "loss": 1.6777,
766
+ "step": 510
767
+ },
768
+ {
769
+ "epoch": 6.8,
770
+ "eval_loss": 2.8877696990966797,
771
+ "eval_runtime": 43.8489,
772
+ "eval_samples_per_second": 22.806,
773
+ "eval_steps_per_second": 2.851,
774
+ "step": 510
775
+ },
776
+ {
777
+ "epoch": 6.933333333333334,
778
+ "grad_norm": 4.23176908493042,
779
+ "learning_rate": 1.837037037037037e-05,
780
+ "loss": 1.7331,
781
+ "step": 520
782
+ },
783
+ {
784
+ "epoch": 6.933333333333334,
785
+ "eval_loss": 2.889272928237915,
786
+ "eval_runtime": 43.8577,
787
+ "eval_samples_per_second": 22.801,
788
+ "eval_steps_per_second": 2.85,
789
+ "step": 520
790
+ }
791
+ ],
792
+ "logging_steps": 10,
793
+ "max_steps": 675,
794
+ "num_input_tokens_seen": 0,
795
+ "num_train_epochs": 9,
796
+ "save_steps": 10,
797
+ "stateful_callbacks": {
798
+ "TrainerControl": {
799
+ "args": {
800
+ "should_epoch_stop": false,
801
+ "should_evaluate": false,
802
+ "should_log": false,
803
+ "should_save": true,
804
+ "should_training_stop": false
805
+ },
806
+ "attributes": {}
807
+ }
808
+ },
809
+ "total_flos": 8.52075743281152e+16,
810
+ "train_batch_size": 8,
811
+ "trial_name": null,
812
+ "trial_params": null
813
+ }
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-530/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/pythia-6_9b
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-530/adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/workspace/pythia-6_9b",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.1,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 8,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "dense_h_to_4h",
24
+ "query_key_value",
25
+ "dense",
26
+ "dense_4h_to_h"
27
+ ],
28
+ "task_type": "CAUSAL_LM",
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-530/trainer_state.json ADDED
@@ -0,0 +1,828 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 2.535032033920288,
3
+ "best_model_checkpoint": "./output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-150",
4
+ "epoch": 7.066666666666666,
5
+ "eval_steps": 10,
6
+ "global_step": 530,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.13333333333333333,
13
+ "grad_norm": 0.36938729882240295,
14
+ "learning_rate": 7.881481481481482e-05,
15
+ "loss": 2.519,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.13333333333333333,
20
+ "eval_loss": 2.579638957977295,
21
+ "eval_runtime": 43.8215,
22
+ "eval_samples_per_second": 22.82,
23
+ "eval_steps_per_second": 2.852,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.26666666666666666,
28
+ "grad_norm": 0.39850670099258423,
29
+ "learning_rate": 7.762962962962963e-05,
30
+ "loss": 2.5224,
31
+ "step": 20
32
+ },
33
+ {
34
+ "epoch": 0.26666666666666666,
35
+ "eval_loss": 2.5729691982269287,
36
+ "eval_runtime": 43.8179,
37
+ "eval_samples_per_second": 22.822,
38
+ "eval_steps_per_second": 2.853,
39
+ "step": 20
40
+ },
41
+ {
42
+ "epoch": 0.4,
43
+ "grad_norm": 0.40211933851242065,
44
+ "learning_rate": 7.644444444444445e-05,
45
+ "loss": 2.5169,
46
+ "step": 30
47
+ },
48
+ {
49
+ "epoch": 0.4,
50
+ "eval_loss": 2.567735433578491,
51
+ "eval_runtime": 43.8366,
52
+ "eval_samples_per_second": 22.812,
53
+ "eval_steps_per_second": 2.851,
54
+ "step": 30
55
+ },
56
+ {
57
+ "epoch": 0.5333333333333333,
58
+ "grad_norm": 0.6892333030700684,
59
+ "learning_rate": 7.525925925925926e-05,
60
+ "loss": 2.5784,
61
+ "step": 40
62
+ },
63
+ {
64
+ "epoch": 0.5333333333333333,
65
+ "eval_loss": 2.562650442123413,
66
+ "eval_runtime": 43.8377,
67
+ "eval_samples_per_second": 22.811,
68
+ "eval_steps_per_second": 2.851,
69
+ "step": 40
70
+ },
71
+ {
72
+ "epoch": 0.6666666666666666,
73
+ "grad_norm": 0.442343533039093,
74
+ "learning_rate": 7.407407407407409e-05,
75
+ "loss": 2.5431,
76
+ "step": 50
77
+ },
78
+ {
79
+ "epoch": 0.6666666666666666,
80
+ "eval_loss": 2.556513786315918,
81
+ "eval_runtime": 43.8656,
82
+ "eval_samples_per_second": 22.797,
83
+ "eval_steps_per_second": 2.85,
84
+ "step": 50
85
+ },
86
+ {
87
+ "epoch": 0.8,
88
+ "grad_norm": 0.4059845805168152,
89
+ "learning_rate": 7.28888888888889e-05,
90
+ "loss": 2.4936,
91
+ "step": 60
92
+ },
93
+ {
94
+ "epoch": 0.8,
95
+ "eval_loss": 2.552133798599243,
96
+ "eval_runtime": 43.8403,
97
+ "eval_samples_per_second": 22.81,
98
+ "eval_steps_per_second": 2.851,
99
+ "step": 60
100
+ },
101
+ {
102
+ "epoch": 0.9333333333333333,
103
+ "grad_norm": 0.48126307129859924,
104
+ "learning_rate": 7.170370370370371e-05,
105
+ "loss": 2.4901,
106
+ "step": 70
107
+ },
108
+ {
109
+ "epoch": 0.9333333333333333,
110
+ "eval_loss": 2.5477023124694824,
111
+ "eval_runtime": 43.8351,
112
+ "eval_samples_per_second": 22.813,
113
+ "eval_steps_per_second": 2.852,
114
+ "step": 70
115
+ },
116
+ {
117
+ "epoch": 1.0666666666666667,
118
+ "grad_norm": 0.48629865050315857,
119
+ "learning_rate": 7.051851851851853e-05,
120
+ "loss": 2.5114,
121
+ "step": 80
122
+ },
123
+ {
124
+ "epoch": 1.0666666666666667,
125
+ "eval_loss": 2.543431043624878,
126
+ "eval_runtime": 43.8432,
127
+ "eval_samples_per_second": 22.809,
128
+ "eval_steps_per_second": 2.851,
129
+ "step": 80
130
+ },
131
+ {
132
+ "epoch": 1.2,
133
+ "grad_norm": 0.5880796313285828,
134
+ "learning_rate": 6.933333333333334e-05,
135
+ "loss": 2.4446,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 1.2,
140
+ "eval_loss": 2.544339418411255,
141
+ "eval_runtime": 43.8437,
142
+ "eval_samples_per_second": 22.808,
143
+ "eval_steps_per_second": 2.851,
144
+ "step": 90
145
+ },
146
+ {
147
+ "epoch": 1.3333333333333333,
148
+ "grad_norm": 0.6746829748153687,
149
+ "learning_rate": 6.814814814814815e-05,
150
+ "loss": 2.4477,
151
+ "step": 100
152
+ },
153
+ {
154
+ "epoch": 1.3333333333333333,
155
+ "eval_loss": 2.544358968734741,
156
+ "eval_runtime": 43.8613,
157
+ "eval_samples_per_second": 22.799,
158
+ "eval_steps_per_second": 2.85,
159
+ "step": 100
160
+ },
161
+ {
162
+ "epoch": 1.4666666666666668,
163
+ "grad_norm": 0.8208937048912048,
164
+ "learning_rate": 6.696296296296296e-05,
165
+ "loss": 2.4004,
166
+ "step": 110
167
+ },
168
+ {
169
+ "epoch": 1.4666666666666668,
170
+ "eval_loss": 2.54068660736084,
171
+ "eval_runtime": 43.8426,
172
+ "eval_samples_per_second": 22.809,
173
+ "eval_steps_per_second": 2.851,
174
+ "step": 110
175
+ },
176
+ {
177
+ "epoch": 1.6,
178
+ "grad_norm": 0.925931453704834,
179
+ "learning_rate": 6.577777777777777e-05,
180
+ "loss": 2.3889,
181
+ "step": 120
182
+ },
183
+ {
184
+ "epoch": 1.6,
185
+ "eval_loss": 2.5393033027648926,
186
+ "eval_runtime": 43.8383,
187
+ "eval_samples_per_second": 22.811,
188
+ "eval_steps_per_second": 2.851,
189
+ "step": 120
190
+ },
191
+ {
192
+ "epoch": 1.7333333333333334,
193
+ "grad_norm": 0.8785662055015564,
194
+ "learning_rate": 6.45925925925926e-05,
195
+ "loss": 2.3959,
196
+ "step": 130
197
+ },
198
+ {
199
+ "epoch": 1.7333333333333334,
200
+ "eval_loss": 2.5367038249969482,
201
+ "eval_runtime": 43.8508,
202
+ "eval_samples_per_second": 22.805,
203
+ "eval_steps_per_second": 2.851,
204
+ "step": 130
205
+ },
206
+ {
207
+ "epoch": 1.8666666666666667,
208
+ "grad_norm": 0.941368818283081,
209
+ "learning_rate": 6.340740740740741e-05,
210
+ "loss": 2.3924,
211
+ "step": 140
212
+ },
213
+ {
214
+ "epoch": 1.8666666666666667,
215
+ "eval_loss": 2.535139560699463,
216
+ "eval_runtime": 43.8588,
217
+ "eval_samples_per_second": 22.8,
218
+ "eval_steps_per_second": 2.85,
219
+ "step": 140
220
+ },
221
+ {
222
+ "epoch": 2.0,
223
+ "grad_norm": 0.9578835368156433,
224
+ "learning_rate": 6.222222222222223e-05,
225
+ "loss": 2.4278,
226
+ "step": 150
227
+ },
228
+ {
229
+ "epoch": 2.0,
230
+ "eval_loss": 2.535032033920288,
231
+ "eval_runtime": 43.8484,
232
+ "eval_samples_per_second": 22.806,
233
+ "eval_steps_per_second": 2.851,
234
+ "step": 150
235
+ },
236
+ {
237
+ "epoch": 2.1333333333333333,
238
+ "grad_norm": 1.1541856527328491,
239
+ "learning_rate": 6.103703703703704e-05,
240
+ "loss": 2.2895,
241
+ "step": 160
242
+ },
243
+ {
244
+ "epoch": 2.1333333333333333,
245
+ "eval_loss": 2.564768075942993,
246
+ "eval_runtime": 43.8568,
247
+ "eval_samples_per_second": 22.801,
248
+ "eval_steps_per_second": 2.85,
249
+ "step": 160
250
+ },
251
+ {
252
+ "epoch": 2.2666666666666666,
253
+ "grad_norm": 1.4076604843139648,
254
+ "learning_rate": 5.9851851851851855e-05,
255
+ "loss": 2.2107,
256
+ "step": 170
257
+ },
258
+ {
259
+ "epoch": 2.2666666666666666,
260
+ "eval_loss": 2.5832314491271973,
261
+ "eval_runtime": 43.8455,
262
+ "eval_samples_per_second": 22.807,
263
+ "eval_steps_per_second": 2.851,
264
+ "step": 170
265
+ },
266
+ {
267
+ "epoch": 2.4,
268
+ "grad_norm": 1.4847813844680786,
269
+ "learning_rate": 5.8666666666666665e-05,
270
+ "loss": 2.2588,
271
+ "step": 180
272
+ },
273
+ {
274
+ "epoch": 2.4,
275
+ "eval_loss": 2.5781586170196533,
276
+ "eval_runtime": 43.8578,
277
+ "eval_samples_per_second": 22.801,
278
+ "eval_steps_per_second": 2.85,
279
+ "step": 180
280
+ },
281
+ {
282
+ "epoch": 2.533333333333333,
283
+ "grad_norm": 1.5135377645492554,
284
+ "learning_rate": 5.748148148148149e-05,
285
+ "loss": 2.2099,
286
+ "step": 190
287
+ },
288
+ {
289
+ "epoch": 2.533333333333333,
290
+ "eval_loss": 2.5752007961273193,
291
+ "eval_runtime": 43.8521,
292
+ "eval_samples_per_second": 22.804,
293
+ "eval_steps_per_second": 2.85,
294
+ "step": 190
295
+ },
296
+ {
297
+ "epoch": 2.6666666666666665,
298
+ "grad_norm": 1.5297592878341675,
299
+ "learning_rate": 5.62962962962963e-05,
300
+ "loss": 2.2965,
301
+ "step": 200
302
+ },
303
+ {
304
+ "epoch": 2.6666666666666665,
305
+ "eval_loss": 2.579918622970581,
306
+ "eval_runtime": 43.8661,
307
+ "eval_samples_per_second": 22.797,
308
+ "eval_steps_per_second": 2.85,
309
+ "step": 200
310
+ },
311
+ {
312
+ "epoch": 2.8,
313
+ "grad_norm": 1.6282892227172852,
314
+ "learning_rate": 5.511111111111112e-05,
315
+ "loss": 2.2487,
316
+ "step": 210
317
+ },
318
+ {
319
+ "epoch": 2.8,
320
+ "eval_loss": 2.5760037899017334,
321
+ "eval_runtime": 43.8379,
322
+ "eval_samples_per_second": 22.811,
323
+ "eval_steps_per_second": 2.851,
324
+ "step": 210
325
+ },
326
+ {
327
+ "epoch": 2.9333333333333336,
328
+ "grad_norm": 1.74424409866333,
329
+ "learning_rate": 5.392592592592593e-05,
330
+ "loss": 2.2049,
331
+ "step": 220
332
+ },
333
+ {
334
+ "epoch": 2.9333333333333336,
335
+ "eval_loss": 2.576190233230591,
336
+ "eval_runtime": 43.8491,
337
+ "eval_samples_per_second": 22.805,
338
+ "eval_steps_per_second": 2.851,
339
+ "step": 220
340
+ },
341
+ {
342
+ "epoch": 3.066666666666667,
343
+ "grad_norm": 1.654069423675537,
344
+ "learning_rate": 5.274074074074074e-05,
345
+ "loss": 2.1188,
346
+ "step": 230
347
+ },
348
+ {
349
+ "epoch": 3.066666666666667,
350
+ "eval_loss": 2.5971405506134033,
351
+ "eval_runtime": 43.855,
352
+ "eval_samples_per_second": 22.802,
353
+ "eval_steps_per_second": 2.85,
354
+ "step": 230
355
+ },
356
+ {
357
+ "epoch": 3.2,
358
+ "grad_norm": 2.541767120361328,
359
+ "learning_rate": 5.155555555555556e-05,
360
+ "loss": 2.0788,
361
+ "step": 240
362
+ },
363
+ {
364
+ "epoch": 3.2,
365
+ "eval_loss": 2.6767666339874268,
366
+ "eval_runtime": 43.8368,
367
+ "eval_samples_per_second": 22.812,
368
+ "eval_steps_per_second": 2.851,
369
+ "step": 240
370
+ },
371
+ {
372
+ "epoch": 3.3333333333333335,
373
+ "grad_norm": 2.0508077144622803,
374
+ "learning_rate": 5.037037037037037e-05,
375
+ "loss": 2.0784,
376
+ "step": 250
377
+ },
378
+ {
379
+ "epoch": 3.3333333333333335,
380
+ "eval_loss": 2.6486454010009766,
381
+ "eval_runtime": 43.8529,
382
+ "eval_samples_per_second": 22.803,
383
+ "eval_steps_per_second": 2.85,
384
+ "step": 250
385
+ },
386
+ {
387
+ "epoch": 3.466666666666667,
388
+ "grad_norm": 2.1096036434173584,
389
+ "learning_rate": 4.918518518518519e-05,
390
+ "loss": 2.0633,
391
+ "step": 260
392
+ },
393
+ {
394
+ "epoch": 3.466666666666667,
395
+ "eval_loss": 2.6501405239105225,
396
+ "eval_runtime": 43.8632,
397
+ "eval_samples_per_second": 22.798,
398
+ "eval_steps_per_second": 2.85,
399
+ "step": 260
400
+ },
401
+ {
402
+ "epoch": 3.6,
403
+ "grad_norm": 2.3028736114501953,
404
+ "learning_rate": 4.8e-05,
405
+ "loss": 2.0722,
406
+ "step": 270
407
+ },
408
+ {
409
+ "epoch": 3.6,
410
+ "eval_loss": 2.657053232192993,
411
+ "eval_runtime": 43.8423,
412
+ "eval_samples_per_second": 22.809,
413
+ "eval_steps_per_second": 2.851,
414
+ "step": 270
415
+ },
416
+ {
417
+ "epoch": 3.7333333333333334,
418
+ "grad_norm": 2.1536757946014404,
419
+ "learning_rate": 4.681481481481481e-05,
420
+ "loss": 2.0155,
421
+ "step": 280
422
+ },
423
+ {
424
+ "epoch": 3.7333333333333334,
425
+ "eval_loss": 2.648275375366211,
426
+ "eval_runtime": 43.8328,
427
+ "eval_samples_per_second": 22.814,
428
+ "eval_steps_per_second": 2.852,
429
+ "step": 280
430
+ },
431
+ {
432
+ "epoch": 3.8666666666666667,
433
+ "grad_norm": 2.4079270362854004,
434
+ "learning_rate": 4.5629629629629636e-05,
435
+ "loss": 2.1111,
436
+ "step": 290
437
+ },
438
+ {
439
+ "epoch": 3.8666666666666667,
440
+ "eval_loss": 2.650322675704956,
441
+ "eval_runtime": 43.835,
442
+ "eval_samples_per_second": 22.813,
443
+ "eval_steps_per_second": 2.852,
444
+ "step": 290
445
+ },
446
+ {
447
+ "epoch": 4.0,
448
+ "grad_norm": 2.426234722137451,
449
+ "learning_rate": 4.444444444444445e-05,
450
+ "loss": 2.041,
451
+ "step": 300
452
+ },
453
+ {
454
+ "epoch": 4.0,
455
+ "eval_loss": 2.6490862369537354,
456
+ "eval_runtime": 43.845,
457
+ "eval_samples_per_second": 22.808,
458
+ "eval_steps_per_second": 2.851,
459
+ "step": 300
460
+ },
461
+ {
462
+ "epoch": 4.133333333333334,
463
+ "grad_norm": 2.8063745498657227,
464
+ "learning_rate": 4.3259259259259264e-05,
465
+ "loss": 1.9316,
466
+ "step": 310
467
+ },
468
+ {
469
+ "epoch": 4.133333333333334,
470
+ "eval_loss": 2.7609620094299316,
471
+ "eval_runtime": 43.8481,
472
+ "eval_samples_per_second": 22.806,
473
+ "eval_steps_per_second": 2.851,
474
+ "step": 310
475
+ },
476
+ {
477
+ "epoch": 4.266666666666667,
478
+ "grad_norm": 2.96854305267334,
479
+ "learning_rate": 4.2074074074074075e-05,
480
+ "loss": 1.8889,
481
+ "step": 320
482
+ },
483
+ {
484
+ "epoch": 4.266666666666667,
485
+ "eval_loss": 2.736968994140625,
486
+ "eval_runtime": 43.8633,
487
+ "eval_samples_per_second": 22.798,
488
+ "eval_steps_per_second": 2.85,
489
+ "step": 320
490
+ },
491
+ {
492
+ "epoch": 4.4,
493
+ "grad_norm": 2.637695789337158,
494
+ "learning_rate": 4.088888888888889e-05,
495
+ "loss": 1.9187,
496
+ "step": 330
497
+ },
498
+ {
499
+ "epoch": 4.4,
500
+ "eval_loss": 2.7382876873016357,
501
+ "eval_runtime": 43.8486,
502
+ "eval_samples_per_second": 22.806,
503
+ "eval_steps_per_second": 2.851,
504
+ "step": 330
505
+ },
506
+ {
507
+ "epoch": 4.533333333333333,
508
+ "grad_norm": 2.9106290340423584,
509
+ "learning_rate": 3.970370370370371e-05,
510
+ "loss": 1.9002,
511
+ "step": 340
512
+ },
513
+ {
514
+ "epoch": 4.533333333333333,
515
+ "eval_loss": 2.734544515609741,
516
+ "eval_runtime": 43.8491,
517
+ "eval_samples_per_second": 22.805,
518
+ "eval_steps_per_second": 2.851,
519
+ "step": 340
520
+ },
521
+ {
522
+ "epoch": 4.666666666666667,
523
+ "grad_norm": 2.769315481185913,
524
+ "learning_rate": 3.851851851851852e-05,
525
+ "loss": 1.9251,
526
+ "step": 350
527
+ },
528
+ {
529
+ "epoch": 4.666666666666667,
530
+ "eval_loss": 2.734708070755005,
531
+ "eval_runtime": 43.8534,
532
+ "eval_samples_per_second": 22.803,
533
+ "eval_steps_per_second": 2.85,
534
+ "step": 350
535
+ },
536
+ {
537
+ "epoch": 4.8,
538
+ "grad_norm": 2.940281867980957,
539
+ "learning_rate": 3.733333333333334e-05,
540
+ "loss": 1.9319,
541
+ "step": 360
542
+ },
543
+ {
544
+ "epoch": 4.8,
545
+ "eval_loss": 2.7300503253936768,
546
+ "eval_runtime": 43.9017,
547
+ "eval_samples_per_second": 22.778,
548
+ "eval_steps_per_second": 2.847,
549
+ "step": 360
550
+ },
551
+ {
552
+ "epoch": 4.933333333333334,
553
+ "grad_norm": 2.8305609226226807,
554
+ "learning_rate": 3.614814814814815e-05,
555
+ "loss": 1.9332,
556
+ "step": 370
557
+ },
558
+ {
559
+ "epoch": 4.933333333333334,
560
+ "eval_loss": 2.7309281826019287,
561
+ "eval_runtime": 43.8842,
562
+ "eval_samples_per_second": 22.787,
563
+ "eval_steps_per_second": 2.848,
564
+ "step": 370
565
+ },
566
+ {
567
+ "epoch": 5.066666666666666,
568
+ "grad_norm": 2.8739213943481445,
569
+ "learning_rate": 3.4962962962962965e-05,
570
+ "loss": 1.8846,
571
+ "step": 380
572
+ },
573
+ {
574
+ "epoch": 5.066666666666666,
575
+ "eval_loss": 2.76513671875,
576
+ "eval_runtime": 43.906,
577
+ "eval_samples_per_second": 22.776,
578
+ "eval_steps_per_second": 2.847,
579
+ "step": 380
580
+ },
581
+ {
582
+ "epoch": 5.2,
583
+ "grad_norm": 3.9025838375091553,
584
+ "learning_rate": 3.377777777777778e-05,
585
+ "loss": 1.7575,
586
+ "step": 390
587
+ },
588
+ {
589
+ "epoch": 5.2,
590
+ "eval_loss": 2.847782611846924,
591
+ "eval_runtime": 43.8665,
592
+ "eval_samples_per_second": 22.796,
593
+ "eval_steps_per_second": 2.85,
594
+ "step": 390
595
+ },
596
+ {
597
+ "epoch": 5.333333333333333,
598
+ "grad_norm": 3.299649715423584,
599
+ "learning_rate": 3.259259259259259e-05,
600
+ "loss": 1.7713,
601
+ "step": 400
602
+ },
603
+ {
604
+ "epoch": 5.333333333333333,
605
+ "eval_loss": 2.8094286918640137,
606
+ "eval_runtime": 43.8629,
607
+ "eval_samples_per_second": 22.798,
608
+ "eval_steps_per_second": 2.85,
609
+ "step": 400
610
+ },
611
+ {
612
+ "epoch": 5.466666666666667,
613
+ "grad_norm": 3.4474265575408936,
614
+ "learning_rate": 3.140740740740741e-05,
615
+ "loss": 1.7983,
616
+ "step": 410
617
+ },
618
+ {
619
+ "epoch": 5.466666666666667,
620
+ "eval_loss": 2.827517509460449,
621
+ "eval_runtime": 43.8611,
622
+ "eval_samples_per_second": 22.799,
623
+ "eval_steps_per_second": 2.85,
624
+ "step": 410
625
+ },
626
+ {
627
+ "epoch": 5.6,
628
+ "grad_norm": 3.1924540996551514,
629
+ "learning_rate": 3.0222222222222225e-05,
630
+ "loss": 1.8091,
631
+ "step": 420
632
+ },
633
+ {
634
+ "epoch": 5.6,
635
+ "eval_loss": 2.81618332862854,
636
+ "eval_runtime": 43.8544,
637
+ "eval_samples_per_second": 22.803,
638
+ "eval_steps_per_second": 2.85,
639
+ "step": 420
640
+ },
641
+ {
642
+ "epoch": 5.733333333333333,
643
+ "grad_norm": 3.5224015712738037,
644
+ "learning_rate": 2.9037037037037042e-05,
645
+ "loss": 1.8253,
646
+ "step": 430
647
+ },
648
+ {
649
+ "epoch": 5.733333333333333,
650
+ "eval_loss": 2.816711187362671,
651
+ "eval_runtime": 43.8685,
652
+ "eval_samples_per_second": 22.795,
653
+ "eval_steps_per_second": 2.849,
654
+ "step": 430
655
+ },
656
+ {
657
+ "epoch": 5.866666666666667,
658
+ "grad_norm": 3.60918927192688,
659
+ "learning_rate": 2.7851851851851856e-05,
660
+ "loss": 1.8013,
661
+ "step": 440
662
+ },
663
+ {
664
+ "epoch": 5.866666666666667,
665
+ "eval_loss": 2.8146169185638428,
666
+ "eval_runtime": 43.8516,
667
+ "eval_samples_per_second": 22.804,
668
+ "eval_steps_per_second": 2.851,
669
+ "step": 440
670
+ },
671
+ {
672
+ "epoch": 6.0,
673
+ "grad_norm": 3.5798070430755615,
674
+ "learning_rate": 2.6666666666666667e-05,
675
+ "loss": 1.8258,
676
+ "step": 450
677
+ },
678
+ {
679
+ "epoch": 6.0,
680
+ "eval_loss": 2.8134233951568604,
681
+ "eval_runtime": 43.8442,
682
+ "eval_samples_per_second": 22.808,
683
+ "eval_steps_per_second": 2.851,
684
+ "step": 450
685
+ },
686
+ {
687
+ "epoch": 6.133333333333334,
688
+ "grad_norm": 5.563477993011475,
689
+ "learning_rate": 2.5481481481481484e-05,
690
+ "loss": 1.6649,
691
+ "step": 460
692
+ },
693
+ {
694
+ "epoch": 6.133333333333334,
695
+ "eval_loss": 2.9189789295196533,
696
+ "eval_runtime": 43.8602,
697
+ "eval_samples_per_second": 22.8,
698
+ "eval_steps_per_second": 2.85,
699
+ "step": 460
700
+ },
701
+ {
702
+ "epoch": 6.266666666666667,
703
+ "grad_norm": 4.192393779754639,
704
+ "learning_rate": 2.4296296296296298e-05,
705
+ "loss": 1.7443,
706
+ "step": 470
707
+ },
708
+ {
709
+ "epoch": 6.266666666666667,
710
+ "eval_loss": 2.893780469894409,
711
+ "eval_runtime": 43.8434,
712
+ "eval_samples_per_second": 22.808,
713
+ "eval_steps_per_second": 2.851,
714
+ "step": 470
715
+ },
716
+ {
717
+ "epoch": 6.4,
718
+ "grad_norm": 4.8650593757629395,
719
+ "learning_rate": 2.3111111111111112e-05,
720
+ "loss": 1.6961,
721
+ "step": 480
722
+ },
723
+ {
724
+ "epoch": 6.4,
725
+ "eval_loss": 2.8861398696899414,
726
+ "eval_runtime": 43.8417,
727
+ "eval_samples_per_second": 22.809,
728
+ "eval_steps_per_second": 2.851,
729
+ "step": 480
730
+ },
731
+ {
732
+ "epoch": 6.533333333333333,
733
+ "grad_norm": 3.844482660293579,
734
+ "learning_rate": 2.192592592592593e-05,
735
+ "loss": 1.6868,
736
+ "step": 490
737
+ },
738
+ {
739
+ "epoch": 6.533333333333333,
740
+ "eval_loss": 2.900317907333374,
741
+ "eval_runtime": 43.8557,
742
+ "eval_samples_per_second": 22.802,
743
+ "eval_steps_per_second": 2.85,
744
+ "step": 490
745
+ },
746
+ {
747
+ "epoch": 6.666666666666667,
748
+ "grad_norm": 4.230032920837402,
749
+ "learning_rate": 2.074074074074074e-05,
750
+ "loss": 1.6593,
751
+ "step": 500
752
+ },
753
+ {
754
+ "epoch": 6.666666666666667,
755
+ "eval_loss": 2.892076253890991,
756
+ "eval_runtime": 43.8479,
757
+ "eval_samples_per_second": 22.806,
758
+ "eval_steps_per_second": 2.851,
759
+ "step": 500
760
+ },
761
+ {
762
+ "epoch": 6.8,
763
+ "grad_norm": 4.427380561828613,
764
+ "learning_rate": 1.9555555555555557e-05,
765
+ "loss": 1.6777,
766
+ "step": 510
767
+ },
768
+ {
769
+ "epoch": 6.8,
770
+ "eval_loss": 2.8877696990966797,
771
+ "eval_runtime": 43.8489,
772
+ "eval_samples_per_second": 22.806,
773
+ "eval_steps_per_second": 2.851,
774
+ "step": 510
775
+ },
776
+ {
777
+ "epoch": 6.933333333333334,
778
+ "grad_norm": 4.23176908493042,
779
+ "learning_rate": 1.837037037037037e-05,
780
+ "loss": 1.7331,
781
+ "step": 520
782
+ },
783
+ {
784
+ "epoch": 6.933333333333334,
785
+ "eval_loss": 2.889272928237915,
786
+ "eval_runtime": 43.8577,
787
+ "eval_samples_per_second": 22.801,
788
+ "eval_steps_per_second": 2.85,
789
+ "step": 520
790
+ },
791
+ {
792
+ "epoch": 7.066666666666666,
793
+ "grad_norm": 3.9098429679870605,
794
+ "learning_rate": 1.7185185185185185e-05,
795
+ "loss": 1.6741,
796
+ "step": 530
797
+ },
798
+ {
799
+ "epoch": 7.066666666666666,
800
+ "eval_loss": 2.9202494621276855,
801
+ "eval_runtime": 43.8571,
802
+ "eval_samples_per_second": 22.801,
803
+ "eval_steps_per_second": 2.85,
804
+ "step": 530
805
+ }
806
+ ],
807
+ "logging_steps": 10,
808
+ "max_steps": 675,
809
+ "num_input_tokens_seen": 0,
810
+ "num_train_epochs": 9,
811
+ "save_steps": 10,
812
+ "stateful_callbacks": {
813
+ "TrainerControl": {
814
+ "args": {
815
+ "should_epoch_stop": false,
816
+ "should_evaluate": false,
817
+ "should_log": false,
818
+ "should_save": true,
819
+ "should_training_stop": false
820
+ },
821
+ "attributes": {}
822
+ }
823
+ },
824
+ "total_flos": 8.68461815267328e+16,
825
+ "train_batch_size": 8,
826
+ "trial_name": null,
827
+ "trial_params": null
828
+ }
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-540/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/pythia-6_9b
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-540/adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/workspace/pythia-6_9b",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.1,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 8,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "dense_h_to_4h",
24
+ "query_key_value",
25
+ "dense",
26
+ "dense_4h_to_h"
27
+ ],
28
+ "task_type": "CAUSAL_LM",
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-540/trainer_state.json ADDED
@@ -0,0 +1,843 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 2.535032033920288,
3
+ "best_model_checkpoint": "./output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-150",
4
+ "epoch": 7.2,
5
+ "eval_steps": 10,
6
+ "global_step": 540,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.13333333333333333,
13
+ "grad_norm": 0.36938729882240295,
14
+ "learning_rate": 7.881481481481482e-05,
15
+ "loss": 2.519,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.13333333333333333,
20
+ "eval_loss": 2.579638957977295,
21
+ "eval_runtime": 43.8215,
22
+ "eval_samples_per_second": 22.82,
23
+ "eval_steps_per_second": 2.852,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.26666666666666666,
28
+ "grad_norm": 0.39850670099258423,
29
+ "learning_rate": 7.762962962962963e-05,
30
+ "loss": 2.5224,
31
+ "step": 20
32
+ },
33
+ {
34
+ "epoch": 0.26666666666666666,
35
+ "eval_loss": 2.5729691982269287,
36
+ "eval_runtime": 43.8179,
37
+ "eval_samples_per_second": 22.822,
38
+ "eval_steps_per_second": 2.853,
39
+ "step": 20
40
+ },
41
+ {
42
+ "epoch": 0.4,
43
+ "grad_norm": 0.40211933851242065,
44
+ "learning_rate": 7.644444444444445e-05,
45
+ "loss": 2.5169,
46
+ "step": 30
47
+ },
48
+ {
49
+ "epoch": 0.4,
50
+ "eval_loss": 2.567735433578491,
51
+ "eval_runtime": 43.8366,
52
+ "eval_samples_per_second": 22.812,
53
+ "eval_steps_per_second": 2.851,
54
+ "step": 30
55
+ },
56
+ {
57
+ "epoch": 0.5333333333333333,
58
+ "grad_norm": 0.6892333030700684,
59
+ "learning_rate": 7.525925925925926e-05,
60
+ "loss": 2.5784,
61
+ "step": 40
62
+ },
63
+ {
64
+ "epoch": 0.5333333333333333,
65
+ "eval_loss": 2.562650442123413,
66
+ "eval_runtime": 43.8377,
67
+ "eval_samples_per_second": 22.811,
68
+ "eval_steps_per_second": 2.851,
69
+ "step": 40
70
+ },
71
+ {
72
+ "epoch": 0.6666666666666666,
73
+ "grad_norm": 0.442343533039093,
74
+ "learning_rate": 7.407407407407409e-05,
75
+ "loss": 2.5431,
76
+ "step": 50
77
+ },
78
+ {
79
+ "epoch": 0.6666666666666666,
80
+ "eval_loss": 2.556513786315918,
81
+ "eval_runtime": 43.8656,
82
+ "eval_samples_per_second": 22.797,
83
+ "eval_steps_per_second": 2.85,
84
+ "step": 50
85
+ },
86
+ {
87
+ "epoch": 0.8,
88
+ "grad_norm": 0.4059845805168152,
89
+ "learning_rate": 7.28888888888889e-05,
90
+ "loss": 2.4936,
91
+ "step": 60
92
+ },
93
+ {
94
+ "epoch": 0.8,
95
+ "eval_loss": 2.552133798599243,
96
+ "eval_runtime": 43.8403,
97
+ "eval_samples_per_second": 22.81,
98
+ "eval_steps_per_second": 2.851,
99
+ "step": 60
100
+ },
101
+ {
102
+ "epoch": 0.9333333333333333,
103
+ "grad_norm": 0.48126307129859924,
104
+ "learning_rate": 7.170370370370371e-05,
105
+ "loss": 2.4901,
106
+ "step": 70
107
+ },
108
+ {
109
+ "epoch": 0.9333333333333333,
110
+ "eval_loss": 2.5477023124694824,
111
+ "eval_runtime": 43.8351,
112
+ "eval_samples_per_second": 22.813,
113
+ "eval_steps_per_second": 2.852,
114
+ "step": 70
115
+ },
116
+ {
117
+ "epoch": 1.0666666666666667,
118
+ "grad_norm": 0.48629865050315857,
119
+ "learning_rate": 7.051851851851853e-05,
120
+ "loss": 2.5114,
121
+ "step": 80
122
+ },
123
+ {
124
+ "epoch": 1.0666666666666667,
125
+ "eval_loss": 2.543431043624878,
126
+ "eval_runtime": 43.8432,
127
+ "eval_samples_per_second": 22.809,
128
+ "eval_steps_per_second": 2.851,
129
+ "step": 80
130
+ },
131
+ {
132
+ "epoch": 1.2,
133
+ "grad_norm": 0.5880796313285828,
134
+ "learning_rate": 6.933333333333334e-05,
135
+ "loss": 2.4446,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 1.2,
140
+ "eval_loss": 2.544339418411255,
141
+ "eval_runtime": 43.8437,
142
+ "eval_samples_per_second": 22.808,
143
+ "eval_steps_per_second": 2.851,
144
+ "step": 90
145
+ },
146
+ {
147
+ "epoch": 1.3333333333333333,
148
+ "grad_norm": 0.6746829748153687,
149
+ "learning_rate": 6.814814814814815e-05,
150
+ "loss": 2.4477,
151
+ "step": 100
152
+ },
153
+ {
154
+ "epoch": 1.3333333333333333,
155
+ "eval_loss": 2.544358968734741,
156
+ "eval_runtime": 43.8613,
157
+ "eval_samples_per_second": 22.799,
158
+ "eval_steps_per_second": 2.85,
159
+ "step": 100
160
+ },
161
+ {
162
+ "epoch": 1.4666666666666668,
163
+ "grad_norm": 0.8208937048912048,
164
+ "learning_rate": 6.696296296296296e-05,
165
+ "loss": 2.4004,
166
+ "step": 110
167
+ },
168
+ {
169
+ "epoch": 1.4666666666666668,
170
+ "eval_loss": 2.54068660736084,
171
+ "eval_runtime": 43.8426,
172
+ "eval_samples_per_second": 22.809,
173
+ "eval_steps_per_second": 2.851,
174
+ "step": 110
175
+ },
176
+ {
177
+ "epoch": 1.6,
178
+ "grad_norm": 0.925931453704834,
179
+ "learning_rate": 6.577777777777777e-05,
180
+ "loss": 2.3889,
181
+ "step": 120
182
+ },
183
+ {
184
+ "epoch": 1.6,
185
+ "eval_loss": 2.5393033027648926,
186
+ "eval_runtime": 43.8383,
187
+ "eval_samples_per_second": 22.811,
188
+ "eval_steps_per_second": 2.851,
189
+ "step": 120
190
+ },
191
+ {
192
+ "epoch": 1.7333333333333334,
193
+ "grad_norm": 0.8785662055015564,
194
+ "learning_rate": 6.45925925925926e-05,
195
+ "loss": 2.3959,
196
+ "step": 130
197
+ },
198
+ {
199
+ "epoch": 1.7333333333333334,
200
+ "eval_loss": 2.5367038249969482,
201
+ "eval_runtime": 43.8508,
202
+ "eval_samples_per_second": 22.805,
203
+ "eval_steps_per_second": 2.851,
204
+ "step": 130
205
+ },
206
+ {
207
+ "epoch": 1.8666666666666667,
208
+ "grad_norm": 0.941368818283081,
209
+ "learning_rate": 6.340740740740741e-05,
210
+ "loss": 2.3924,
211
+ "step": 140
212
+ },
213
+ {
214
+ "epoch": 1.8666666666666667,
215
+ "eval_loss": 2.535139560699463,
216
+ "eval_runtime": 43.8588,
217
+ "eval_samples_per_second": 22.8,
218
+ "eval_steps_per_second": 2.85,
219
+ "step": 140
220
+ },
221
+ {
222
+ "epoch": 2.0,
223
+ "grad_norm": 0.9578835368156433,
224
+ "learning_rate": 6.222222222222223e-05,
225
+ "loss": 2.4278,
226
+ "step": 150
227
+ },
228
+ {
229
+ "epoch": 2.0,
230
+ "eval_loss": 2.535032033920288,
231
+ "eval_runtime": 43.8484,
232
+ "eval_samples_per_second": 22.806,
233
+ "eval_steps_per_second": 2.851,
234
+ "step": 150
235
+ },
236
+ {
237
+ "epoch": 2.1333333333333333,
238
+ "grad_norm": 1.1541856527328491,
239
+ "learning_rate": 6.103703703703704e-05,
240
+ "loss": 2.2895,
241
+ "step": 160
242
+ },
243
+ {
244
+ "epoch": 2.1333333333333333,
245
+ "eval_loss": 2.564768075942993,
246
+ "eval_runtime": 43.8568,
247
+ "eval_samples_per_second": 22.801,
248
+ "eval_steps_per_second": 2.85,
249
+ "step": 160
250
+ },
251
+ {
252
+ "epoch": 2.2666666666666666,
253
+ "grad_norm": 1.4076604843139648,
254
+ "learning_rate": 5.9851851851851855e-05,
255
+ "loss": 2.2107,
256
+ "step": 170
257
+ },
258
+ {
259
+ "epoch": 2.2666666666666666,
260
+ "eval_loss": 2.5832314491271973,
261
+ "eval_runtime": 43.8455,
262
+ "eval_samples_per_second": 22.807,
263
+ "eval_steps_per_second": 2.851,
264
+ "step": 170
265
+ },
266
+ {
267
+ "epoch": 2.4,
268
+ "grad_norm": 1.4847813844680786,
269
+ "learning_rate": 5.8666666666666665e-05,
270
+ "loss": 2.2588,
271
+ "step": 180
272
+ },
273
+ {
274
+ "epoch": 2.4,
275
+ "eval_loss": 2.5781586170196533,
276
+ "eval_runtime": 43.8578,
277
+ "eval_samples_per_second": 22.801,
278
+ "eval_steps_per_second": 2.85,
279
+ "step": 180
280
+ },
281
+ {
282
+ "epoch": 2.533333333333333,
283
+ "grad_norm": 1.5135377645492554,
284
+ "learning_rate": 5.748148148148149e-05,
285
+ "loss": 2.2099,
286
+ "step": 190
287
+ },
288
+ {
289
+ "epoch": 2.533333333333333,
290
+ "eval_loss": 2.5752007961273193,
291
+ "eval_runtime": 43.8521,
292
+ "eval_samples_per_second": 22.804,
293
+ "eval_steps_per_second": 2.85,
294
+ "step": 190
295
+ },
296
+ {
297
+ "epoch": 2.6666666666666665,
298
+ "grad_norm": 1.5297592878341675,
299
+ "learning_rate": 5.62962962962963e-05,
300
+ "loss": 2.2965,
301
+ "step": 200
302
+ },
303
+ {
304
+ "epoch": 2.6666666666666665,
305
+ "eval_loss": 2.579918622970581,
306
+ "eval_runtime": 43.8661,
307
+ "eval_samples_per_second": 22.797,
308
+ "eval_steps_per_second": 2.85,
309
+ "step": 200
310
+ },
311
+ {
312
+ "epoch": 2.8,
313
+ "grad_norm": 1.6282892227172852,
314
+ "learning_rate": 5.511111111111112e-05,
315
+ "loss": 2.2487,
316
+ "step": 210
317
+ },
318
+ {
319
+ "epoch": 2.8,
320
+ "eval_loss": 2.5760037899017334,
321
+ "eval_runtime": 43.8379,
322
+ "eval_samples_per_second": 22.811,
323
+ "eval_steps_per_second": 2.851,
324
+ "step": 210
325
+ },
326
+ {
327
+ "epoch": 2.9333333333333336,
328
+ "grad_norm": 1.74424409866333,
329
+ "learning_rate": 5.392592592592593e-05,
330
+ "loss": 2.2049,
331
+ "step": 220
332
+ },
333
+ {
334
+ "epoch": 2.9333333333333336,
335
+ "eval_loss": 2.576190233230591,
336
+ "eval_runtime": 43.8491,
337
+ "eval_samples_per_second": 22.805,
338
+ "eval_steps_per_second": 2.851,
339
+ "step": 220
340
+ },
341
+ {
342
+ "epoch": 3.066666666666667,
343
+ "grad_norm": 1.654069423675537,
344
+ "learning_rate": 5.274074074074074e-05,
345
+ "loss": 2.1188,
346
+ "step": 230
347
+ },
348
+ {
349
+ "epoch": 3.066666666666667,
350
+ "eval_loss": 2.5971405506134033,
351
+ "eval_runtime": 43.855,
352
+ "eval_samples_per_second": 22.802,
353
+ "eval_steps_per_second": 2.85,
354
+ "step": 230
355
+ },
356
+ {
357
+ "epoch": 3.2,
358
+ "grad_norm": 2.541767120361328,
359
+ "learning_rate": 5.155555555555556e-05,
360
+ "loss": 2.0788,
361
+ "step": 240
362
+ },
363
+ {
364
+ "epoch": 3.2,
365
+ "eval_loss": 2.6767666339874268,
366
+ "eval_runtime": 43.8368,
367
+ "eval_samples_per_second": 22.812,
368
+ "eval_steps_per_second": 2.851,
369
+ "step": 240
370
+ },
371
+ {
372
+ "epoch": 3.3333333333333335,
373
+ "grad_norm": 2.0508077144622803,
374
+ "learning_rate": 5.037037037037037e-05,
375
+ "loss": 2.0784,
376
+ "step": 250
377
+ },
378
+ {
379
+ "epoch": 3.3333333333333335,
380
+ "eval_loss": 2.6486454010009766,
381
+ "eval_runtime": 43.8529,
382
+ "eval_samples_per_second": 22.803,
383
+ "eval_steps_per_second": 2.85,
384
+ "step": 250
385
+ },
386
+ {
387
+ "epoch": 3.466666666666667,
388
+ "grad_norm": 2.1096036434173584,
389
+ "learning_rate": 4.918518518518519e-05,
390
+ "loss": 2.0633,
391
+ "step": 260
392
+ },
393
+ {
394
+ "epoch": 3.466666666666667,
395
+ "eval_loss": 2.6501405239105225,
396
+ "eval_runtime": 43.8632,
397
+ "eval_samples_per_second": 22.798,
398
+ "eval_steps_per_second": 2.85,
399
+ "step": 260
400
+ },
401
+ {
402
+ "epoch": 3.6,
403
+ "grad_norm": 2.3028736114501953,
404
+ "learning_rate": 4.8e-05,
405
+ "loss": 2.0722,
406
+ "step": 270
407
+ },
408
+ {
409
+ "epoch": 3.6,
410
+ "eval_loss": 2.657053232192993,
411
+ "eval_runtime": 43.8423,
412
+ "eval_samples_per_second": 22.809,
413
+ "eval_steps_per_second": 2.851,
414
+ "step": 270
415
+ },
416
+ {
417
+ "epoch": 3.7333333333333334,
418
+ "grad_norm": 2.1536757946014404,
419
+ "learning_rate": 4.681481481481481e-05,
420
+ "loss": 2.0155,
421
+ "step": 280
422
+ },
423
+ {
424
+ "epoch": 3.7333333333333334,
425
+ "eval_loss": 2.648275375366211,
426
+ "eval_runtime": 43.8328,
427
+ "eval_samples_per_second": 22.814,
428
+ "eval_steps_per_second": 2.852,
429
+ "step": 280
430
+ },
431
+ {
432
+ "epoch": 3.8666666666666667,
433
+ "grad_norm": 2.4079270362854004,
434
+ "learning_rate": 4.5629629629629636e-05,
435
+ "loss": 2.1111,
436
+ "step": 290
437
+ },
438
+ {
439
+ "epoch": 3.8666666666666667,
440
+ "eval_loss": 2.650322675704956,
441
+ "eval_runtime": 43.835,
442
+ "eval_samples_per_second": 22.813,
443
+ "eval_steps_per_second": 2.852,
444
+ "step": 290
445
+ },
446
+ {
447
+ "epoch": 4.0,
448
+ "grad_norm": 2.426234722137451,
449
+ "learning_rate": 4.444444444444445e-05,
450
+ "loss": 2.041,
451
+ "step": 300
452
+ },
453
+ {
454
+ "epoch": 4.0,
455
+ "eval_loss": 2.6490862369537354,
456
+ "eval_runtime": 43.845,
457
+ "eval_samples_per_second": 22.808,
458
+ "eval_steps_per_second": 2.851,
459
+ "step": 300
460
+ },
461
+ {
462
+ "epoch": 4.133333333333334,
463
+ "grad_norm": 2.8063745498657227,
464
+ "learning_rate": 4.3259259259259264e-05,
465
+ "loss": 1.9316,
466
+ "step": 310
467
+ },
468
+ {
469
+ "epoch": 4.133333333333334,
470
+ "eval_loss": 2.7609620094299316,
471
+ "eval_runtime": 43.8481,
472
+ "eval_samples_per_second": 22.806,
473
+ "eval_steps_per_second": 2.851,
474
+ "step": 310
475
+ },
476
+ {
477
+ "epoch": 4.266666666666667,
478
+ "grad_norm": 2.96854305267334,
479
+ "learning_rate": 4.2074074074074075e-05,
480
+ "loss": 1.8889,
481
+ "step": 320
482
+ },
483
+ {
484
+ "epoch": 4.266666666666667,
485
+ "eval_loss": 2.736968994140625,
486
+ "eval_runtime": 43.8633,
487
+ "eval_samples_per_second": 22.798,
488
+ "eval_steps_per_second": 2.85,
489
+ "step": 320
490
+ },
491
+ {
492
+ "epoch": 4.4,
493
+ "grad_norm": 2.637695789337158,
494
+ "learning_rate": 4.088888888888889e-05,
495
+ "loss": 1.9187,
496
+ "step": 330
497
+ },
498
+ {
499
+ "epoch": 4.4,
500
+ "eval_loss": 2.7382876873016357,
501
+ "eval_runtime": 43.8486,
502
+ "eval_samples_per_second": 22.806,
503
+ "eval_steps_per_second": 2.851,
504
+ "step": 330
505
+ },
506
+ {
507
+ "epoch": 4.533333333333333,
508
+ "grad_norm": 2.9106290340423584,
509
+ "learning_rate": 3.970370370370371e-05,
510
+ "loss": 1.9002,
511
+ "step": 340
512
+ },
513
+ {
514
+ "epoch": 4.533333333333333,
515
+ "eval_loss": 2.734544515609741,
516
+ "eval_runtime": 43.8491,
517
+ "eval_samples_per_second": 22.805,
518
+ "eval_steps_per_second": 2.851,
519
+ "step": 340
520
+ },
521
+ {
522
+ "epoch": 4.666666666666667,
523
+ "grad_norm": 2.769315481185913,
524
+ "learning_rate": 3.851851851851852e-05,
525
+ "loss": 1.9251,
526
+ "step": 350
527
+ },
528
+ {
529
+ "epoch": 4.666666666666667,
530
+ "eval_loss": 2.734708070755005,
531
+ "eval_runtime": 43.8534,
532
+ "eval_samples_per_second": 22.803,
533
+ "eval_steps_per_second": 2.85,
534
+ "step": 350
535
+ },
536
+ {
537
+ "epoch": 4.8,
538
+ "grad_norm": 2.940281867980957,
539
+ "learning_rate": 3.733333333333334e-05,
540
+ "loss": 1.9319,
541
+ "step": 360
542
+ },
543
+ {
544
+ "epoch": 4.8,
545
+ "eval_loss": 2.7300503253936768,
546
+ "eval_runtime": 43.9017,
547
+ "eval_samples_per_second": 22.778,
548
+ "eval_steps_per_second": 2.847,
549
+ "step": 360
550
+ },
551
+ {
552
+ "epoch": 4.933333333333334,
553
+ "grad_norm": 2.8305609226226807,
554
+ "learning_rate": 3.614814814814815e-05,
555
+ "loss": 1.9332,
556
+ "step": 370
557
+ },
558
+ {
559
+ "epoch": 4.933333333333334,
560
+ "eval_loss": 2.7309281826019287,
561
+ "eval_runtime": 43.8842,
562
+ "eval_samples_per_second": 22.787,
563
+ "eval_steps_per_second": 2.848,
564
+ "step": 370
565
+ },
566
+ {
567
+ "epoch": 5.066666666666666,
568
+ "grad_norm": 2.8739213943481445,
569
+ "learning_rate": 3.4962962962962965e-05,
570
+ "loss": 1.8846,
571
+ "step": 380
572
+ },
573
+ {
574
+ "epoch": 5.066666666666666,
575
+ "eval_loss": 2.76513671875,
576
+ "eval_runtime": 43.906,
577
+ "eval_samples_per_second": 22.776,
578
+ "eval_steps_per_second": 2.847,
579
+ "step": 380
580
+ },
581
+ {
582
+ "epoch": 5.2,
583
+ "grad_norm": 3.9025838375091553,
584
+ "learning_rate": 3.377777777777778e-05,
585
+ "loss": 1.7575,
586
+ "step": 390
587
+ },
588
+ {
589
+ "epoch": 5.2,
590
+ "eval_loss": 2.847782611846924,
591
+ "eval_runtime": 43.8665,
592
+ "eval_samples_per_second": 22.796,
593
+ "eval_steps_per_second": 2.85,
594
+ "step": 390
595
+ },
596
+ {
597
+ "epoch": 5.333333333333333,
598
+ "grad_norm": 3.299649715423584,
599
+ "learning_rate": 3.259259259259259e-05,
600
+ "loss": 1.7713,
601
+ "step": 400
602
+ },
603
+ {
604
+ "epoch": 5.333333333333333,
605
+ "eval_loss": 2.8094286918640137,
606
+ "eval_runtime": 43.8629,
607
+ "eval_samples_per_second": 22.798,
608
+ "eval_steps_per_second": 2.85,
609
+ "step": 400
610
+ },
611
+ {
612
+ "epoch": 5.466666666666667,
613
+ "grad_norm": 3.4474265575408936,
614
+ "learning_rate": 3.140740740740741e-05,
615
+ "loss": 1.7983,
616
+ "step": 410
617
+ },
618
+ {
619
+ "epoch": 5.466666666666667,
620
+ "eval_loss": 2.827517509460449,
621
+ "eval_runtime": 43.8611,
622
+ "eval_samples_per_second": 22.799,
623
+ "eval_steps_per_second": 2.85,
624
+ "step": 410
625
+ },
626
+ {
627
+ "epoch": 5.6,
628
+ "grad_norm": 3.1924540996551514,
629
+ "learning_rate": 3.0222222222222225e-05,
630
+ "loss": 1.8091,
631
+ "step": 420
632
+ },
633
+ {
634
+ "epoch": 5.6,
635
+ "eval_loss": 2.81618332862854,
636
+ "eval_runtime": 43.8544,
637
+ "eval_samples_per_second": 22.803,
638
+ "eval_steps_per_second": 2.85,
639
+ "step": 420
640
+ },
641
+ {
642
+ "epoch": 5.733333333333333,
643
+ "grad_norm": 3.5224015712738037,
644
+ "learning_rate": 2.9037037037037042e-05,
645
+ "loss": 1.8253,
646
+ "step": 430
647
+ },
648
+ {
649
+ "epoch": 5.733333333333333,
650
+ "eval_loss": 2.816711187362671,
651
+ "eval_runtime": 43.8685,
652
+ "eval_samples_per_second": 22.795,
653
+ "eval_steps_per_second": 2.849,
654
+ "step": 430
655
+ },
656
+ {
657
+ "epoch": 5.866666666666667,
658
+ "grad_norm": 3.60918927192688,
659
+ "learning_rate": 2.7851851851851856e-05,
660
+ "loss": 1.8013,
661
+ "step": 440
662
+ },
663
+ {
664
+ "epoch": 5.866666666666667,
665
+ "eval_loss": 2.8146169185638428,
666
+ "eval_runtime": 43.8516,
667
+ "eval_samples_per_second": 22.804,
668
+ "eval_steps_per_second": 2.851,
669
+ "step": 440
670
+ },
671
+ {
672
+ "epoch": 6.0,
673
+ "grad_norm": 3.5798070430755615,
674
+ "learning_rate": 2.6666666666666667e-05,
675
+ "loss": 1.8258,
676
+ "step": 450
677
+ },
678
+ {
679
+ "epoch": 6.0,
680
+ "eval_loss": 2.8134233951568604,
681
+ "eval_runtime": 43.8442,
682
+ "eval_samples_per_second": 22.808,
683
+ "eval_steps_per_second": 2.851,
684
+ "step": 450
685
+ },
686
+ {
687
+ "epoch": 6.133333333333334,
688
+ "grad_norm": 5.563477993011475,
689
+ "learning_rate": 2.5481481481481484e-05,
690
+ "loss": 1.6649,
691
+ "step": 460
692
+ },
693
+ {
694
+ "epoch": 6.133333333333334,
695
+ "eval_loss": 2.9189789295196533,
696
+ "eval_runtime": 43.8602,
697
+ "eval_samples_per_second": 22.8,
698
+ "eval_steps_per_second": 2.85,
699
+ "step": 460
700
+ },
701
+ {
702
+ "epoch": 6.266666666666667,
703
+ "grad_norm": 4.192393779754639,
704
+ "learning_rate": 2.4296296296296298e-05,
705
+ "loss": 1.7443,
706
+ "step": 470
707
+ },
708
+ {
709
+ "epoch": 6.266666666666667,
710
+ "eval_loss": 2.893780469894409,
711
+ "eval_runtime": 43.8434,
712
+ "eval_samples_per_second": 22.808,
713
+ "eval_steps_per_second": 2.851,
714
+ "step": 470
715
+ },
716
+ {
717
+ "epoch": 6.4,
718
+ "grad_norm": 4.8650593757629395,
719
+ "learning_rate": 2.3111111111111112e-05,
720
+ "loss": 1.6961,
721
+ "step": 480
722
+ },
723
+ {
724
+ "epoch": 6.4,
725
+ "eval_loss": 2.8861398696899414,
726
+ "eval_runtime": 43.8417,
727
+ "eval_samples_per_second": 22.809,
728
+ "eval_steps_per_second": 2.851,
729
+ "step": 480
730
+ },
731
+ {
732
+ "epoch": 6.533333333333333,
733
+ "grad_norm": 3.844482660293579,
734
+ "learning_rate": 2.192592592592593e-05,
735
+ "loss": 1.6868,
736
+ "step": 490
737
+ },
738
+ {
739
+ "epoch": 6.533333333333333,
740
+ "eval_loss": 2.900317907333374,
741
+ "eval_runtime": 43.8557,
742
+ "eval_samples_per_second": 22.802,
743
+ "eval_steps_per_second": 2.85,
744
+ "step": 490
745
+ },
746
+ {
747
+ "epoch": 6.666666666666667,
748
+ "grad_norm": 4.230032920837402,
749
+ "learning_rate": 2.074074074074074e-05,
750
+ "loss": 1.6593,
751
+ "step": 500
752
+ },
753
+ {
754
+ "epoch": 6.666666666666667,
755
+ "eval_loss": 2.892076253890991,
756
+ "eval_runtime": 43.8479,
757
+ "eval_samples_per_second": 22.806,
758
+ "eval_steps_per_second": 2.851,
759
+ "step": 500
760
+ },
761
+ {
762
+ "epoch": 6.8,
763
+ "grad_norm": 4.427380561828613,
764
+ "learning_rate": 1.9555555555555557e-05,
765
+ "loss": 1.6777,
766
+ "step": 510
767
+ },
768
+ {
769
+ "epoch": 6.8,
770
+ "eval_loss": 2.8877696990966797,
771
+ "eval_runtime": 43.8489,
772
+ "eval_samples_per_second": 22.806,
773
+ "eval_steps_per_second": 2.851,
774
+ "step": 510
775
+ },
776
+ {
777
+ "epoch": 6.933333333333334,
778
+ "grad_norm": 4.23176908493042,
779
+ "learning_rate": 1.837037037037037e-05,
780
+ "loss": 1.7331,
781
+ "step": 520
782
+ },
783
+ {
784
+ "epoch": 6.933333333333334,
785
+ "eval_loss": 2.889272928237915,
786
+ "eval_runtime": 43.8577,
787
+ "eval_samples_per_second": 22.801,
788
+ "eval_steps_per_second": 2.85,
789
+ "step": 520
790
+ },
791
+ {
792
+ "epoch": 7.066666666666666,
793
+ "grad_norm": 3.9098429679870605,
794
+ "learning_rate": 1.7185185185185185e-05,
795
+ "loss": 1.6741,
796
+ "step": 530
797
+ },
798
+ {
799
+ "epoch": 7.066666666666666,
800
+ "eval_loss": 2.9202494621276855,
801
+ "eval_runtime": 43.8571,
802
+ "eval_samples_per_second": 22.801,
803
+ "eval_steps_per_second": 2.85,
804
+ "step": 530
805
+ },
806
+ {
807
+ "epoch": 7.2,
808
+ "grad_norm": 4.320191383361816,
809
+ "learning_rate": 1.6000000000000003e-05,
810
+ "loss": 1.5711,
811
+ "step": 540
812
+ },
813
+ {
814
+ "epoch": 7.2,
815
+ "eval_loss": 2.97855806350708,
816
+ "eval_runtime": 43.8599,
817
+ "eval_samples_per_second": 22.8,
818
+ "eval_steps_per_second": 2.85,
819
+ "step": 540
820
+ }
821
+ ],
822
+ "logging_steps": 10,
823
+ "max_steps": 675,
824
+ "num_input_tokens_seen": 0,
825
+ "num_train_epochs": 9,
826
+ "save_steps": 10,
827
+ "stateful_callbacks": {
828
+ "TrainerControl": {
829
+ "args": {
830
+ "should_epoch_stop": false,
831
+ "should_evaluate": false,
832
+ "should_log": false,
833
+ "should_save": true,
834
+ "should_training_stop": false
835
+ },
836
+ "attributes": {}
837
+ }
838
+ },
839
+ "total_flos": 8.84847887253504e+16,
840
+ "train_batch_size": 8,
841
+ "trial_name": null,
842
+ "trial_params": null
843
+ }
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-550/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/pythia-6_9b
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-550/adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/workspace/pythia-6_9b",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.1,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 8,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "dense_h_to_4h",
24
+ "query_key_value",
25
+ "dense",
26
+ "dense_4h_to_h"
27
+ ],
28
+ "task_type": "CAUSAL_LM",
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-550/trainer_state.json ADDED
@@ -0,0 +1,858 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 2.535032033920288,
3
+ "best_model_checkpoint": "./output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-150",
4
+ "epoch": 7.333333333333333,
5
+ "eval_steps": 10,
6
+ "global_step": 550,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.13333333333333333,
13
+ "grad_norm": 0.36938729882240295,
14
+ "learning_rate": 7.881481481481482e-05,
15
+ "loss": 2.519,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.13333333333333333,
20
+ "eval_loss": 2.579638957977295,
21
+ "eval_runtime": 43.8215,
22
+ "eval_samples_per_second": 22.82,
23
+ "eval_steps_per_second": 2.852,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.26666666666666666,
28
+ "grad_norm": 0.39850670099258423,
29
+ "learning_rate": 7.762962962962963e-05,
30
+ "loss": 2.5224,
31
+ "step": 20
32
+ },
33
+ {
34
+ "epoch": 0.26666666666666666,
35
+ "eval_loss": 2.5729691982269287,
36
+ "eval_runtime": 43.8179,
37
+ "eval_samples_per_second": 22.822,
38
+ "eval_steps_per_second": 2.853,
39
+ "step": 20
40
+ },
41
+ {
42
+ "epoch": 0.4,
43
+ "grad_norm": 0.40211933851242065,
44
+ "learning_rate": 7.644444444444445e-05,
45
+ "loss": 2.5169,
46
+ "step": 30
47
+ },
48
+ {
49
+ "epoch": 0.4,
50
+ "eval_loss": 2.567735433578491,
51
+ "eval_runtime": 43.8366,
52
+ "eval_samples_per_second": 22.812,
53
+ "eval_steps_per_second": 2.851,
54
+ "step": 30
55
+ },
56
+ {
57
+ "epoch": 0.5333333333333333,
58
+ "grad_norm": 0.6892333030700684,
59
+ "learning_rate": 7.525925925925926e-05,
60
+ "loss": 2.5784,
61
+ "step": 40
62
+ },
63
+ {
64
+ "epoch": 0.5333333333333333,
65
+ "eval_loss": 2.562650442123413,
66
+ "eval_runtime": 43.8377,
67
+ "eval_samples_per_second": 22.811,
68
+ "eval_steps_per_second": 2.851,
69
+ "step": 40
70
+ },
71
+ {
72
+ "epoch": 0.6666666666666666,
73
+ "grad_norm": 0.442343533039093,
74
+ "learning_rate": 7.407407407407409e-05,
75
+ "loss": 2.5431,
76
+ "step": 50
77
+ },
78
+ {
79
+ "epoch": 0.6666666666666666,
80
+ "eval_loss": 2.556513786315918,
81
+ "eval_runtime": 43.8656,
82
+ "eval_samples_per_second": 22.797,
83
+ "eval_steps_per_second": 2.85,
84
+ "step": 50
85
+ },
86
+ {
87
+ "epoch": 0.8,
88
+ "grad_norm": 0.4059845805168152,
89
+ "learning_rate": 7.28888888888889e-05,
90
+ "loss": 2.4936,
91
+ "step": 60
92
+ },
93
+ {
94
+ "epoch": 0.8,
95
+ "eval_loss": 2.552133798599243,
96
+ "eval_runtime": 43.8403,
97
+ "eval_samples_per_second": 22.81,
98
+ "eval_steps_per_second": 2.851,
99
+ "step": 60
100
+ },
101
+ {
102
+ "epoch": 0.9333333333333333,
103
+ "grad_norm": 0.48126307129859924,
104
+ "learning_rate": 7.170370370370371e-05,
105
+ "loss": 2.4901,
106
+ "step": 70
107
+ },
108
+ {
109
+ "epoch": 0.9333333333333333,
110
+ "eval_loss": 2.5477023124694824,
111
+ "eval_runtime": 43.8351,
112
+ "eval_samples_per_second": 22.813,
113
+ "eval_steps_per_second": 2.852,
114
+ "step": 70
115
+ },
116
+ {
117
+ "epoch": 1.0666666666666667,
118
+ "grad_norm": 0.48629865050315857,
119
+ "learning_rate": 7.051851851851853e-05,
120
+ "loss": 2.5114,
121
+ "step": 80
122
+ },
123
+ {
124
+ "epoch": 1.0666666666666667,
125
+ "eval_loss": 2.543431043624878,
126
+ "eval_runtime": 43.8432,
127
+ "eval_samples_per_second": 22.809,
128
+ "eval_steps_per_second": 2.851,
129
+ "step": 80
130
+ },
131
+ {
132
+ "epoch": 1.2,
133
+ "grad_norm": 0.5880796313285828,
134
+ "learning_rate": 6.933333333333334e-05,
135
+ "loss": 2.4446,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 1.2,
140
+ "eval_loss": 2.544339418411255,
141
+ "eval_runtime": 43.8437,
142
+ "eval_samples_per_second": 22.808,
143
+ "eval_steps_per_second": 2.851,
144
+ "step": 90
145
+ },
146
+ {
147
+ "epoch": 1.3333333333333333,
148
+ "grad_norm": 0.6746829748153687,
149
+ "learning_rate": 6.814814814814815e-05,
150
+ "loss": 2.4477,
151
+ "step": 100
152
+ },
153
+ {
154
+ "epoch": 1.3333333333333333,
155
+ "eval_loss": 2.544358968734741,
156
+ "eval_runtime": 43.8613,
157
+ "eval_samples_per_second": 22.799,
158
+ "eval_steps_per_second": 2.85,
159
+ "step": 100
160
+ },
161
+ {
162
+ "epoch": 1.4666666666666668,
163
+ "grad_norm": 0.8208937048912048,
164
+ "learning_rate": 6.696296296296296e-05,
165
+ "loss": 2.4004,
166
+ "step": 110
167
+ },
168
+ {
169
+ "epoch": 1.4666666666666668,
170
+ "eval_loss": 2.54068660736084,
171
+ "eval_runtime": 43.8426,
172
+ "eval_samples_per_second": 22.809,
173
+ "eval_steps_per_second": 2.851,
174
+ "step": 110
175
+ },
176
+ {
177
+ "epoch": 1.6,
178
+ "grad_norm": 0.925931453704834,
179
+ "learning_rate": 6.577777777777777e-05,
180
+ "loss": 2.3889,
181
+ "step": 120
182
+ },
183
+ {
184
+ "epoch": 1.6,
185
+ "eval_loss": 2.5393033027648926,
186
+ "eval_runtime": 43.8383,
187
+ "eval_samples_per_second": 22.811,
188
+ "eval_steps_per_second": 2.851,
189
+ "step": 120
190
+ },
191
+ {
192
+ "epoch": 1.7333333333333334,
193
+ "grad_norm": 0.8785662055015564,
194
+ "learning_rate": 6.45925925925926e-05,
195
+ "loss": 2.3959,
196
+ "step": 130
197
+ },
198
+ {
199
+ "epoch": 1.7333333333333334,
200
+ "eval_loss": 2.5367038249969482,
201
+ "eval_runtime": 43.8508,
202
+ "eval_samples_per_second": 22.805,
203
+ "eval_steps_per_second": 2.851,
204
+ "step": 130
205
+ },
206
+ {
207
+ "epoch": 1.8666666666666667,
208
+ "grad_norm": 0.941368818283081,
209
+ "learning_rate": 6.340740740740741e-05,
210
+ "loss": 2.3924,
211
+ "step": 140
212
+ },
213
+ {
214
+ "epoch": 1.8666666666666667,
215
+ "eval_loss": 2.535139560699463,
216
+ "eval_runtime": 43.8588,
217
+ "eval_samples_per_second": 22.8,
218
+ "eval_steps_per_second": 2.85,
219
+ "step": 140
220
+ },
221
+ {
222
+ "epoch": 2.0,
223
+ "grad_norm": 0.9578835368156433,
224
+ "learning_rate": 6.222222222222223e-05,
225
+ "loss": 2.4278,
226
+ "step": 150
227
+ },
228
+ {
229
+ "epoch": 2.0,
230
+ "eval_loss": 2.535032033920288,
231
+ "eval_runtime": 43.8484,
232
+ "eval_samples_per_second": 22.806,
233
+ "eval_steps_per_second": 2.851,
234
+ "step": 150
235
+ },
236
+ {
237
+ "epoch": 2.1333333333333333,
238
+ "grad_norm": 1.1541856527328491,
239
+ "learning_rate": 6.103703703703704e-05,
240
+ "loss": 2.2895,
241
+ "step": 160
242
+ },
243
+ {
244
+ "epoch": 2.1333333333333333,
245
+ "eval_loss": 2.564768075942993,
246
+ "eval_runtime": 43.8568,
247
+ "eval_samples_per_second": 22.801,
248
+ "eval_steps_per_second": 2.85,
249
+ "step": 160
250
+ },
251
+ {
252
+ "epoch": 2.2666666666666666,
253
+ "grad_norm": 1.4076604843139648,
254
+ "learning_rate": 5.9851851851851855e-05,
255
+ "loss": 2.2107,
256
+ "step": 170
257
+ },
258
+ {
259
+ "epoch": 2.2666666666666666,
260
+ "eval_loss": 2.5832314491271973,
261
+ "eval_runtime": 43.8455,
262
+ "eval_samples_per_second": 22.807,
263
+ "eval_steps_per_second": 2.851,
264
+ "step": 170
265
+ },
266
+ {
267
+ "epoch": 2.4,
268
+ "grad_norm": 1.4847813844680786,
269
+ "learning_rate": 5.8666666666666665e-05,
270
+ "loss": 2.2588,
271
+ "step": 180
272
+ },
273
+ {
274
+ "epoch": 2.4,
275
+ "eval_loss": 2.5781586170196533,
276
+ "eval_runtime": 43.8578,
277
+ "eval_samples_per_second": 22.801,
278
+ "eval_steps_per_second": 2.85,
279
+ "step": 180
280
+ },
281
+ {
282
+ "epoch": 2.533333333333333,
283
+ "grad_norm": 1.5135377645492554,
284
+ "learning_rate": 5.748148148148149e-05,
285
+ "loss": 2.2099,
286
+ "step": 190
287
+ },
288
+ {
289
+ "epoch": 2.533333333333333,
290
+ "eval_loss": 2.5752007961273193,
291
+ "eval_runtime": 43.8521,
292
+ "eval_samples_per_second": 22.804,
293
+ "eval_steps_per_second": 2.85,
294
+ "step": 190
295
+ },
296
+ {
297
+ "epoch": 2.6666666666666665,
298
+ "grad_norm": 1.5297592878341675,
299
+ "learning_rate": 5.62962962962963e-05,
300
+ "loss": 2.2965,
301
+ "step": 200
302
+ },
303
+ {
304
+ "epoch": 2.6666666666666665,
305
+ "eval_loss": 2.579918622970581,
306
+ "eval_runtime": 43.8661,
307
+ "eval_samples_per_second": 22.797,
308
+ "eval_steps_per_second": 2.85,
309
+ "step": 200
310
+ },
311
+ {
312
+ "epoch": 2.8,
313
+ "grad_norm": 1.6282892227172852,
314
+ "learning_rate": 5.511111111111112e-05,
315
+ "loss": 2.2487,
316
+ "step": 210
317
+ },
318
+ {
319
+ "epoch": 2.8,
320
+ "eval_loss": 2.5760037899017334,
321
+ "eval_runtime": 43.8379,
322
+ "eval_samples_per_second": 22.811,
323
+ "eval_steps_per_second": 2.851,
324
+ "step": 210
325
+ },
326
+ {
327
+ "epoch": 2.9333333333333336,
328
+ "grad_norm": 1.74424409866333,
329
+ "learning_rate": 5.392592592592593e-05,
330
+ "loss": 2.2049,
331
+ "step": 220
332
+ },
333
+ {
334
+ "epoch": 2.9333333333333336,
335
+ "eval_loss": 2.576190233230591,
336
+ "eval_runtime": 43.8491,
337
+ "eval_samples_per_second": 22.805,
338
+ "eval_steps_per_second": 2.851,
339
+ "step": 220
340
+ },
341
+ {
342
+ "epoch": 3.066666666666667,
343
+ "grad_norm": 1.654069423675537,
344
+ "learning_rate": 5.274074074074074e-05,
345
+ "loss": 2.1188,
346
+ "step": 230
347
+ },
348
+ {
349
+ "epoch": 3.066666666666667,
350
+ "eval_loss": 2.5971405506134033,
351
+ "eval_runtime": 43.855,
352
+ "eval_samples_per_second": 22.802,
353
+ "eval_steps_per_second": 2.85,
354
+ "step": 230
355
+ },
356
+ {
357
+ "epoch": 3.2,
358
+ "grad_norm": 2.541767120361328,
359
+ "learning_rate": 5.155555555555556e-05,
360
+ "loss": 2.0788,
361
+ "step": 240
362
+ },
363
+ {
364
+ "epoch": 3.2,
365
+ "eval_loss": 2.6767666339874268,
366
+ "eval_runtime": 43.8368,
367
+ "eval_samples_per_second": 22.812,
368
+ "eval_steps_per_second": 2.851,
369
+ "step": 240
370
+ },
371
+ {
372
+ "epoch": 3.3333333333333335,
373
+ "grad_norm": 2.0508077144622803,
374
+ "learning_rate": 5.037037037037037e-05,
375
+ "loss": 2.0784,
376
+ "step": 250
377
+ },
378
+ {
379
+ "epoch": 3.3333333333333335,
380
+ "eval_loss": 2.6486454010009766,
381
+ "eval_runtime": 43.8529,
382
+ "eval_samples_per_second": 22.803,
383
+ "eval_steps_per_second": 2.85,
384
+ "step": 250
385
+ },
386
+ {
387
+ "epoch": 3.466666666666667,
388
+ "grad_norm": 2.1096036434173584,
389
+ "learning_rate": 4.918518518518519e-05,
390
+ "loss": 2.0633,
391
+ "step": 260
392
+ },
393
+ {
394
+ "epoch": 3.466666666666667,
395
+ "eval_loss": 2.6501405239105225,
396
+ "eval_runtime": 43.8632,
397
+ "eval_samples_per_second": 22.798,
398
+ "eval_steps_per_second": 2.85,
399
+ "step": 260
400
+ },
401
+ {
402
+ "epoch": 3.6,
403
+ "grad_norm": 2.3028736114501953,
404
+ "learning_rate": 4.8e-05,
405
+ "loss": 2.0722,
406
+ "step": 270
407
+ },
408
+ {
409
+ "epoch": 3.6,
410
+ "eval_loss": 2.657053232192993,
411
+ "eval_runtime": 43.8423,
412
+ "eval_samples_per_second": 22.809,
413
+ "eval_steps_per_second": 2.851,
414
+ "step": 270
415
+ },
416
+ {
417
+ "epoch": 3.7333333333333334,
418
+ "grad_norm": 2.1536757946014404,
419
+ "learning_rate": 4.681481481481481e-05,
420
+ "loss": 2.0155,
421
+ "step": 280
422
+ },
423
+ {
424
+ "epoch": 3.7333333333333334,
425
+ "eval_loss": 2.648275375366211,
426
+ "eval_runtime": 43.8328,
427
+ "eval_samples_per_second": 22.814,
428
+ "eval_steps_per_second": 2.852,
429
+ "step": 280
430
+ },
431
+ {
432
+ "epoch": 3.8666666666666667,
433
+ "grad_norm": 2.4079270362854004,
434
+ "learning_rate": 4.5629629629629636e-05,
435
+ "loss": 2.1111,
436
+ "step": 290
437
+ },
438
+ {
439
+ "epoch": 3.8666666666666667,
440
+ "eval_loss": 2.650322675704956,
441
+ "eval_runtime": 43.835,
442
+ "eval_samples_per_second": 22.813,
443
+ "eval_steps_per_second": 2.852,
444
+ "step": 290
445
+ },
446
+ {
447
+ "epoch": 4.0,
448
+ "grad_norm": 2.426234722137451,
449
+ "learning_rate": 4.444444444444445e-05,
450
+ "loss": 2.041,
451
+ "step": 300
452
+ },
453
+ {
454
+ "epoch": 4.0,
455
+ "eval_loss": 2.6490862369537354,
456
+ "eval_runtime": 43.845,
457
+ "eval_samples_per_second": 22.808,
458
+ "eval_steps_per_second": 2.851,
459
+ "step": 300
460
+ },
461
+ {
462
+ "epoch": 4.133333333333334,
463
+ "grad_norm": 2.8063745498657227,
464
+ "learning_rate": 4.3259259259259264e-05,
465
+ "loss": 1.9316,
466
+ "step": 310
467
+ },
468
+ {
469
+ "epoch": 4.133333333333334,
470
+ "eval_loss": 2.7609620094299316,
471
+ "eval_runtime": 43.8481,
472
+ "eval_samples_per_second": 22.806,
473
+ "eval_steps_per_second": 2.851,
474
+ "step": 310
475
+ },
476
+ {
477
+ "epoch": 4.266666666666667,
478
+ "grad_norm": 2.96854305267334,
479
+ "learning_rate": 4.2074074074074075e-05,
480
+ "loss": 1.8889,
481
+ "step": 320
482
+ },
483
+ {
484
+ "epoch": 4.266666666666667,
485
+ "eval_loss": 2.736968994140625,
486
+ "eval_runtime": 43.8633,
487
+ "eval_samples_per_second": 22.798,
488
+ "eval_steps_per_second": 2.85,
489
+ "step": 320
490
+ },
491
+ {
492
+ "epoch": 4.4,
493
+ "grad_norm": 2.637695789337158,
494
+ "learning_rate": 4.088888888888889e-05,
495
+ "loss": 1.9187,
496
+ "step": 330
497
+ },
498
+ {
499
+ "epoch": 4.4,
500
+ "eval_loss": 2.7382876873016357,
501
+ "eval_runtime": 43.8486,
502
+ "eval_samples_per_second": 22.806,
503
+ "eval_steps_per_second": 2.851,
504
+ "step": 330
505
+ },
506
+ {
507
+ "epoch": 4.533333333333333,
508
+ "grad_norm": 2.9106290340423584,
509
+ "learning_rate": 3.970370370370371e-05,
510
+ "loss": 1.9002,
511
+ "step": 340
512
+ },
513
+ {
514
+ "epoch": 4.533333333333333,
515
+ "eval_loss": 2.734544515609741,
516
+ "eval_runtime": 43.8491,
517
+ "eval_samples_per_second": 22.805,
518
+ "eval_steps_per_second": 2.851,
519
+ "step": 340
520
+ },
521
+ {
522
+ "epoch": 4.666666666666667,
523
+ "grad_norm": 2.769315481185913,
524
+ "learning_rate": 3.851851851851852e-05,
525
+ "loss": 1.9251,
526
+ "step": 350
527
+ },
528
+ {
529
+ "epoch": 4.666666666666667,
530
+ "eval_loss": 2.734708070755005,
531
+ "eval_runtime": 43.8534,
532
+ "eval_samples_per_second": 22.803,
533
+ "eval_steps_per_second": 2.85,
534
+ "step": 350
535
+ },
536
+ {
537
+ "epoch": 4.8,
538
+ "grad_norm": 2.940281867980957,
539
+ "learning_rate": 3.733333333333334e-05,
540
+ "loss": 1.9319,
541
+ "step": 360
542
+ },
543
+ {
544
+ "epoch": 4.8,
545
+ "eval_loss": 2.7300503253936768,
546
+ "eval_runtime": 43.9017,
547
+ "eval_samples_per_second": 22.778,
548
+ "eval_steps_per_second": 2.847,
549
+ "step": 360
550
+ },
551
+ {
552
+ "epoch": 4.933333333333334,
553
+ "grad_norm": 2.8305609226226807,
554
+ "learning_rate": 3.614814814814815e-05,
555
+ "loss": 1.9332,
556
+ "step": 370
557
+ },
558
+ {
559
+ "epoch": 4.933333333333334,
560
+ "eval_loss": 2.7309281826019287,
561
+ "eval_runtime": 43.8842,
562
+ "eval_samples_per_second": 22.787,
563
+ "eval_steps_per_second": 2.848,
564
+ "step": 370
565
+ },
566
+ {
567
+ "epoch": 5.066666666666666,
568
+ "grad_norm": 2.8739213943481445,
569
+ "learning_rate": 3.4962962962962965e-05,
570
+ "loss": 1.8846,
571
+ "step": 380
572
+ },
573
+ {
574
+ "epoch": 5.066666666666666,
575
+ "eval_loss": 2.76513671875,
576
+ "eval_runtime": 43.906,
577
+ "eval_samples_per_second": 22.776,
578
+ "eval_steps_per_second": 2.847,
579
+ "step": 380
580
+ },
581
+ {
582
+ "epoch": 5.2,
583
+ "grad_norm": 3.9025838375091553,
584
+ "learning_rate": 3.377777777777778e-05,
585
+ "loss": 1.7575,
586
+ "step": 390
587
+ },
588
+ {
589
+ "epoch": 5.2,
590
+ "eval_loss": 2.847782611846924,
591
+ "eval_runtime": 43.8665,
592
+ "eval_samples_per_second": 22.796,
593
+ "eval_steps_per_second": 2.85,
594
+ "step": 390
595
+ },
596
+ {
597
+ "epoch": 5.333333333333333,
598
+ "grad_norm": 3.299649715423584,
599
+ "learning_rate": 3.259259259259259e-05,
600
+ "loss": 1.7713,
601
+ "step": 400
602
+ },
603
+ {
604
+ "epoch": 5.333333333333333,
605
+ "eval_loss": 2.8094286918640137,
606
+ "eval_runtime": 43.8629,
607
+ "eval_samples_per_second": 22.798,
608
+ "eval_steps_per_second": 2.85,
609
+ "step": 400
610
+ },
611
+ {
612
+ "epoch": 5.466666666666667,
613
+ "grad_norm": 3.4474265575408936,
614
+ "learning_rate": 3.140740740740741e-05,
615
+ "loss": 1.7983,
616
+ "step": 410
617
+ },
618
+ {
619
+ "epoch": 5.466666666666667,
620
+ "eval_loss": 2.827517509460449,
621
+ "eval_runtime": 43.8611,
622
+ "eval_samples_per_second": 22.799,
623
+ "eval_steps_per_second": 2.85,
624
+ "step": 410
625
+ },
626
+ {
627
+ "epoch": 5.6,
628
+ "grad_norm": 3.1924540996551514,
629
+ "learning_rate": 3.0222222222222225e-05,
630
+ "loss": 1.8091,
631
+ "step": 420
632
+ },
633
+ {
634
+ "epoch": 5.6,
635
+ "eval_loss": 2.81618332862854,
636
+ "eval_runtime": 43.8544,
637
+ "eval_samples_per_second": 22.803,
638
+ "eval_steps_per_second": 2.85,
639
+ "step": 420
640
+ },
641
+ {
642
+ "epoch": 5.733333333333333,
643
+ "grad_norm": 3.5224015712738037,
644
+ "learning_rate": 2.9037037037037042e-05,
645
+ "loss": 1.8253,
646
+ "step": 430
647
+ },
648
+ {
649
+ "epoch": 5.733333333333333,
650
+ "eval_loss": 2.816711187362671,
651
+ "eval_runtime": 43.8685,
652
+ "eval_samples_per_second": 22.795,
653
+ "eval_steps_per_second": 2.849,
654
+ "step": 430
655
+ },
656
+ {
657
+ "epoch": 5.866666666666667,
658
+ "grad_norm": 3.60918927192688,
659
+ "learning_rate": 2.7851851851851856e-05,
660
+ "loss": 1.8013,
661
+ "step": 440
662
+ },
663
+ {
664
+ "epoch": 5.866666666666667,
665
+ "eval_loss": 2.8146169185638428,
666
+ "eval_runtime": 43.8516,
667
+ "eval_samples_per_second": 22.804,
668
+ "eval_steps_per_second": 2.851,
669
+ "step": 440
670
+ },
671
+ {
672
+ "epoch": 6.0,
673
+ "grad_norm": 3.5798070430755615,
674
+ "learning_rate": 2.6666666666666667e-05,
675
+ "loss": 1.8258,
676
+ "step": 450
677
+ },
678
+ {
679
+ "epoch": 6.0,
680
+ "eval_loss": 2.8134233951568604,
681
+ "eval_runtime": 43.8442,
682
+ "eval_samples_per_second": 22.808,
683
+ "eval_steps_per_second": 2.851,
684
+ "step": 450
685
+ },
686
+ {
687
+ "epoch": 6.133333333333334,
688
+ "grad_norm": 5.563477993011475,
689
+ "learning_rate": 2.5481481481481484e-05,
690
+ "loss": 1.6649,
691
+ "step": 460
692
+ },
693
+ {
694
+ "epoch": 6.133333333333334,
695
+ "eval_loss": 2.9189789295196533,
696
+ "eval_runtime": 43.8602,
697
+ "eval_samples_per_second": 22.8,
698
+ "eval_steps_per_second": 2.85,
699
+ "step": 460
700
+ },
701
+ {
702
+ "epoch": 6.266666666666667,
703
+ "grad_norm": 4.192393779754639,
704
+ "learning_rate": 2.4296296296296298e-05,
705
+ "loss": 1.7443,
706
+ "step": 470
707
+ },
708
+ {
709
+ "epoch": 6.266666666666667,
710
+ "eval_loss": 2.893780469894409,
711
+ "eval_runtime": 43.8434,
712
+ "eval_samples_per_second": 22.808,
713
+ "eval_steps_per_second": 2.851,
714
+ "step": 470
715
+ },
716
+ {
717
+ "epoch": 6.4,
718
+ "grad_norm": 4.8650593757629395,
719
+ "learning_rate": 2.3111111111111112e-05,
720
+ "loss": 1.6961,
721
+ "step": 480
722
+ },
723
+ {
724
+ "epoch": 6.4,
725
+ "eval_loss": 2.8861398696899414,
726
+ "eval_runtime": 43.8417,
727
+ "eval_samples_per_second": 22.809,
728
+ "eval_steps_per_second": 2.851,
729
+ "step": 480
730
+ },
731
+ {
732
+ "epoch": 6.533333333333333,
733
+ "grad_norm": 3.844482660293579,
734
+ "learning_rate": 2.192592592592593e-05,
735
+ "loss": 1.6868,
736
+ "step": 490
737
+ },
738
+ {
739
+ "epoch": 6.533333333333333,
740
+ "eval_loss": 2.900317907333374,
741
+ "eval_runtime": 43.8557,
742
+ "eval_samples_per_second": 22.802,
743
+ "eval_steps_per_second": 2.85,
744
+ "step": 490
745
+ },
746
+ {
747
+ "epoch": 6.666666666666667,
748
+ "grad_norm": 4.230032920837402,
749
+ "learning_rate": 2.074074074074074e-05,
750
+ "loss": 1.6593,
751
+ "step": 500
752
+ },
753
+ {
754
+ "epoch": 6.666666666666667,
755
+ "eval_loss": 2.892076253890991,
756
+ "eval_runtime": 43.8479,
757
+ "eval_samples_per_second": 22.806,
758
+ "eval_steps_per_second": 2.851,
759
+ "step": 500
760
+ },
761
+ {
762
+ "epoch": 6.8,
763
+ "grad_norm": 4.427380561828613,
764
+ "learning_rate": 1.9555555555555557e-05,
765
+ "loss": 1.6777,
766
+ "step": 510
767
+ },
768
+ {
769
+ "epoch": 6.8,
770
+ "eval_loss": 2.8877696990966797,
771
+ "eval_runtime": 43.8489,
772
+ "eval_samples_per_second": 22.806,
773
+ "eval_steps_per_second": 2.851,
774
+ "step": 510
775
+ },
776
+ {
777
+ "epoch": 6.933333333333334,
778
+ "grad_norm": 4.23176908493042,
779
+ "learning_rate": 1.837037037037037e-05,
780
+ "loss": 1.7331,
781
+ "step": 520
782
+ },
783
+ {
784
+ "epoch": 6.933333333333334,
785
+ "eval_loss": 2.889272928237915,
786
+ "eval_runtime": 43.8577,
787
+ "eval_samples_per_second": 22.801,
788
+ "eval_steps_per_second": 2.85,
789
+ "step": 520
790
+ },
791
+ {
792
+ "epoch": 7.066666666666666,
793
+ "grad_norm": 3.9098429679870605,
794
+ "learning_rate": 1.7185185185185185e-05,
795
+ "loss": 1.6741,
796
+ "step": 530
797
+ },
798
+ {
799
+ "epoch": 7.066666666666666,
800
+ "eval_loss": 2.9202494621276855,
801
+ "eval_runtime": 43.8571,
802
+ "eval_samples_per_second": 22.801,
803
+ "eval_steps_per_second": 2.85,
804
+ "step": 530
805
+ },
806
+ {
807
+ "epoch": 7.2,
808
+ "grad_norm": 4.320191383361816,
809
+ "learning_rate": 1.6000000000000003e-05,
810
+ "loss": 1.5711,
811
+ "step": 540
812
+ },
813
+ {
814
+ "epoch": 7.2,
815
+ "eval_loss": 2.97855806350708,
816
+ "eval_runtime": 43.8599,
817
+ "eval_samples_per_second": 22.8,
818
+ "eval_steps_per_second": 2.85,
819
+ "step": 540
820
+ },
821
+ {
822
+ "epoch": 7.333333333333333,
823
+ "grad_norm": 4.003049850463867,
824
+ "learning_rate": 1.4814814814814815e-05,
825
+ "loss": 1.6106,
826
+ "step": 550
827
+ },
828
+ {
829
+ "epoch": 7.333333333333333,
830
+ "eval_loss": 2.9440739154815674,
831
+ "eval_runtime": 43.8605,
832
+ "eval_samples_per_second": 22.8,
833
+ "eval_steps_per_second": 2.85,
834
+ "step": 550
835
+ }
836
+ ],
837
+ "logging_steps": 10,
838
+ "max_steps": 675,
839
+ "num_input_tokens_seen": 0,
840
+ "num_train_epochs": 9,
841
+ "save_steps": 10,
842
+ "stateful_callbacks": {
843
+ "TrainerControl": {
844
+ "args": {
845
+ "should_epoch_stop": false,
846
+ "should_evaluate": false,
847
+ "should_log": false,
848
+ "should_save": true,
849
+ "should_training_stop": false
850
+ },
851
+ "attributes": {}
852
+ }
853
+ },
854
+ "total_flos": 9.0123395923968e+16,
855
+ "train_batch_size": 8,
856
+ "trial_name": null,
857
+ "trial_params": null
858
+ }
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-560/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/pythia-6_9b
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-560/adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/workspace/pythia-6_9b",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.1,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 8,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "dense_h_to_4h",
24
+ "query_key_value",
25
+ "dense",
26
+ "dense_4h_to_h"
27
+ ],
28
+ "task_type": "CAUSAL_LM",
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-560/trainer_state.json ADDED
@@ -0,0 +1,873 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 2.535032033920288,
3
+ "best_model_checkpoint": "./output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-150",
4
+ "epoch": 7.466666666666667,
5
+ "eval_steps": 10,
6
+ "global_step": 560,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.13333333333333333,
13
+ "grad_norm": 0.36938729882240295,
14
+ "learning_rate": 7.881481481481482e-05,
15
+ "loss": 2.519,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.13333333333333333,
20
+ "eval_loss": 2.579638957977295,
21
+ "eval_runtime": 43.8215,
22
+ "eval_samples_per_second": 22.82,
23
+ "eval_steps_per_second": 2.852,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.26666666666666666,
28
+ "grad_norm": 0.39850670099258423,
29
+ "learning_rate": 7.762962962962963e-05,
30
+ "loss": 2.5224,
31
+ "step": 20
32
+ },
33
+ {
34
+ "epoch": 0.26666666666666666,
35
+ "eval_loss": 2.5729691982269287,
36
+ "eval_runtime": 43.8179,
37
+ "eval_samples_per_second": 22.822,
38
+ "eval_steps_per_second": 2.853,
39
+ "step": 20
40
+ },
41
+ {
42
+ "epoch": 0.4,
43
+ "grad_norm": 0.40211933851242065,
44
+ "learning_rate": 7.644444444444445e-05,
45
+ "loss": 2.5169,
46
+ "step": 30
47
+ },
48
+ {
49
+ "epoch": 0.4,
50
+ "eval_loss": 2.567735433578491,
51
+ "eval_runtime": 43.8366,
52
+ "eval_samples_per_second": 22.812,
53
+ "eval_steps_per_second": 2.851,
54
+ "step": 30
55
+ },
56
+ {
57
+ "epoch": 0.5333333333333333,
58
+ "grad_norm": 0.6892333030700684,
59
+ "learning_rate": 7.525925925925926e-05,
60
+ "loss": 2.5784,
61
+ "step": 40
62
+ },
63
+ {
64
+ "epoch": 0.5333333333333333,
65
+ "eval_loss": 2.562650442123413,
66
+ "eval_runtime": 43.8377,
67
+ "eval_samples_per_second": 22.811,
68
+ "eval_steps_per_second": 2.851,
69
+ "step": 40
70
+ },
71
+ {
72
+ "epoch": 0.6666666666666666,
73
+ "grad_norm": 0.442343533039093,
74
+ "learning_rate": 7.407407407407409e-05,
75
+ "loss": 2.5431,
76
+ "step": 50
77
+ },
78
+ {
79
+ "epoch": 0.6666666666666666,
80
+ "eval_loss": 2.556513786315918,
81
+ "eval_runtime": 43.8656,
82
+ "eval_samples_per_second": 22.797,
83
+ "eval_steps_per_second": 2.85,
84
+ "step": 50
85
+ },
86
+ {
87
+ "epoch": 0.8,
88
+ "grad_norm": 0.4059845805168152,
89
+ "learning_rate": 7.28888888888889e-05,
90
+ "loss": 2.4936,
91
+ "step": 60
92
+ },
93
+ {
94
+ "epoch": 0.8,
95
+ "eval_loss": 2.552133798599243,
96
+ "eval_runtime": 43.8403,
97
+ "eval_samples_per_second": 22.81,
98
+ "eval_steps_per_second": 2.851,
99
+ "step": 60
100
+ },
101
+ {
102
+ "epoch": 0.9333333333333333,
103
+ "grad_norm": 0.48126307129859924,
104
+ "learning_rate": 7.170370370370371e-05,
105
+ "loss": 2.4901,
106
+ "step": 70
107
+ },
108
+ {
109
+ "epoch": 0.9333333333333333,
110
+ "eval_loss": 2.5477023124694824,
111
+ "eval_runtime": 43.8351,
112
+ "eval_samples_per_second": 22.813,
113
+ "eval_steps_per_second": 2.852,
114
+ "step": 70
115
+ },
116
+ {
117
+ "epoch": 1.0666666666666667,
118
+ "grad_norm": 0.48629865050315857,
119
+ "learning_rate": 7.051851851851853e-05,
120
+ "loss": 2.5114,
121
+ "step": 80
122
+ },
123
+ {
124
+ "epoch": 1.0666666666666667,
125
+ "eval_loss": 2.543431043624878,
126
+ "eval_runtime": 43.8432,
127
+ "eval_samples_per_second": 22.809,
128
+ "eval_steps_per_second": 2.851,
129
+ "step": 80
130
+ },
131
+ {
132
+ "epoch": 1.2,
133
+ "grad_norm": 0.5880796313285828,
134
+ "learning_rate": 6.933333333333334e-05,
135
+ "loss": 2.4446,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 1.2,
140
+ "eval_loss": 2.544339418411255,
141
+ "eval_runtime": 43.8437,
142
+ "eval_samples_per_second": 22.808,
143
+ "eval_steps_per_second": 2.851,
144
+ "step": 90
145
+ },
146
+ {
147
+ "epoch": 1.3333333333333333,
148
+ "grad_norm": 0.6746829748153687,
149
+ "learning_rate": 6.814814814814815e-05,
150
+ "loss": 2.4477,
151
+ "step": 100
152
+ },
153
+ {
154
+ "epoch": 1.3333333333333333,
155
+ "eval_loss": 2.544358968734741,
156
+ "eval_runtime": 43.8613,
157
+ "eval_samples_per_second": 22.799,
158
+ "eval_steps_per_second": 2.85,
159
+ "step": 100
160
+ },
161
+ {
162
+ "epoch": 1.4666666666666668,
163
+ "grad_norm": 0.8208937048912048,
164
+ "learning_rate": 6.696296296296296e-05,
165
+ "loss": 2.4004,
166
+ "step": 110
167
+ },
168
+ {
169
+ "epoch": 1.4666666666666668,
170
+ "eval_loss": 2.54068660736084,
171
+ "eval_runtime": 43.8426,
172
+ "eval_samples_per_second": 22.809,
173
+ "eval_steps_per_second": 2.851,
174
+ "step": 110
175
+ },
176
+ {
177
+ "epoch": 1.6,
178
+ "grad_norm": 0.925931453704834,
179
+ "learning_rate": 6.577777777777777e-05,
180
+ "loss": 2.3889,
181
+ "step": 120
182
+ },
183
+ {
184
+ "epoch": 1.6,
185
+ "eval_loss": 2.5393033027648926,
186
+ "eval_runtime": 43.8383,
187
+ "eval_samples_per_second": 22.811,
188
+ "eval_steps_per_second": 2.851,
189
+ "step": 120
190
+ },
191
+ {
192
+ "epoch": 1.7333333333333334,
193
+ "grad_norm": 0.8785662055015564,
194
+ "learning_rate": 6.45925925925926e-05,
195
+ "loss": 2.3959,
196
+ "step": 130
197
+ },
198
+ {
199
+ "epoch": 1.7333333333333334,
200
+ "eval_loss": 2.5367038249969482,
201
+ "eval_runtime": 43.8508,
202
+ "eval_samples_per_second": 22.805,
203
+ "eval_steps_per_second": 2.851,
204
+ "step": 130
205
+ },
206
+ {
207
+ "epoch": 1.8666666666666667,
208
+ "grad_norm": 0.941368818283081,
209
+ "learning_rate": 6.340740740740741e-05,
210
+ "loss": 2.3924,
211
+ "step": 140
212
+ },
213
+ {
214
+ "epoch": 1.8666666666666667,
215
+ "eval_loss": 2.535139560699463,
216
+ "eval_runtime": 43.8588,
217
+ "eval_samples_per_second": 22.8,
218
+ "eval_steps_per_second": 2.85,
219
+ "step": 140
220
+ },
221
+ {
222
+ "epoch": 2.0,
223
+ "grad_norm": 0.9578835368156433,
224
+ "learning_rate": 6.222222222222223e-05,
225
+ "loss": 2.4278,
226
+ "step": 150
227
+ },
228
+ {
229
+ "epoch": 2.0,
230
+ "eval_loss": 2.535032033920288,
231
+ "eval_runtime": 43.8484,
232
+ "eval_samples_per_second": 22.806,
233
+ "eval_steps_per_second": 2.851,
234
+ "step": 150
235
+ },
236
+ {
237
+ "epoch": 2.1333333333333333,
238
+ "grad_norm": 1.1541856527328491,
239
+ "learning_rate": 6.103703703703704e-05,
240
+ "loss": 2.2895,
241
+ "step": 160
242
+ },
243
+ {
244
+ "epoch": 2.1333333333333333,
245
+ "eval_loss": 2.564768075942993,
246
+ "eval_runtime": 43.8568,
247
+ "eval_samples_per_second": 22.801,
248
+ "eval_steps_per_second": 2.85,
249
+ "step": 160
250
+ },
251
+ {
252
+ "epoch": 2.2666666666666666,
253
+ "grad_norm": 1.4076604843139648,
254
+ "learning_rate": 5.9851851851851855e-05,
255
+ "loss": 2.2107,
256
+ "step": 170
257
+ },
258
+ {
259
+ "epoch": 2.2666666666666666,
260
+ "eval_loss": 2.5832314491271973,
261
+ "eval_runtime": 43.8455,
262
+ "eval_samples_per_second": 22.807,
263
+ "eval_steps_per_second": 2.851,
264
+ "step": 170
265
+ },
266
+ {
267
+ "epoch": 2.4,
268
+ "grad_norm": 1.4847813844680786,
269
+ "learning_rate": 5.8666666666666665e-05,
270
+ "loss": 2.2588,
271
+ "step": 180
272
+ },
273
+ {
274
+ "epoch": 2.4,
275
+ "eval_loss": 2.5781586170196533,
276
+ "eval_runtime": 43.8578,
277
+ "eval_samples_per_second": 22.801,
278
+ "eval_steps_per_second": 2.85,
279
+ "step": 180
280
+ },
281
+ {
282
+ "epoch": 2.533333333333333,
283
+ "grad_norm": 1.5135377645492554,
284
+ "learning_rate": 5.748148148148149e-05,
285
+ "loss": 2.2099,
286
+ "step": 190
287
+ },
288
+ {
289
+ "epoch": 2.533333333333333,
290
+ "eval_loss": 2.5752007961273193,
291
+ "eval_runtime": 43.8521,
292
+ "eval_samples_per_second": 22.804,
293
+ "eval_steps_per_second": 2.85,
294
+ "step": 190
295
+ },
296
+ {
297
+ "epoch": 2.6666666666666665,
298
+ "grad_norm": 1.5297592878341675,
299
+ "learning_rate": 5.62962962962963e-05,
300
+ "loss": 2.2965,
301
+ "step": 200
302
+ },
303
+ {
304
+ "epoch": 2.6666666666666665,
305
+ "eval_loss": 2.579918622970581,
306
+ "eval_runtime": 43.8661,
307
+ "eval_samples_per_second": 22.797,
308
+ "eval_steps_per_second": 2.85,
309
+ "step": 200
310
+ },
311
+ {
312
+ "epoch": 2.8,
313
+ "grad_norm": 1.6282892227172852,
314
+ "learning_rate": 5.511111111111112e-05,
315
+ "loss": 2.2487,
316
+ "step": 210
317
+ },
318
+ {
319
+ "epoch": 2.8,
320
+ "eval_loss": 2.5760037899017334,
321
+ "eval_runtime": 43.8379,
322
+ "eval_samples_per_second": 22.811,
323
+ "eval_steps_per_second": 2.851,
324
+ "step": 210
325
+ },
326
+ {
327
+ "epoch": 2.9333333333333336,
328
+ "grad_norm": 1.74424409866333,
329
+ "learning_rate": 5.392592592592593e-05,
330
+ "loss": 2.2049,
331
+ "step": 220
332
+ },
333
+ {
334
+ "epoch": 2.9333333333333336,
335
+ "eval_loss": 2.576190233230591,
336
+ "eval_runtime": 43.8491,
337
+ "eval_samples_per_second": 22.805,
338
+ "eval_steps_per_second": 2.851,
339
+ "step": 220
340
+ },
341
+ {
342
+ "epoch": 3.066666666666667,
343
+ "grad_norm": 1.654069423675537,
344
+ "learning_rate": 5.274074074074074e-05,
345
+ "loss": 2.1188,
346
+ "step": 230
347
+ },
348
+ {
349
+ "epoch": 3.066666666666667,
350
+ "eval_loss": 2.5971405506134033,
351
+ "eval_runtime": 43.855,
352
+ "eval_samples_per_second": 22.802,
353
+ "eval_steps_per_second": 2.85,
354
+ "step": 230
355
+ },
356
+ {
357
+ "epoch": 3.2,
358
+ "grad_norm": 2.541767120361328,
359
+ "learning_rate": 5.155555555555556e-05,
360
+ "loss": 2.0788,
361
+ "step": 240
362
+ },
363
+ {
364
+ "epoch": 3.2,
365
+ "eval_loss": 2.6767666339874268,
366
+ "eval_runtime": 43.8368,
367
+ "eval_samples_per_second": 22.812,
368
+ "eval_steps_per_second": 2.851,
369
+ "step": 240
370
+ },
371
+ {
372
+ "epoch": 3.3333333333333335,
373
+ "grad_norm": 2.0508077144622803,
374
+ "learning_rate": 5.037037037037037e-05,
375
+ "loss": 2.0784,
376
+ "step": 250
377
+ },
378
+ {
379
+ "epoch": 3.3333333333333335,
380
+ "eval_loss": 2.6486454010009766,
381
+ "eval_runtime": 43.8529,
382
+ "eval_samples_per_second": 22.803,
383
+ "eval_steps_per_second": 2.85,
384
+ "step": 250
385
+ },
386
+ {
387
+ "epoch": 3.466666666666667,
388
+ "grad_norm": 2.1096036434173584,
389
+ "learning_rate": 4.918518518518519e-05,
390
+ "loss": 2.0633,
391
+ "step": 260
392
+ },
393
+ {
394
+ "epoch": 3.466666666666667,
395
+ "eval_loss": 2.6501405239105225,
396
+ "eval_runtime": 43.8632,
397
+ "eval_samples_per_second": 22.798,
398
+ "eval_steps_per_second": 2.85,
399
+ "step": 260
400
+ },
401
+ {
402
+ "epoch": 3.6,
403
+ "grad_norm": 2.3028736114501953,
404
+ "learning_rate": 4.8e-05,
405
+ "loss": 2.0722,
406
+ "step": 270
407
+ },
408
+ {
409
+ "epoch": 3.6,
410
+ "eval_loss": 2.657053232192993,
411
+ "eval_runtime": 43.8423,
412
+ "eval_samples_per_second": 22.809,
413
+ "eval_steps_per_second": 2.851,
414
+ "step": 270
415
+ },
416
+ {
417
+ "epoch": 3.7333333333333334,
418
+ "grad_norm": 2.1536757946014404,
419
+ "learning_rate": 4.681481481481481e-05,
420
+ "loss": 2.0155,
421
+ "step": 280
422
+ },
423
+ {
424
+ "epoch": 3.7333333333333334,
425
+ "eval_loss": 2.648275375366211,
426
+ "eval_runtime": 43.8328,
427
+ "eval_samples_per_second": 22.814,
428
+ "eval_steps_per_second": 2.852,
429
+ "step": 280
430
+ },
431
+ {
432
+ "epoch": 3.8666666666666667,
433
+ "grad_norm": 2.4079270362854004,
434
+ "learning_rate": 4.5629629629629636e-05,
435
+ "loss": 2.1111,
436
+ "step": 290
437
+ },
438
+ {
439
+ "epoch": 3.8666666666666667,
440
+ "eval_loss": 2.650322675704956,
441
+ "eval_runtime": 43.835,
442
+ "eval_samples_per_second": 22.813,
443
+ "eval_steps_per_second": 2.852,
444
+ "step": 290
445
+ },
446
+ {
447
+ "epoch": 4.0,
448
+ "grad_norm": 2.426234722137451,
449
+ "learning_rate": 4.444444444444445e-05,
450
+ "loss": 2.041,
451
+ "step": 300
452
+ },
453
+ {
454
+ "epoch": 4.0,
455
+ "eval_loss": 2.6490862369537354,
456
+ "eval_runtime": 43.845,
457
+ "eval_samples_per_second": 22.808,
458
+ "eval_steps_per_second": 2.851,
459
+ "step": 300
460
+ },
461
+ {
462
+ "epoch": 4.133333333333334,
463
+ "grad_norm": 2.8063745498657227,
464
+ "learning_rate": 4.3259259259259264e-05,
465
+ "loss": 1.9316,
466
+ "step": 310
467
+ },
468
+ {
469
+ "epoch": 4.133333333333334,
470
+ "eval_loss": 2.7609620094299316,
471
+ "eval_runtime": 43.8481,
472
+ "eval_samples_per_second": 22.806,
473
+ "eval_steps_per_second": 2.851,
474
+ "step": 310
475
+ },
476
+ {
477
+ "epoch": 4.266666666666667,
478
+ "grad_norm": 2.96854305267334,
479
+ "learning_rate": 4.2074074074074075e-05,
480
+ "loss": 1.8889,
481
+ "step": 320
482
+ },
483
+ {
484
+ "epoch": 4.266666666666667,
485
+ "eval_loss": 2.736968994140625,
486
+ "eval_runtime": 43.8633,
487
+ "eval_samples_per_second": 22.798,
488
+ "eval_steps_per_second": 2.85,
489
+ "step": 320
490
+ },
491
+ {
492
+ "epoch": 4.4,
493
+ "grad_norm": 2.637695789337158,
494
+ "learning_rate": 4.088888888888889e-05,
495
+ "loss": 1.9187,
496
+ "step": 330
497
+ },
498
+ {
499
+ "epoch": 4.4,
500
+ "eval_loss": 2.7382876873016357,
501
+ "eval_runtime": 43.8486,
502
+ "eval_samples_per_second": 22.806,
503
+ "eval_steps_per_second": 2.851,
504
+ "step": 330
505
+ },
506
+ {
507
+ "epoch": 4.533333333333333,
508
+ "grad_norm": 2.9106290340423584,
509
+ "learning_rate": 3.970370370370371e-05,
510
+ "loss": 1.9002,
511
+ "step": 340
512
+ },
513
+ {
514
+ "epoch": 4.533333333333333,
515
+ "eval_loss": 2.734544515609741,
516
+ "eval_runtime": 43.8491,
517
+ "eval_samples_per_second": 22.805,
518
+ "eval_steps_per_second": 2.851,
519
+ "step": 340
520
+ },
521
+ {
522
+ "epoch": 4.666666666666667,
523
+ "grad_norm": 2.769315481185913,
524
+ "learning_rate": 3.851851851851852e-05,
525
+ "loss": 1.9251,
526
+ "step": 350
527
+ },
528
+ {
529
+ "epoch": 4.666666666666667,
530
+ "eval_loss": 2.734708070755005,
531
+ "eval_runtime": 43.8534,
532
+ "eval_samples_per_second": 22.803,
533
+ "eval_steps_per_second": 2.85,
534
+ "step": 350
535
+ },
536
+ {
537
+ "epoch": 4.8,
538
+ "grad_norm": 2.940281867980957,
539
+ "learning_rate": 3.733333333333334e-05,
540
+ "loss": 1.9319,
541
+ "step": 360
542
+ },
543
+ {
544
+ "epoch": 4.8,
545
+ "eval_loss": 2.7300503253936768,
546
+ "eval_runtime": 43.9017,
547
+ "eval_samples_per_second": 22.778,
548
+ "eval_steps_per_second": 2.847,
549
+ "step": 360
550
+ },
551
+ {
552
+ "epoch": 4.933333333333334,
553
+ "grad_norm": 2.8305609226226807,
554
+ "learning_rate": 3.614814814814815e-05,
555
+ "loss": 1.9332,
556
+ "step": 370
557
+ },
558
+ {
559
+ "epoch": 4.933333333333334,
560
+ "eval_loss": 2.7309281826019287,
561
+ "eval_runtime": 43.8842,
562
+ "eval_samples_per_second": 22.787,
563
+ "eval_steps_per_second": 2.848,
564
+ "step": 370
565
+ },
566
+ {
567
+ "epoch": 5.066666666666666,
568
+ "grad_norm": 2.8739213943481445,
569
+ "learning_rate": 3.4962962962962965e-05,
570
+ "loss": 1.8846,
571
+ "step": 380
572
+ },
573
+ {
574
+ "epoch": 5.066666666666666,
575
+ "eval_loss": 2.76513671875,
576
+ "eval_runtime": 43.906,
577
+ "eval_samples_per_second": 22.776,
578
+ "eval_steps_per_second": 2.847,
579
+ "step": 380
580
+ },
581
+ {
582
+ "epoch": 5.2,
583
+ "grad_norm": 3.9025838375091553,
584
+ "learning_rate": 3.377777777777778e-05,
585
+ "loss": 1.7575,
586
+ "step": 390
587
+ },
588
+ {
589
+ "epoch": 5.2,
590
+ "eval_loss": 2.847782611846924,
591
+ "eval_runtime": 43.8665,
592
+ "eval_samples_per_second": 22.796,
593
+ "eval_steps_per_second": 2.85,
594
+ "step": 390
595
+ },
596
+ {
597
+ "epoch": 5.333333333333333,
598
+ "grad_norm": 3.299649715423584,
599
+ "learning_rate": 3.259259259259259e-05,
600
+ "loss": 1.7713,
601
+ "step": 400
602
+ },
603
+ {
604
+ "epoch": 5.333333333333333,
605
+ "eval_loss": 2.8094286918640137,
606
+ "eval_runtime": 43.8629,
607
+ "eval_samples_per_second": 22.798,
608
+ "eval_steps_per_second": 2.85,
609
+ "step": 400
610
+ },
611
+ {
612
+ "epoch": 5.466666666666667,
613
+ "grad_norm": 3.4474265575408936,
614
+ "learning_rate": 3.140740740740741e-05,
615
+ "loss": 1.7983,
616
+ "step": 410
617
+ },
618
+ {
619
+ "epoch": 5.466666666666667,
620
+ "eval_loss": 2.827517509460449,
621
+ "eval_runtime": 43.8611,
622
+ "eval_samples_per_second": 22.799,
623
+ "eval_steps_per_second": 2.85,
624
+ "step": 410
625
+ },
626
+ {
627
+ "epoch": 5.6,
628
+ "grad_norm": 3.1924540996551514,
629
+ "learning_rate": 3.0222222222222225e-05,
630
+ "loss": 1.8091,
631
+ "step": 420
632
+ },
633
+ {
634
+ "epoch": 5.6,
635
+ "eval_loss": 2.81618332862854,
636
+ "eval_runtime": 43.8544,
637
+ "eval_samples_per_second": 22.803,
638
+ "eval_steps_per_second": 2.85,
639
+ "step": 420
640
+ },
641
+ {
642
+ "epoch": 5.733333333333333,
643
+ "grad_norm": 3.5224015712738037,
644
+ "learning_rate": 2.9037037037037042e-05,
645
+ "loss": 1.8253,
646
+ "step": 430
647
+ },
648
+ {
649
+ "epoch": 5.733333333333333,
650
+ "eval_loss": 2.816711187362671,
651
+ "eval_runtime": 43.8685,
652
+ "eval_samples_per_second": 22.795,
653
+ "eval_steps_per_second": 2.849,
654
+ "step": 430
655
+ },
656
+ {
657
+ "epoch": 5.866666666666667,
658
+ "grad_norm": 3.60918927192688,
659
+ "learning_rate": 2.7851851851851856e-05,
660
+ "loss": 1.8013,
661
+ "step": 440
662
+ },
663
+ {
664
+ "epoch": 5.866666666666667,
665
+ "eval_loss": 2.8146169185638428,
666
+ "eval_runtime": 43.8516,
667
+ "eval_samples_per_second": 22.804,
668
+ "eval_steps_per_second": 2.851,
669
+ "step": 440
670
+ },
671
+ {
672
+ "epoch": 6.0,
673
+ "grad_norm": 3.5798070430755615,
674
+ "learning_rate": 2.6666666666666667e-05,
675
+ "loss": 1.8258,
676
+ "step": 450
677
+ },
678
+ {
679
+ "epoch": 6.0,
680
+ "eval_loss": 2.8134233951568604,
681
+ "eval_runtime": 43.8442,
682
+ "eval_samples_per_second": 22.808,
683
+ "eval_steps_per_second": 2.851,
684
+ "step": 450
685
+ },
686
+ {
687
+ "epoch": 6.133333333333334,
688
+ "grad_norm": 5.563477993011475,
689
+ "learning_rate": 2.5481481481481484e-05,
690
+ "loss": 1.6649,
691
+ "step": 460
692
+ },
693
+ {
694
+ "epoch": 6.133333333333334,
695
+ "eval_loss": 2.9189789295196533,
696
+ "eval_runtime": 43.8602,
697
+ "eval_samples_per_second": 22.8,
698
+ "eval_steps_per_second": 2.85,
699
+ "step": 460
700
+ },
701
+ {
702
+ "epoch": 6.266666666666667,
703
+ "grad_norm": 4.192393779754639,
704
+ "learning_rate": 2.4296296296296298e-05,
705
+ "loss": 1.7443,
706
+ "step": 470
707
+ },
708
+ {
709
+ "epoch": 6.266666666666667,
710
+ "eval_loss": 2.893780469894409,
711
+ "eval_runtime": 43.8434,
712
+ "eval_samples_per_second": 22.808,
713
+ "eval_steps_per_second": 2.851,
714
+ "step": 470
715
+ },
716
+ {
717
+ "epoch": 6.4,
718
+ "grad_norm": 4.8650593757629395,
719
+ "learning_rate": 2.3111111111111112e-05,
720
+ "loss": 1.6961,
721
+ "step": 480
722
+ },
723
+ {
724
+ "epoch": 6.4,
725
+ "eval_loss": 2.8861398696899414,
726
+ "eval_runtime": 43.8417,
727
+ "eval_samples_per_second": 22.809,
728
+ "eval_steps_per_second": 2.851,
729
+ "step": 480
730
+ },
731
+ {
732
+ "epoch": 6.533333333333333,
733
+ "grad_norm": 3.844482660293579,
734
+ "learning_rate": 2.192592592592593e-05,
735
+ "loss": 1.6868,
736
+ "step": 490
737
+ },
738
+ {
739
+ "epoch": 6.533333333333333,
740
+ "eval_loss": 2.900317907333374,
741
+ "eval_runtime": 43.8557,
742
+ "eval_samples_per_second": 22.802,
743
+ "eval_steps_per_second": 2.85,
744
+ "step": 490
745
+ },
746
+ {
747
+ "epoch": 6.666666666666667,
748
+ "grad_norm": 4.230032920837402,
749
+ "learning_rate": 2.074074074074074e-05,
750
+ "loss": 1.6593,
751
+ "step": 500
752
+ },
753
+ {
754
+ "epoch": 6.666666666666667,
755
+ "eval_loss": 2.892076253890991,
756
+ "eval_runtime": 43.8479,
757
+ "eval_samples_per_second": 22.806,
758
+ "eval_steps_per_second": 2.851,
759
+ "step": 500
760
+ },
761
+ {
762
+ "epoch": 6.8,
763
+ "grad_norm": 4.427380561828613,
764
+ "learning_rate": 1.9555555555555557e-05,
765
+ "loss": 1.6777,
766
+ "step": 510
767
+ },
768
+ {
769
+ "epoch": 6.8,
770
+ "eval_loss": 2.8877696990966797,
771
+ "eval_runtime": 43.8489,
772
+ "eval_samples_per_second": 22.806,
773
+ "eval_steps_per_second": 2.851,
774
+ "step": 510
775
+ },
776
+ {
777
+ "epoch": 6.933333333333334,
778
+ "grad_norm": 4.23176908493042,
779
+ "learning_rate": 1.837037037037037e-05,
780
+ "loss": 1.7331,
781
+ "step": 520
782
+ },
783
+ {
784
+ "epoch": 6.933333333333334,
785
+ "eval_loss": 2.889272928237915,
786
+ "eval_runtime": 43.8577,
787
+ "eval_samples_per_second": 22.801,
788
+ "eval_steps_per_second": 2.85,
789
+ "step": 520
790
+ },
791
+ {
792
+ "epoch": 7.066666666666666,
793
+ "grad_norm": 3.9098429679870605,
794
+ "learning_rate": 1.7185185185185185e-05,
795
+ "loss": 1.6741,
796
+ "step": 530
797
+ },
798
+ {
799
+ "epoch": 7.066666666666666,
800
+ "eval_loss": 2.9202494621276855,
801
+ "eval_runtime": 43.8571,
802
+ "eval_samples_per_second": 22.801,
803
+ "eval_steps_per_second": 2.85,
804
+ "step": 530
805
+ },
806
+ {
807
+ "epoch": 7.2,
808
+ "grad_norm": 4.320191383361816,
809
+ "learning_rate": 1.6000000000000003e-05,
810
+ "loss": 1.5711,
811
+ "step": 540
812
+ },
813
+ {
814
+ "epoch": 7.2,
815
+ "eval_loss": 2.97855806350708,
816
+ "eval_runtime": 43.8599,
817
+ "eval_samples_per_second": 22.8,
818
+ "eval_steps_per_second": 2.85,
819
+ "step": 540
820
+ },
821
+ {
822
+ "epoch": 7.333333333333333,
823
+ "grad_norm": 4.003049850463867,
824
+ "learning_rate": 1.4814814814814815e-05,
825
+ "loss": 1.6106,
826
+ "step": 550
827
+ },
828
+ {
829
+ "epoch": 7.333333333333333,
830
+ "eval_loss": 2.9440739154815674,
831
+ "eval_runtime": 43.8605,
832
+ "eval_samples_per_second": 22.8,
833
+ "eval_steps_per_second": 2.85,
834
+ "step": 550
835
+ },
836
+ {
837
+ "epoch": 7.466666666666667,
838
+ "grad_norm": 4.265935897827148,
839
+ "learning_rate": 1.362962962962963e-05,
840
+ "loss": 1.6241,
841
+ "step": 560
842
+ },
843
+ {
844
+ "epoch": 7.466666666666667,
845
+ "eval_loss": 2.958505630493164,
846
+ "eval_runtime": 43.8614,
847
+ "eval_samples_per_second": 22.799,
848
+ "eval_steps_per_second": 2.85,
849
+ "step": 560
850
+ }
851
+ ],
852
+ "logging_steps": 10,
853
+ "max_steps": 675,
854
+ "num_input_tokens_seen": 0,
855
+ "num_train_epochs": 9,
856
+ "save_steps": 10,
857
+ "stateful_callbacks": {
858
+ "TrainerControl": {
859
+ "args": {
860
+ "should_epoch_stop": false,
861
+ "should_evaluate": false,
862
+ "should_log": false,
863
+ "should_save": true,
864
+ "should_training_stop": false
865
+ },
866
+ "attributes": {}
867
+ }
868
+ },
869
+ "total_flos": 9.17620031225856e+16,
870
+ "train_batch_size": 8,
871
+ "trial_name": null,
872
+ "trial_params": null
873
+ }
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-570/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/pythia-6_9b
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-570/adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/workspace/pythia-6_9b",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.1,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 8,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "dense_h_to_4h",
24
+ "query_key_value",
25
+ "dense",
26
+ "dense_4h_to_h"
27
+ ],
28
+ "task_type": "CAUSAL_LM",
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-570/trainer_state.json ADDED
@@ -0,0 +1,888 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 2.535032033920288,
3
+ "best_model_checkpoint": "./output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-150",
4
+ "epoch": 7.6,
5
+ "eval_steps": 10,
6
+ "global_step": 570,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.13333333333333333,
13
+ "grad_norm": 0.36938729882240295,
14
+ "learning_rate": 7.881481481481482e-05,
15
+ "loss": 2.519,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.13333333333333333,
20
+ "eval_loss": 2.579638957977295,
21
+ "eval_runtime": 43.8215,
22
+ "eval_samples_per_second": 22.82,
23
+ "eval_steps_per_second": 2.852,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.26666666666666666,
28
+ "grad_norm": 0.39850670099258423,
29
+ "learning_rate": 7.762962962962963e-05,
30
+ "loss": 2.5224,
31
+ "step": 20
32
+ },
33
+ {
34
+ "epoch": 0.26666666666666666,
35
+ "eval_loss": 2.5729691982269287,
36
+ "eval_runtime": 43.8179,
37
+ "eval_samples_per_second": 22.822,
38
+ "eval_steps_per_second": 2.853,
39
+ "step": 20
40
+ },
41
+ {
42
+ "epoch": 0.4,
43
+ "grad_norm": 0.40211933851242065,
44
+ "learning_rate": 7.644444444444445e-05,
45
+ "loss": 2.5169,
46
+ "step": 30
47
+ },
48
+ {
49
+ "epoch": 0.4,
50
+ "eval_loss": 2.567735433578491,
51
+ "eval_runtime": 43.8366,
52
+ "eval_samples_per_second": 22.812,
53
+ "eval_steps_per_second": 2.851,
54
+ "step": 30
55
+ },
56
+ {
57
+ "epoch": 0.5333333333333333,
58
+ "grad_norm": 0.6892333030700684,
59
+ "learning_rate": 7.525925925925926e-05,
60
+ "loss": 2.5784,
61
+ "step": 40
62
+ },
63
+ {
64
+ "epoch": 0.5333333333333333,
65
+ "eval_loss": 2.562650442123413,
66
+ "eval_runtime": 43.8377,
67
+ "eval_samples_per_second": 22.811,
68
+ "eval_steps_per_second": 2.851,
69
+ "step": 40
70
+ },
71
+ {
72
+ "epoch": 0.6666666666666666,
73
+ "grad_norm": 0.442343533039093,
74
+ "learning_rate": 7.407407407407409e-05,
75
+ "loss": 2.5431,
76
+ "step": 50
77
+ },
78
+ {
79
+ "epoch": 0.6666666666666666,
80
+ "eval_loss": 2.556513786315918,
81
+ "eval_runtime": 43.8656,
82
+ "eval_samples_per_second": 22.797,
83
+ "eval_steps_per_second": 2.85,
84
+ "step": 50
85
+ },
86
+ {
87
+ "epoch": 0.8,
88
+ "grad_norm": 0.4059845805168152,
89
+ "learning_rate": 7.28888888888889e-05,
90
+ "loss": 2.4936,
91
+ "step": 60
92
+ },
93
+ {
94
+ "epoch": 0.8,
95
+ "eval_loss": 2.552133798599243,
96
+ "eval_runtime": 43.8403,
97
+ "eval_samples_per_second": 22.81,
98
+ "eval_steps_per_second": 2.851,
99
+ "step": 60
100
+ },
101
+ {
102
+ "epoch": 0.9333333333333333,
103
+ "grad_norm": 0.48126307129859924,
104
+ "learning_rate": 7.170370370370371e-05,
105
+ "loss": 2.4901,
106
+ "step": 70
107
+ },
108
+ {
109
+ "epoch": 0.9333333333333333,
110
+ "eval_loss": 2.5477023124694824,
111
+ "eval_runtime": 43.8351,
112
+ "eval_samples_per_second": 22.813,
113
+ "eval_steps_per_second": 2.852,
114
+ "step": 70
115
+ },
116
+ {
117
+ "epoch": 1.0666666666666667,
118
+ "grad_norm": 0.48629865050315857,
119
+ "learning_rate": 7.051851851851853e-05,
120
+ "loss": 2.5114,
121
+ "step": 80
122
+ },
123
+ {
124
+ "epoch": 1.0666666666666667,
125
+ "eval_loss": 2.543431043624878,
126
+ "eval_runtime": 43.8432,
127
+ "eval_samples_per_second": 22.809,
128
+ "eval_steps_per_second": 2.851,
129
+ "step": 80
130
+ },
131
+ {
132
+ "epoch": 1.2,
133
+ "grad_norm": 0.5880796313285828,
134
+ "learning_rate": 6.933333333333334e-05,
135
+ "loss": 2.4446,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 1.2,
140
+ "eval_loss": 2.544339418411255,
141
+ "eval_runtime": 43.8437,
142
+ "eval_samples_per_second": 22.808,
143
+ "eval_steps_per_second": 2.851,
144
+ "step": 90
145
+ },
146
+ {
147
+ "epoch": 1.3333333333333333,
148
+ "grad_norm": 0.6746829748153687,
149
+ "learning_rate": 6.814814814814815e-05,
150
+ "loss": 2.4477,
151
+ "step": 100
152
+ },
153
+ {
154
+ "epoch": 1.3333333333333333,
155
+ "eval_loss": 2.544358968734741,
156
+ "eval_runtime": 43.8613,
157
+ "eval_samples_per_second": 22.799,
158
+ "eval_steps_per_second": 2.85,
159
+ "step": 100
160
+ },
161
+ {
162
+ "epoch": 1.4666666666666668,
163
+ "grad_norm": 0.8208937048912048,
164
+ "learning_rate": 6.696296296296296e-05,
165
+ "loss": 2.4004,
166
+ "step": 110
167
+ },
168
+ {
169
+ "epoch": 1.4666666666666668,
170
+ "eval_loss": 2.54068660736084,
171
+ "eval_runtime": 43.8426,
172
+ "eval_samples_per_second": 22.809,
173
+ "eval_steps_per_second": 2.851,
174
+ "step": 110
175
+ },
176
+ {
177
+ "epoch": 1.6,
178
+ "grad_norm": 0.925931453704834,
179
+ "learning_rate": 6.577777777777777e-05,
180
+ "loss": 2.3889,
181
+ "step": 120
182
+ },
183
+ {
184
+ "epoch": 1.6,
185
+ "eval_loss": 2.5393033027648926,
186
+ "eval_runtime": 43.8383,
187
+ "eval_samples_per_second": 22.811,
188
+ "eval_steps_per_second": 2.851,
189
+ "step": 120
190
+ },
191
+ {
192
+ "epoch": 1.7333333333333334,
193
+ "grad_norm": 0.8785662055015564,
194
+ "learning_rate": 6.45925925925926e-05,
195
+ "loss": 2.3959,
196
+ "step": 130
197
+ },
198
+ {
199
+ "epoch": 1.7333333333333334,
200
+ "eval_loss": 2.5367038249969482,
201
+ "eval_runtime": 43.8508,
202
+ "eval_samples_per_second": 22.805,
203
+ "eval_steps_per_second": 2.851,
204
+ "step": 130
205
+ },
206
+ {
207
+ "epoch": 1.8666666666666667,
208
+ "grad_norm": 0.941368818283081,
209
+ "learning_rate": 6.340740740740741e-05,
210
+ "loss": 2.3924,
211
+ "step": 140
212
+ },
213
+ {
214
+ "epoch": 1.8666666666666667,
215
+ "eval_loss": 2.535139560699463,
216
+ "eval_runtime": 43.8588,
217
+ "eval_samples_per_second": 22.8,
218
+ "eval_steps_per_second": 2.85,
219
+ "step": 140
220
+ },
221
+ {
222
+ "epoch": 2.0,
223
+ "grad_norm": 0.9578835368156433,
224
+ "learning_rate": 6.222222222222223e-05,
225
+ "loss": 2.4278,
226
+ "step": 150
227
+ },
228
+ {
229
+ "epoch": 2.0,
230
+ "eval_loss": 2.535032033920288,
231
+ "eval_runtime": 43.8484,
232
+ "eval_samples_per_second": 22.806,
233
+ "eval_steps_per_second": 2.851,
234
+ "step": 150
235
+ },
236
+ {
237
+ "epoch": 2.1333333333333333,
238
+ "grad_norm": 1.1541856527328491,
239
+ "learning_rate": 6.103703703703704e-05,
240
+ "loss": 2.2895,
241
+ "step": 160
242
+ },
243
+ {
244
+ "epoch": 2.1333333333333333,
245
+ "eval_loss": 2.564768075942993,
246
+ "eval_runtime": 43.8568,
247
+ "eval_samples_per_second": 22.801,
248
+ "eval_steps_per_second": 2.85,
249
+ "step": 160
250
+ },
251
+ {
252
+ "epoch": 2.2666666666666666,
253
+ "grad_norm": 1.4076604843139648,
254
+ "learning_rate": 5.9851851851851855e-05,
255
+ "loss": 2.2107,
256
+ "step": 170
257
+ },
258
+ {
259
+ "epoch": 2.2666666666666666,
260
+ "eval_loss": 2.5832314491271973,
261
+ "eval_runtime": 43.8455,
262
+ "eval_samples_per_second": 22.807,
263
+ "eval_steps_per_second": 2.851,
264
+ "step": 170
265
+ },
266
+ {
267
+ "epoch": 2.4,
268
+ "grad_norm": 1.4847813844680786,
269
+ "learning_rate": 5.8666666666666665e-05,
270
+ "loss": 2.2588,
271
+ "step": 180
272
+ },
273
+ {
274
+ "epoch": 2.4,
275
+ "eval_loss": 2.5781586170196533,
276
+ "eval_runtime": 43.8578,
277
+ "eval_samples_per_second": 22.801,
278
+ "eval_steps_per_second": 2.85,
279
+ "step": 180
280
+ },
281
+ {
282
+ "epoch": 2.533333333333333,
283
+ "grad_norm": 1.5135377645492554,
284
+ "learning_rate": 5.748148148148149e-05,
285
+ "loss": 2.2099,
286
+ "step": 190
287
+ },
288
+ {
289
+ "epoch": 2.533333333333333,
290
+ "eval_loss": 2.5752007961273193,
291
+ "eval_runtime": 43.8521,
292
+ "eval_samples_per_second": 22.804,
293
+ "eval_steps_per_second": 2.85,
294
+ "step": 190
295
+ },
296
+ {
297
+ "epoch": 2.6666666666666665,
298
+ "grad_norm": 1.5297592878341675,
299
+ "learning_rate": 5.62962962962963e-05,
300
+ "loss": 2.2965,
301
+ "step": 200
302
+ },
303
+ {
304
+ "epoch": 2.6666666666666665,
305
+ "eval_loss": 2.579918622970581,
306
+ "eval_runtime": 43.8661,
307
+ "eval_samples_per_second": 22.797,
308
+ "eval_steps_per_second": 2.85,
309
+ "step": 200
310
+ },
311
+ {
312
+ "epoch": 2.8,
313
+ "grad_norm": 1.6282892227172852,
314
+ "learning_rate": 5.511111111111112e-05,
315
+ "loss": 2.2487,
316
+ "step": 210
317
+ },
318
+ {
319
+ "epoch": 2.8,
320
+ "eval_loss": 2.5760037899017334,
321
+ "eval_runtime": 43.8379,
322
+ "eval_samples_per_second": 22.811,
323
+ "eval_steps_per_second": 2.851,
324
+ "step": 210
325
+ },
326
+ {
327
+ "epoch": 2.9333333333333336,
328
+ "grad_norm": 1.74424409866333,
329
+ "learning_rate": 5.392592592592593e-05,
330
+ "loss": 2.2049,
331
+ "step": 220
332
+ },
333
+ {
334
+ "epoch": 2.9333333333333336,
335
+ "eval_loss": 2.576190233230591,
336
+ "eval_runtime": 43.8491,
337
+ "eval_samples_per_second": 22.805,
338
+ "eval_steps_per_second": 2.851,
339
+ "step": 220
340
+ },
341
+ {
342
+ "epoch": 3.066666666666667,
343
+ "grad_norm": 1.654069423675537,
344
+ "learning_rate": 5.274074074074074e-05,
345
+ "loss": 2.1188,
346
+ "step": 230
347
+ },
348
+ {
349
+ "epoch": 3.066666666666667,
350
+ "eval_loss": 2.5971405506134033,
351
+ "eval_runtime": 43.855,
352
+ "eval_samples_per_second": 22.802,
353
+ "eval_steps_per_second": 2.85,
354
+ "step": 230
355
+ },
356
+ {
357
+ "epoch": 3.2,
358
+ "grad_norm": 2.541767120361328,
359
+ "learning_rate": 5.155555555555556e-05,
360
+ "loss": 2.0788,
361
+ "step": 240
362
+ },
363
+ {
364
+ "epoch": 3.2,
365
+ "eval_loss": 2.6767666339874268,
366
+ "eval_runtime": 43.8368,
367
+ "eval_samples_per_second": 22.812,
368
+ "eval_steps_per_second": 2.851,
369
+ "step": 240
370
+ },
371
+ {
372
+ "epoch": 3.3333333333333335,
373
+ "grad_norm": 2.0508077144622803,
374
+ "learning_rate": 5.037037037037037e-05,
375
+ "loss": 2.0784,
376
+ "step": 250
377
+ },
378
+ {
379
+ "epoch": 3.3333333333333335,
380
+ "eval_loss": 2.6486454010009766,
381
+ "eval_runtime": 43.8529,
382
+ "eval_samples_per_second": 22.803,
383
+ "eval_steps_per_second": 2.85,
384
+ "step": 250
385
+ },
386
+ {
387
+ "epoch": 3.466666666666667,
388
+ "grad_norm": 2.1096036434173584,
389
+ "learning_rate": 4.918518518518519e-05,
390
+ "loss": 2.0633,
391
+ "step": 260
392
+ },
393
+ {
394
+ "epoch": 3.466666666666667,
395
+ "eval_loss": 2.6501405239105225,
396
+ "eval_runtime": 43.8632,
397
+ "eval_samples_per_second": 22.798,
398
+ "eval_steps_per_second": 2.85,
399
+ "step": 260
400
+ },
401
+ {
402
+ "epoch": 3.6,
403
+ "grad_norm": 2.3028736114501953,
404
+ "learning_rate": 4.8e-05,
405
+ "loss": 2.0722,
406
+ "step": 270
407
+ },
408
+ {
409
+ "epoch": 3.6,
410
+ "eval_loss": 2.657053232192993,
411
+ "eval_runtime": 43.8423,
412
+ "eval_samples_per_second": 22.809,
413
+ "eval_steps_per_second": 2.851,
414
+ "step": 270
415
+ },
416
+ {
417
+ "epoch": 3.7333333333333334,
418
+ "grad_norm": 2.1536757946014404,
419
+ "learning_rate": 4.681481481481481e-05,
420
+ "loss": 2.0155,
421
+ "step": 280
422
+ },
423
+ {
424
+ "epoch": 3.7333333333333334,
425
+ "eval_loss": 2.648275375366211,
426
+ "eval_runtime": 43.8328,
427
+ "eval_samples_per_second": 22.814,
428
+ "eval_steps_per_second": 2.852,
429
+ "step": 280
430
+ },
431
+ {
432
+ "epoch": 3.8666666666666667,
433
+ "grad_norm": 2.4079270362854004,
434
+ "learning_rate": 4.5629629629629636e-05,
435
+ "loss": 2.1111,
436
+ "step": 290
437
+ },
438
+ {
439
+ "epoch": 3.8666666666666667,
440
+ "eval_loss": 2.650322675704956,
441
+ "eval_runtime": 43.835,
442
+ "eval_samples_per_second": 22.813,
443
+ "eval_steps_per_second": 2.852,
444
+ "step": 290
445
+ },
446
+ {
447
+ "epoch": 4.0,
448
+ "grad_norm": 2.426234722137451,
449
+ "learning_rate": 4.444444444444445e-05,
450
+ "loss": 2.041,
451
+ "step": 300
452
+ },
453
+ {
454
+ "epoch": 4.0,
455
+ "eval_loss": 2.6490862369537354,
456
+ "eval_runtime": 43.845,
457
+ "eval_samples_per_second": 22.808,
458
+ "eval_steps_per_second": 2.851,
459
+ "step": 300
460
+ },
461
+ {
462
+ "epoch": 4.133333333333334,
463
+ "grad_norm": 2.8063745498657227,
464
+ "learning_rate": 4.3259259259259264e-05,
465
+ "loss": 1.9316,
466
+ "step": 310
467
+ },
468
+ {
469
+ "epoch": 4.133333333333334,
470
+ "eval_loss": 2.7609620094299316,
471
+ "eval_runtime": 43.8481,
472
+ "eval_samples_per_second": 22.806,
473
+ "eval_steps_per_second": 2.851,
474
+ "step": 310
475
+ },
476
+ {
477
+ "epoch": 4.266666666666667,
478
+ "grad_norm": 2.96854305267334,
479
+ "learning_rate": 4.2074074074074075e-05,
480
+ "loss": 1.8889,
481
+ "step": 320
482
+ },
483
+ {
484
+ "epoch": 4.266666666666667,
485
+ "eval_loss": 2.736968994140625,
486
+ "eval_runtime": 43.8633,
487
+ "eval_samples_per_second": 22.798,
488
+ "eval_steps_per_second": 2.85,
489
+ "step": 320
490
+ },
491
+ {
492
+ "epoch": 4.4,
493
+ "grad_norm": 2.637695789337158,
494
+ "learning_rate": 4.088888888888889e-05,
495
+ "loss": 1.9187,
496
+ "step": 330
497
+ },
498
+ {
499
+ "epoch": 4.4,
500
+ "eval_loss": 2.7382876873016357,
501
+ "eval_runtime": 43.8486,
502
+ "eval_samples_per_second": 22.806,
503
+ "eval_steps_per_second": 2.851,
504
+ "step": 330
505
+ },
506
+ {
507
+ "epoch": 4.533333333333333,
508
+ "grad_norm": 2.9106290340423584,
509
+ "learning_rate": 3.970370370370371e-05,
510
+ "loss": 1.9002,
511
+ "step": 340
512
+ },
513
+ {
514
+ "epoch": 4.533333333333333,
515
+ "eval_loss": 2.734544515609741,
516
+ "eval_runtime": 43.8491,
517
+ "eval_samples_per_second": 22.805,
518
+ "eval_steps_per_second": 2.851,
519
+ "step": 340
520
+ },
521
+ {
522
+ "epoch": 4.666666666666667,
523
+ "grad_norm": 2.769315481185913,
524
+ "learning_rate": 3.851851851851852e-05,
525
+ "loss": 1.9251,
526
+ "step": 350
527
+ },
528
+ {
529
+ "epoch": 4.666666666666667,
530
+ "eval_loss": 2.734708070755005,
531
+ "eval_runtime": 43.8534,
532
+ "eval_samples_per_second": 22.803,
533
+ "eval_steps_per_second": 2.85,
534
+ "step": 350
535
+ },
536
+ {
537
+ "epoch": 4.8,
538
+ "grad_norm": 2.940281867980957,
539
+ "learning_rate": 3.733333333333334e-05,
540
+ "loss": 1.9319,
541
+ "step": 360
542
+ },
543
+ {
544
+ "epoch": 4.8,
545
+ "eval_loss": 2.7300503253936768,
546
+ "eval_runtime": 43.9017,
547
+ "eval_samples_per_second": 22.778,
548
+ "eval_steps_per_second": 2.847,
549
+ "step": 360
550
+ },
551
+ {
552
+ "epoch": 4.933333333333334,
553
+ "grad_norm": 2.8305609226226807,
554
+ "learning_rate": 3.614814814814815e-05,
555
+ "loss": 1.9332,
556
+ "step": 370
557
+ },
558
+ {
559
+ "epoch": 4.933333333333334,
560
+ "eval_loss": 2.7309281826019287,
561
+ "eval_runtime": 43.8842,
562
+ "eval_samples_per_second": 22.787,
563
+ "eval_steps_per_second": 2.848,
564
+ "step": 370
565
+ },
566
+ {
567
+ "epoch": 5.066666666666666,
568
+ "grad_norm": 2.8739213943481445,
569
+ "learning_rate": 3.4962962962962965e-05,
570
+ "loss": 1.8846,
571
+ "step": 380
572
+ },
573
+ {
574
+ "epoch": 5.066666666666666,
575
+ "eval_loss": 2.76513671875,
576
+ "eval_runtime": 43.906,
577
+ "eval_samples_per_second": 22.776,
578
+ "eval_steps_per_second": 2.847,
579
+ "step": 380
580
+ },
581
+ {
582
+ "epoch": 5.2,
583
+ "grad_norm": 3.9025838375091553,
584
+ "learning_rate": 3.377777777777778e-05,
585
+ "loss": 1.7575,
586
+ "step": 390
587
+ },
588
+ {
589
+ "epoch": 5.2,
590
+ "eval_loss": 2.847782611846924,
591
+ "eval_runtime": 43.8665,
592
+ "eval_samples_per_second": 22.796,
593
+ "eval_steps_per_second": 2.85,
594
+ "step": 390
595
+ },
596
+ {
597
+ "epoch": 5.333333333333333,
598
+ "grad_norm": 3.299649715423584,
599
+ "learning_rate": 3.259259259259259e-05,
600
+ "loss": 1.7713,
601
+ "step": 400
602
+ },
603
+ {
604
+ "epoch": 5.333333333333333,
605
+ "eval_loss": 2.8094286918640137,
606
+ "eval_runtime": 43.8629,
607
+ "eval_samples_per_second": 22.798,
608
+ "eval_steps_per_second": 2.85,
609
+ "step": 400
610
+ },
611
+ {
612
+ "epoch": 5.466666666666667,
613
+ "grad_norm": 3.4474265575408936,
614
+ "learning_rate": 3.140740740740741e-05,
615
+ "loss": 1.7983,
616
+ "step": 410
617
+ },
618
+ {
619
+ "epoch": 5.466666666666667,
620
+ "eval_loss": 2.827517509460449,
621
+ "eval_runtime": 43.8611,
622
+ "eval_samples_per_second": 22.799,
623
+ "eval_steps_per_second": 2.85,
624
+ "step": 410
625
+ },
626
+ {
627
+ "epoch": 5.6,
628
+ "grad_norm": 3.1924540996551514,
629
+ "learning_rate": 3.0222222222222225e-05,
630
+ "loss": 1.8091,
631
+ "step": 420
632
+ },
633
+ {
634
+ "epoch": 5.6,
635
+ "eval_loss": 2.81618332862854,
636
+ "eval_runtime": 43.8544,
637
+ "eval_samples_per_second": 22.803,
638
+ "eval_steps_per_second": 2.85,
639
+ "step": 420
640
+ },
641
+ {
642
+ "epoch": 5.733333333333333,
643
+ "grad_norm": 3.5224015712738037,
644
+ "learning_rate": 2.9037037037037042e-05,
645
+ "loss": 1.8253,
646
+ "step": 430
647
+ },
648
+ {
649
+ "epoch": 5.733333333333333,
650
+ "eval_loss": 2.816711187362671,
651
+ "eval_runtime": 43.8685,
652
+ "eval_samples_per_second": 22.795,
653
+ "eval_steps_per_second": 2.849,
654
+ "step": 430
655
+ },
656
+ {
657
+ "epoch": 5.866666666666667,
658
+ "grad_norm": 3.60918927192688,
659
+ "learning_rate": 2.7851851851851856e-05,
660
+ "loss": 1.8013,
661
+ "step": 440
662
+ },
663
+ {
664
+ "epoch": 5.866666666666667,
665
+ "eval_loss": 2.8146169185638428,
666
+ "eval_runtime": 43.8516,
667
+ "eval_samples_per_second": 22.804,
668
+ "eval_steps_per_second": 2.851,
669
+ "step": 440
670
+ },
671
+ {
672
+ "epoch": 6.0,
673
+ "grad_norm": 3.5798070430755615,
674
+ "learning_rate": 2.6666666666666667e-05,
675
+ "loss": 1.8258,
676
+ "step": 450
677
+ },
678
+ {
679
+ "epoch": 6.0,
680
+ "eval_loss": 2.8134233951568604,
681
+ "eval_runtime": 43.8442,
682
+ "eval_samples_per_second": 22.808,
683
+ "eval_steps_per_second": 2.851,
684
+ "step": 450
685
+ },
686
+ {
687
+ "epoch": 6.133333333333334,
688
+ "grad_norm": 5.563477993011475,
689
+ "learning_rate": 2.5481481481481484e-05,
690
+ "loss": 1.6649,
691
+ "step": 460
692
+ },
693
+ {
694
+ "epoch": 6.133333333333334,
695
+ "eval_loss": 2.9189789295196533,
696
+ "eval_runtime": 43.8602,
697
+ "eval_samples_per_second": 22.8,
698
+ "eval_steps_per_second": 2.85,
699
+ "step": 460
700
+ },
701
+ {
702
+ "epoch": 6.266666666666667,
703
+ "grad_norm": 4.192393779754639,
704
+ "learning_rate": 2.4296296296296298e-05,
705
+ "loss": 1.7443,
706
+ "step": 470
707
+ },
708
+ {
709
+ "epoch": 6.266666666666667,
710
+ "eval_loss": 2.893780469894409,
711
+ "eval_runtime": 43.8434,
712
+ "eval_samples_per_second": 22.808,
713
+ "eval_steps_per_second": 2.851,
714
+ "step": 470
715
+ },
716
+ {
717
+ "epoch": 6.4,
718
+ "grad_norm": 4.8650593757629395,
719
+ "learning_rate": 2.3111111111111112e-05,
720
+ "loss": 1.6961,
721
+ "step": 480
722
+ },
723
+ {
724
+ "epoch": 6.4,
725
+ "eval_loss": 2.8861398696899414,
726
+ "eval_runtime": 43.8417,
727
+ "eval_samples_per_second": 22.809,
728
+ "eval_steps_per_second": 2.851,
729
+ "step": 480
730
+ },
731
+ {
732
+ "epoch": 6.533333333333333,
733
+ "grad_norm": 3.844482660293579,
734
+ "learning_rate": 2.192592592592593e-05,
735
+ "loss": 1.6868,
736
+ "step": 490
737
+ },
738
+ {
739
+ "epoch": 6.533333333333333,
740
+ "eval_loss": 2.900317907333374,
741
+ "eval_runtime": 43.8557,
742
+ "eval_samples_per_second": 22.802,
743
+ "eval_steps_per_second": 2.85,
744
+ "step": 490
745
+ },
746
+ {
747
+ "epoch": 6.666666666666667,
748
+ "grad_norm": 4.230032920837402,
749
+ "learning_rate": 2.074074074074074e-05,
750
+ "loss": 1.6593,
751
+ "step": 500
752
+ },
753
+ {
754
+ "epoch": 6.666666666666667,
755
+ "eval_loss": 2.892076253890991,
756
+ "eval_runtime": 43.8479,
757
+ "eval_samples_per_second": 22.806,
758
+ "eval_steps_per_second": 2.851,
759
+ "step": 500
760
+ },
761
+ {
762
+ "epoch": 6.8,
763
+ "grad_norm": 4.427380561828613,
764
+ "learning_rate": 1.9555555555555557e-05,
765
+ "loss": 1.6777,
766
+ "step": 510
767
+ },
768
+ {
769
+ "epoch": 6.8,
770
+ "eval_loss": 2.8877696990966797,
771
+ "eval_runtime": 43.8489,
772
+ "eval_samples_per_second": 22.806,
773
+ "eval_steps_per_second": 2.851,
774
+ "step": 510
775
+ },
776
+ {
777
+ "epoch": 6.933333333333334,
778
+ "grad_norm": 4.23176908493042,
779
+ "learning_rate": 1.837037037037037e-05,
780
+ "loss": 1.7331,
781
+ "step": 520
782
+ },
783
+ {
784
+ "epoch": 6.933333333333334,
785
+ "eval_loss": 2.889272928237915,
786
+ "eval_runtime": 43.8577,
787
+ "eval_samples_per_second": 22.801,
788
+ "eval_steps_per_second": 2.85,
789
+ "step": 520
790
+ },
791
+ {
792
+ "epoch": 7.066666666666666,
793
+ "grad_norm": 3.9098429679870605,
794
+ "learning_rate": 1.7185185185185185e-05,
795
+ "loss": 1.6741,
796
+ "step": 530
797
+ },
798
+ {
799
+ "epoch": 7.066666666666666,
800
+ "eval_loss": 2.9202494621276855,
801
+ "eval_runtime": 43.8571,
802
+ "eval_samples_per_second": 22.801,
803
+ "eval_steps_per_second": 2.85,
804
+ "step": 530
805
+ },
806
+ {
807
+ "epoch": 7.2,
808
+ "grad_norm": 4.320191383361816,
809
+ "learning_rate": 1.6000000000000003e-05,
810
+ "loss": 1.5711,
811
+ "step": 540
812
+ },
813
+ {
814
+ "epoch": 7.2,
815
+ "eval_loss": 2.97855806350708,
816
+ "eval_runtime": 43.8599,
817
+ "eval_samples_per_second": 22.8,
818
+ "eval_steps_per_second": 2.85,
819
+ "step": 540
820
+ },
821
+ {
822
+ "epoch": 7.333333333333333,
823
+ "grad_norm": 4.003049850463867,
824
+ "learning_rate": 1.4814814814814815e-05,
825
+ "loss": 1.6106,
826
+ "step": 550
827
+ },
828
+ {
829
+ "epoch": 7.333333333333333,
830
+ "eval_loss": 2.9440739154815674,
831
+ "eval_runtime": 43.8605,
832
+ "eval_samples_per_second": 22.8,
833
+ "eval_steps_per_second": 2.85,
834
+ "step": 550
835
+ },
836
+ {
837
+ "epoch": 7.466666666666667,
838
+ "grad_norm": 4.265935897827148,
839
+ "learning_rate": 1.362962962962963e-05,
840
+ "loss": 1.6241,
841
+ "step": 560
842
+ },
843
+ {
844
+ "epoch": 7.466666666666667,
845
+ "eval_loss": 2.958505630493164,
846
+ "eval_runtime": 43.8614,
847
+ "eval_samples_per_second": 22.799,
848
+ "eval_steps_per_second": 2.85,
849
+ "step": 560
850
+ },
851
+ {
852
+ "epoch": 7.6,
853
+ "grad_norm": 5.025564670562744,
854
+ "learning_rate": 1.2444444444444446e-05,
855
+ "loss": 1.6306,
856
+ "step": 570
857
+ },
858
+ {
859
+ "epoch": 7.6,
860
+ "eval_loss": 2.956601619720459,
861
+ "eval_runtime": 43.8595,
862
+ "eval_samples_per_second": 22.8,
863
+ "eval_steps_per_second": 2.85,
864
+ "step": 570
865
+ }
866
+ ],
867
+ "logging_steps": 10,
868
+ "max_steps": 675,
869
+ "num_input_tokens_seen": 0,
870
+ "num_train_epochs": 9,
871
+ "save_steps": 10,
872
+ "stateful_callbacks": {
873
+ "TrainerControl": {
874
+ "args": {
875
+ "should_epoch_stop": false,
876
+ "should_evaluate": false,
877
+ "should_log": false,
878
+ "should_save": true,
879
+ "should_training_stop": false
880
+ },
881
+ "attributes": {}
882
+ }
883
+ },
884
+ "total_flos": 9.34006103212032e+16,
885
+ "train_batch_size": 8,
886
+ "trial_name": null,
887
+ "trial_params": null
888
+ }
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-580/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/pythia-6_9b
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-580/adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/workspace/pythia-6_9b",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.1,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 8,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "dense_h_to_4h",
24
+ "query_key_value",
25
+ "dense",
26
+ "dense_4h_to_h"
27
+ ],
28
+ "task_type": "CAUSAL_LM",
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-580/trainer_state.json ADDED
@@ -0,0 +1,903 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 2.535032033920288,
3
+ "best_model_checkpoint": "./output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-150",
4
+ "epoch": 7.733333333333333,
5
+ "eval_steps": 10,
6
+ "global_step": 580,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.13333333333333333,
13
+ "grad_norm": 0.36938729882240295,
14
+ "learning_rate": 7.881481481481482e-05,
15
+ "loss": 2.519,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.13333333333333333,
20
+ "eval_loss": 2.579638957977295,
21
+ "eval_runtime": 43.8215,
22
+ "eval_samples_per_second": 22.82,
23
+ "eval_steps_per_second": 2.852,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.26666666666666666,
28
+ "grad_norm": 0.39850670099258423,
29
+ "learning_rate": 7.762962962962963e-05,
30
+ "loss": 2.5224,
31
+ "step": 20
32
+ },
33
+ {
34
+ "epoch": 0.26666666666666666,
35
+ "eval_loss": 2.5729691982269287,
36
+ "eval_runtime": 43.8179,
37
+ "eval_samples_per_second": 22.822,
38
+ "eval_steps_per_second": 2.853,
39
+ "step": 20
40
+ },
41
+ {
42
+ "epoch": 0.4,
43
+ "grad_norm": 0.40211933851242065,
44
+ "learning_rate": 7.644444444444445e-05,
45
+ "loss": 2.5169,
46
+ "step": 30
47
+ },
48
+ {
49
+ "epoch": 0.4,
50
+ "eval_loss": 2.567735433578491,
51
+ "eval_runtime": 43.8366,
52
+ "eval_samples_per_second": 22.812,
53
+ "eval_steps_per_second": 2.851,
54
+ "step": 30
55
+ },
56
+ {
57
+ "epoch": 0.5333333333333333,
58
+ "grad_norm": 0.6892333030700684,
59
+ "learning_rate": 7.525925925925926e-05,
60
+ "loss": 2.5784,
61
+ "step": 40
62
+ },
63
+ {
64
+ "epoch": 0.5333333333333333,
65
+ "eval_loss": 2.562650442123413,
66
+ "eval_runtime": 43.8377,
67
+ "eval_samples_per_second": 22.811,
68
+ "eval_steps_per_second": 2.851,
69
+ "step": 40
70
+ },
71
+ {
72
+ "epoch": 0.6666666666666666,
73
+ "grad_norm": 0.442343533039093,
74
+ "learning_rate": 7.407407407407409e-05,
75
+ "loss": 2.5431,
76
+ "step": 50
77
+ },
78
+ {
79
+ "epoch": 0.6666666666666666,
80
+ "eval_loss": 2.556513786315918,
81
+ "eval_runtime": 43.8656,
82
+ "eval_samples_per_second": 22.797,
83
+ "eval_steps_per_second": 2.85,
84
+ "step": 50
85
+ },
86
+ {
87
+ "epoch": 0.8,
88
+ "grad_norm": 0.4059845805168152,
89
+ "learning_rate": 7.28888888888889e-05,
90
+ "loss": 2.4936,
91
+ "step": 60
92
+ },
93
+ {
94
+ "epoch": 0.8,
95
+ "eval_loss": 2.552133798599243,
96
+ "eval_runtime": 43.8403,
97
+ "eval_samples_per_second": 22.81,
98
+ "eval_steps_per_second": 2.851,
99
+ "step": 60
100
+ },
101
+ {
102
+ "epoch": 0.9333333333333333,
103
+ "grad_norm": 0.48126307129859924,
104
+ "learning_rate": 7.170370370370371e-05,
105
+ "loss": 2.4901,
106
+ "step": 70
107
+ },
108
+ {
109
+ "epoch": 0.9333333333333333,
110
+ "eval_loss": 2.5477023124694824,
111
+ "eval_runtime": 43.8351,
112
+ "eval_samples_per_second": 22.813,
113
+ "eval_steps_per_second": 2.852,
114
+ "step": 70
115
+ },
116
+ {
117
+ "epoch": 1.0666666666666667,
118
+ "grad_norm": 0.48629865050315857,
119
+ "learning_rate": 7.051851851851853e-05,
120
+ "loss": 2.5114,
121
+ "step": 80
122
+ },
123
+ {
124
+ "epoch": 1.0666666666666667,
125
+ "eval_loss": 2.543431043624878,
126
+ "eval_runtime": 43.8432,
127
+ "eval_samples_per_second": 22.809,
128
+ "eval_steps_per_second": 2.851,
129
+ "step": 80
130
+ },
131
+ {
132
+ "epoch": 1.2,
133
+ "grad_norm": 0.5880796313285828,
134
+ "learning_rate": 6.933333333333334e-05,
135
+ "loss": 2.4446,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 1.2,
140
+ "eval_loss": 2.544339418411255,
141
+ "eval_runtime": 43.8437,
142
+ "eval_samples_per_second": 22.808,
143
+ "eval_steps_per_second": 2.851,
144
+ "step": 90
145
+ },
146
+ {
147
+ "epoch": 1.3333333333333333,
148
+ "grad_norm": 0.6746829748153687,
149
+ "learning_rate": 6.814814814814815e-05,
150
+ "loss": 2.4477,
151
+ "step": 100
152
+ },
153
+ {
154
+ "epoch": 1.3333333333333333,
155
+ "eval_loss": 2.544358968734741,
156
+ "eval_runtime": 43.8613,
157
+ "eval_samples_per_second": 22.799,
158
+ "eval_steps_per_second": 2.85,
159
+ "step": 100
160
+ },
161
+ {
162
+ "epoch": 1.4666666666666668,
163
+ "grad_norm": 0.8208937048912048,
164
+ "learning_rate": 6.696296296296296e-05,
165
+ "loss": 2.4004,
166
+ "step": 110
167
+ },
168
+ {
169
+ "epoch": 1.4666666666666668,
170
+ "eval_loss": 2.54068660736084,
171
+ "eval_runtime": 43.8426,
172
+ "eval_samples_per_second": 22.809,
173
+ "eval_steps_per_second": 2.851,
174
+ "step": 110
175
+ },
176
+ {
177
+ "epoch": 1.6,
178
+ "grad_norm": 0.925931453704834,
179
+ "learning_rate": 6.577777777777777e-05,
180
+ "loss": 2.3889,
181
+ "step": 120
182
+ },
183
+ {
184
+ "epoch": 1.6,
185
+ "eval_loss": 2.5393033027648926,
186
+ "eval_runtime": 43.8383,
187
+ "eval_samples_per_second": 22.811,
188
+ "eval_steps_per_second": 2.851,
189
+ "step": 120
190
+ },
191
+ {
192
+ "epoch": 1.7333333333333334,
193
+ "grad_norm": 0.8785662055015564,
194
+ "learning_rate": 6.45925925925926e-05,
195
+ "loss": 2.3959,
196
+ "step": 130
197
+ },
198
+ {
199
+ "epoch": 1.7333333333333334,
200
+ "eval_loss": 2.5367038249969482,
201
+ "eval_runtime": 43.8508,
202
+ "eval_samples_per_second": 22.805,
203
+ "eval_steps_per_second": 2.851,
204
+ "step": 130
205
+ },
206
+ {
207
+ "epoch": 1.8666666666666667,
208
+ "grad_norm": 0.941368818283081,
209
+ "learning_rate": 6.340740740740741e-05,
210
+ "loss": 2.3924,
211
+ "step": 140
212
+ },
213
+ {
214
+ "epoch": 1.8666666666666667,
215
+ "eval_loss": 2.535139560699463,
216
+ "eval_runtime": 43.8588,
217
+ "eval_samples_per_second": 22.8,
218
+ "eval_steps_per_second": 2.85,
219
+ "step": 140
220
+ },
221
+ {
222
+ "epoch": 2.0,
223
+ "grad_norm": 0.9578835368156433,
224
+ "learning_rate": 6.222222222222223e-05,
225
+ "loss": 2.4278,
226
+ "step": 150
227
+ },
228
+ {
229
+ "epoch": 2.0,
230
+ "eval_loss": 2.535032033920288,
231
+ "eval_runtime": 43.8484,
232
+ "eval_samples_per_second": 22.806,
233
+ "eval_steps_per_second": 2.851,
234
+ "step": 150
235
+ },
236
+ {
237
+ "epoch": 2.1333333333333333,
238
+ "grad_norm": 1.1541856527328491,
239
+ "learning_rate": 6.103703703703704e-05,
240
+ "loss": 2.2895,
241
+ "step": 160
242
+ },
243
+ {
244
+ "epoch": 2.1333333333333333,
245
+ "eval_loss": 2.564768075942993,
246
+ "eval_runtime": 43.8568,
247
+ "eval_samples_per_second": 22.801,
248
+ "eval_steps_per_second": 2.85,
249
+ "step": 160
250
+ },
251
+ {
252
+ "epoch": 2.2666666666666666,
253
+ "grad_norm": 1.4076604843139648,
254
+ "learning_rate": 5.9851851851851855e-05,
255
+ "loss": 2.2107,
256
+ "step": 170
257
+ },
258
+ {
259
+ "epoch": 2.2666666666666666,
260
+ "eval_loss": 2.5832314491271973,
261
+ "eval_runtime": 43.8455,
262
+ "eval_samples_per_second": 22.807,
263
+ "eval_steps_per_second": 2.851,
264
+ "step": 170
265
+ },
266
+ {
267
+ "epoch": 2.4,
268
+ "grad_norm": 1.4847813844680786,
269
+ "learning_rate": 5.8666666666666665e-05,
270
+ "loss": 2.2588,
271
+ "step": 180
272
+ },
273
+ {
274
+ "epoch": 2.4,
275
+ "eval_loss": 2.5781586170196533,
276
+ "eval_runtime": 43.8578,
277
+ "eval_samples_per_second": 22.801,
278
+ "eval_steps_per_second": 2.85,
279
+ "step": 180
280
+ },
281
+ {
282
+ "epoch": 2.533333333333333,
283
+ "grad_norm": 1.5135377645492554,
284
+ "learning_rate": 5.748148148148149e-05,
285
+ "loss": 2.2099,
286
+ "step": 190
287
+ },
288
+ {
289
+ "epoch": 2.533333333333333,
290
+ "eval_loss": 2.5752007961273193,
291
+ "eval_runtime": 43.8521,
292
+ "eval_samples_per_second": 22.804,
293
+ "eval_steps_per_second": 2.85,
294
+ "step": 190
295
+ },
296
+ {
297
+ "epoch": 2.6666666666666665,
298
+ "grad_norm": 1.5297592878341675,
299
+ "learning_rate": 5.62962962962963e-05,
300
+ "loss": 2.2965,
301
+ "step": 200
302
+ },
303
+ {
304
+ "epoch": 2.6666666666666665,
305
+ "eval_loss": 2.579918622970581,
306
+ "eval_runtime": 43.8661,
307
+ "eval_samples_per_second": 22.797,
308
+ "eval_steps_per_second": 2.85,
309
+ "step": 200
310
+ },
311
+ {
312
+ "epoch": 2.8,
313
+ "grad_norm": 1.6282892227172852,
314
+ "learning_rate": 5.511111111111112e-05,
315
+ "loss": 2.2487,
316
+ "step": 210
317
+ },
318
+ {
319
+ "epoch": 2.8,
320
+ "eval_loss": 2.5760037899017334,
321
+ "eval_runtime": 43.8379,
322
+ "eval_samples_per_second": 22.811,
323
+ "eval_steps_per_second": 2.851,
324
+ "step": 210
325
+ },
326
+ {
327
+ "epoch": 2.9333333333333336,
328
+ "grad_norm": 1.74424409866333,
329
+ "learning_rate": 5.392592592592593e-05,
330
+ "loss": 2.2049,
331
+ "step": 220
332
+ },
333
+ {
334
+ "epoch": 2.9333333333333336,
335
+ "eval_loss": 2.576190233230591,
336
+ "eval_runtime": 43.8491,
337
+ "eval_samples_per_second": 22.805,
338
+ "eval_steps_per_second": 2.851,
339
+ "step": 220
340
+ },
341
+ {
342
+ "epoch": 3.066666666666667,
343
+ "grad_norm": 1.654069423675537,
344
+ "learning_rate": 5.274074074074074e-05,
345
+ "loss": 2.1188,
346
+ "step": 230
347
+ },
348
+ {
349
+ "epoch": 3.066666666666667,
350
+ "eval_loss": 2.5971405506134033,
351
+ "eval_runtime": 43.855,
352
+ "eval_samples_per_second": 22.802,
353
+ "eval_steps_per_second": 2.85,
354
+ "step": 230
355
+ },
356
+ {
357
+ "epoch": 3.2,
358
+ "grad_norm": 2.541767120361328,
359
+ "learning_rate": 5.155555555555556e-05,
360
+ "loss": 2.0788,
361
+ "step": 240
362
+ },
363
+ {
364
+ "epoch": 3.2,
365
+ "eval_loss": 2.6767666339874268,
366
+ "eval_runtime": 43.8368,
367
+ "eval_samples_per_second": 22.812,
368
+ "eval_steps_per_second": 2.851,
369
+ "step": 240
370
+ },
371
+ {
372
+ "epoch": 3.3333333333333335,
373
+ "grad_norm": 2.0508077144622803,
374
+ "learning_rate": 5.037037037037037e-05,
375
+ "loss": 2.0784,
376
+ "step": 250
377
+ },
378
+ {
379
+ "epoch": 3.3333333333333335,
380
+ "eval_loss": 2.6486454010009766,
381
+ "eval_runtime": 43.8529,
382
+ "eval_samples_per_second": 22.803,
383
+ "eval_steps_per_second": 2.85,
384
+ "step": 250
385
+ },
386
+ {
387
+ "epoch": 3.466666666666667,
388
+ "grad_norm": 2.1096036434173584,
389
+ "learning_rate": 4.918518518518519e-05,
390
+ "loss": 2.0633,
391
+ "step": 260
392
+ },
393
+ {
394
+ "epoch": 3.466666666666667,
395
+ "eval_loss": 2.6501405239105225,
396
+ "eval_runtime": 43.8632,
397
+ "eval_samples_per_second": 22.798,
398
+ "eval_steps_per_second": 2.85,
399
+ "step": 260
400
+ },
401
+ {
402
+ "epoch": 3.6,
403
+ "grad_norm": 2.3028736114501953,
404
+ "learning_rate": 4.8e-05,
405
+ "loss": 2.0722,
406
+ "step": 270
407
+ },
408
+ {
409
+ "epoch": 3.6,
410
+ "eval_loss": 2.657053232192993,
411
+ "eval_runtime": 43.8423,
412
+ "eval_samples_per_second": 22.809,
413
+ "eval_steps_per_second": 2.851,
414
+ "step": 270
415
+ },
416
+ {
417
+ "epoch": 3.7333333333333334,
418
+ "grad_norm": 2.1536757946014404,
419
+ "learning_rate": 4.681481481481481e-05,
420
+ "loss": 2.0155,
421
+ "step": 280
422
+ },
423
+ {
424
+ "epoch": 3.7333333333333334,
425
+ "eval_loss": 2.648275375366211,
426
+ "eval_runtime": 43.8328,
427
+ "eval_samples_per_second": 22.814,
428
+ "eval_steps_per_second": 2.852,
429
+ "step": 280
430
+ },
431
+ {
432
+ "epoch": 3.8666666666666667,
433
+ "grad_norm": 2.4079270362854004,
434
+ "learning_rate": 4.5629629629629636e-05,
435
+ "loss": 2.1111,
436
+ "step": 290
437
+ },
438
+ {
439
+ "epoch": 3.8666666666666667,
440
+ "eval_loss": 2.650322675704956,
441
+ "eval_runtime": 43.835,
442
+ "eval_samples_per_second": 22.813,
443
+ "eval_steps_per_second": 2.852,
444
+ "step": 290
445
+ },
446
+ {
447
+ "epoch": 4.0,
448
+ "grad_norm": 2.426234722137451,
449
+ "learning_rate": 4.444444444444445e-05,
450
+ "loss": 2.041,
451
+ "step": 300
452
+ },
453
+ {
454
+ "epoch": 4.0,
455
+ "eval_loss": 2.6490862369537354,
456
+ "eval_runtime": 43.845,
457
+ "eval_samples_per_second": 22.808,
458
+ "eval_steps_per_second": 2.851,
459
+ "step": 300
460
+ },
461
+ {
462
+ "epoch": 4.133333333333334,
463
+ "grad_norm": 2.8063745498657227,
464
+ "learning_rate": 4.3259259259259264e-05,
465
+ "loss": 1.9316,
466
+ "step": 310
467
+ },
468
+ {
469
+ "epoch": 4.133333333333334,
470
+ "eval_loss": 2.7609620094299316,
471
+ "eval_runtime": 43.8481,
472
+ "eval_samples_per_second": 22.806,
473
+ "eval_steps_per_second": 2.851,
474
+ "step": 310
475
+ },
476
+ {
477
+ "epoch": 4.266666666666667,
478
+ "grad_norm": 2.96854305267334,
479
+ "learning_rate": 4.2074074074074075e-05,
480
+ "loss": 1.8889,
481
+ "step": 320
482
+ },
483
+ {
484
+ "epoch": 4.266666666666667,
485
+ "eval_loss": 2.736968994140625,
486
+ "eval_runtime": 43.8633,
487
+ "eval_samples_per_second": 22.798,
488
+ "eval_steps_per_second": 2.85,
489
+ "step": 320
490
+ },
491
+ {
492
+ "epoch": 4.4,
493
+ "grad_norm": 2.637695789337158,
494
+ "learning_rate": 4.088888888888889e-05,
495
+ "loss": 1.9187,
496
+ "step": 330
497
+ },
498
+ {
499
+ "epoch": 4.4,
500
+ "eval_loss": 2.7382876873016357,
501
+ "eval_runtime": 43.8486,
502
+ "eval_samples_per_second": 22.806,
503
+ "eval_steps_per_second": 2.851,
504
+ "step": 330
505
+ },
506
+ {
507
+ "epoch": 4.533333333333333,
508
+ "grad_norm": 2.9106290340423584,
509
+ "learning_rate": 3.970370370370371e-05,
510
+ "loss": 1.9002,
511
+ "step": 340
512
+ },
513
+ {
514
+ "epoch": 4.533333333333333,
515
+ "eval_loss": 2.734544515609741,
516
+ "eval_runtime": 43.8491,
517
+ "eval_samples_per_second": 22.805,
518
+ "eval_steps_per_second": 2.851,
519
+ "step": 340
520
+ },
521
+ {
522
+ "epoch": 4.666666666666667,
523
+ "grad_norm": 2.769315481185913,
524
+ "learning_rate": 3.851851851851852e-05,
525
+ "loss": 1.9251,
526
+ "step": 350
527
+ },
528
+ {
529
+ "epoch": 4.666666666666667,
530
+ "eval_loss": 2.734708070755005,
531
+ "eval_runtime": 43.8534,
532
+ "eval_samples_per_second": 22.803,
533
+ "eval_steps_per_second": 2.85,
534
+ "step": 350
535
+ },
536
+ {
537
+ "epoch": 4.8,
538
+ "grad_norm": 2.940281867980957,
539
+ "learning_rate": 3.733333333333334e-05,
540
+ "loss": 1.9319,
541
+ "step": 360
542
+ },
543
+ {
544
+ "epoch": 4.8,
545
+ "eval_loss": 2.7300503253936768,
546
+ "eval_runtime": 43.9017,
547
+ "eval_samples_per_second": 22.778,
548
+ "eval_steps_per_second": 2.847,
549
+ "step": 360
550
+ },
551
+ {
552
+ "epoch": 4.933333333333334,
553
+ "grad_norm": 2.8305609226226807,
554
+ "learning_rate": 3.614814814814815e-05,
555
+ "loss": 1.9332,
556
+ "step": 370
557
+ },
558
+ {
559
+ "epoch": 4.933333333333334,
560
+ "eval_loss": 2.7309281826019287,
561
+ "eval_runtime": 43.8842,
562
+ "eval_samples_per_second": 22.787,
563
+ "eval_steps_per_second": 2.848,
564
+ "step": 370
565
+ },
566
+ {
567
+ "epoch": 5.066666666666666,
568
+ "grad_norm": 2.8739213943481445,
569
+ "learning_rate": 3.4962962962962965e-05,
570
+ "loss": 1.8846,
571
+ "step": 380
572
+ },
573
+ {
574
+ "epoch": 5.066666666666666,
575
+ "eval_loss": 2.76513671875,
576
+ "eval_runtime": 43.906,
577
+ "eval_samples_per_second": 22.776,
578
+ "eval_steps_per_second": 2.847,
579
+ "step": 380
580
+ },
581
+ {
582
+ "epoch": 5.2,
583
+ "grad_norm": 3.9025838375091553,
584
+ "learning_rate": 3.377777777777778e-05,
585
+ "loss": 1.7575,
586
+ "step": 390
587
+ },
588
+ {
589
+ "epoch": 5.2,
590
+ "eval_loss": 2.847782611846924,
591
+ "eval_runtime": 43.8665,
592
+ "eval_samples_per_second": 22.796,
593
+ "eval_steps_per_second": 2.85,
594
+ "step": 390
595
+ },
596
+ {
597
+ "epoch": 5.333333333333333,
598
+ "grad_norm": 3.299649715423584,
599
+ "learning_rate": 3.259259259259259e-05,
600
+ "loss": 1.7713,
601
+ "step": 400
602
+ },
603
+ {
604
+ "epoch": 5.333333333333333,
605
+ "eval_loss": 2.8094286918640137,
606
+ "eval_runtime": 43.8629,
607
+ "eval_samples_per_second": 22.798,
608
+ "eval_steps_per_second": 2.85,
609
+ "step": 400
610
+ },
611
+ {
612
+ "epoch": 5.466666666666667,
613
+ "grad_norm": 3.4474265575408936,
614
+ "learning_rate": 3.140740740740741e-05,
615
+ "loss": 1.7983,
616
+ "step": 410
617
+ },
618
+ {
619
+ "epoch": 5.466666666666667,
620
+ "eval_loss": 2.827517509460449,
621
+ "eval_runtime": 43.8611,
622
+ "eval_samples_per_second": 22.799,
623
+ "eval_steps_per_second": 2.85,
624
+ "step": 410
625
+ },
626
+ {
627
+ "epoch": 5.6,
628
+ "grad_norm": 3.1924540996551514,
629
+ "learning_rate": 3.0222222222222225e-05,
630
+ "loss": 1.8091,
631
+ "step": 420
632
+ },
633
+ {
634
+ "epoch": 5.6,
635
+ "eval_loss": 2.81618332862854,
636
+ "eval_runtime": 43.8544,
637
+ "eval_samples_per_second": 22.803,
638
+ "eval_steps_per_second": 2.85,
639
+ "step": 420
640
+ },
641
+ {
642
+ "epoch": 5.733333333333333,
643
+ "grad_norm": 3.5224015712738037,
644
+ "learning_rate": 2.9037037037037042e-05,
645
+ "loss": 1.8253,
646
+ "step": 430
647
+ },
648
+ {
649
+ "epoch": 5.733333333333333,
650
+ "eval_loss": 2.816711187362671,
651
+ "eval_runtime": 43.8685,
652
+ "eval_samples_per_second": 22.795,
653
+ "eval_steps_per_second": 2.849,
654
+ "step": 430
655
+ },
656
+ {
657
+ "epoch": 5.866666666666667,
658
+ "grad_norm": 3.60918927192688,
659
+ "learning_rate": 2.7851851851851856e-05,
660
+ "loss": 1.8013,
661
+ "step": 440
662
+ },
663
+ {
664
+ "epoch": 5.866666666666667,
665
+ "eval_loss": 2.8146169185638428,
666
+ "eval_runtime": 43.8516,
667
+ "eval_samples_per_second": 22.804,
668
+ "eval_steps_per_second": 2.851,
669
+ "step": 440
670
+ },
671
+ {
672
+ "epoch": 6.0,
673
+ "grad_norm": 3.5798070430755615,
674
+ "learning_rate": 2.6666666666666667e-05,
675
+ "loss": 1.8258,
676
+ "step": 450
677
+ },
678
+ {
679
+ "epoch": 6.0,
680
+ "eval_loss": 2.8134233951568604,
681
+ "eval_runtime": 43.8442,
682
+ "eval_samples_per_second": 22.808,
683
+ "eval_steps_per_second": 2.851,
684
+ "step": 450
685
+ },
686
+ {
687
+ "epoch": 6.133333333333334,
688
+ "grad_norm": 5.563477993011475,
689
+ "learning_rate": 2.5481481481481484e-05,
690
+ "loss": 1.6649,
691
+ "step": 460
692
+ },
693
+ {
694
+ "epoch": 6.133333333333334,
695
+ "eval_loss": 2.9189789295196533,
696
+ "eval_runtime": 43.8602,
697
+ "eval_samples_per_second": 22.8,
698
+ "eval_steps_per_second": 2.85,
699
+ "step": 460
700
+ },
701
+ {
702
+ "epoch": 6.266666666666667,
703
+ "grad_norm": 4.192393779754639,
704
+ "learning_rate": 2.4296296296296298e-05,
705
+ "loss": 1.7443,
706
+ "step": 470
707
+ },
708
+ {
709
+ "epoch": 6.266666666666667,
710
+ "eval_loss": 2.893780469894409,
711
+ "eval_runtime": 43.8434,
712
+ "eval_samples_per_second": 22.808,
713
+ "eval_steps_per_second": 2.851,
714
+ "step": 470
715
+ },
716
+ {
717
+ "epoch": 6.4,
718
+ "grad_norm": 4.8650593757629395,
719
+ "learning_rate": 2.3111111111111112e-05,
720
+ "loss": 1.6961,
721
+ "step": 480
722
+ },
723
+ {
724
+ "epoch": 6.4,
725
+ "eval_loss": 2.8861398696899414,
726
+ "eval_runtime": 43.8417,
727
+ "eval_samples_per_second": 22.809,
728
+ "eval_steps_per_second": 2.851,
729
+ "step": 480
730
+ },
731
+ {
732
+ "epoch": 6.533333333333333,
733
+ "grad_norm": 3.844482660293579,
734
+ "learning_rate": 2.192592592592593e-05,
735
+ "loss": 1.6868,
736
+ "step": 490
737
+ },
738
+ {
739
+ "epoch": 6.533333333333333,
740
+ "eval_loss": 2.900317907333374,
741
+ "eval_runtime": 43.8557,
742
+ "eval_samples_per_second": 22.802,
743
+ "eval_steps_per_second": 2.85,
744
+ "step": 490
745
+ },
746
+ {
747
+ "epoch": 6.666666666666667,
748
+ "grad_norm": 4.230032920837402,
749
+ "learning_rate": 2.074074074074074e-05,
750
+ "loss": 1.6593,
751
+ "step": 500
752
+ },
753
+ {
754
+ "epoch": 6.666666666666667,
755
+ "eval_loss": 2.892076253890991,
756
+ "eval_runtime": 43.8479,
757
+ "eval_samples_per_second": 22.806,
758
+ "eval_steps_per_second": 2.851,
759
+ "step": 500
760
+ },
761
+ {
762
+ "epoch": 6.8,
763
+ "grad_norm": 4.427380561828613,
764
+ "learning_rate": 1.9555555555555557e-05,
765
+ "loss": 1.6777,
766
+ "step": 510
767
+ },
768
+ {
769
+ "epoch": 6.8,
770
+ "eval_loss": 2.8877696990966797,
771
+ "eval_runtime": 43.8489,
772
+ "eval_samples_per_second": 22.806,
773
+ "eval_steps_per_second": 2.851,
774
+ "step": 510
775
+ },
776
+ {
777
+ "epoch": 6.933333333333334,
778
+ "grad_norm": 4.23176908493042,
779
+ "learning_rate": 1.837037037037037e-05,
780
+ "loss": 1.7331,
781
+ "step": 520
782
+ },
783
+ {
784
+ "epoch": 6.933333333333334,
785
+ "eval_loss": 2.889272928237915,
786
+ "eval_runtime": 43.8577,
787
+ "eval_samples_per_second": 22.801,
788
+ "eval_steps_per_second": 2.85,
789
+ "step": 520
790
+ },
791
+ {
792
+ "epoch": 7.066666666666666,
793
+ "grad_norm": 3.9098429679870605,
794
+ "learning_rate": 1.7185185185185185e-05,
795
+ "loss": 1.6741,
796
+ "step": 530
797
+ },
798
+ {
799
+ "epoch": 7.066666666666666,
800
+ "eval_loss": 2.9202494621276855,
801
+ "eval_runtime": 43.8571,
802
+ "eval_samples_per_second": 22.801,
803
+ "eval_steps_per_second": 2.85,
804
+ "step": 530
805
+ },
806
+ {
807
+ "epoch": 7.2,
808
+ "grad_norm": 4.320191383361816,
809
+ "learning_rate": 1.6000000000000003e-05,
810
+ "loss": 1.5711,
811
+ "step": 540
812
+ },
813
+ {
814
+ "epoch": 7.2,
815
+ "eval_loss": 2.97855806350708,
816
+ "eval_runtime": 43.8599,
817
+ "eval_samples_per_second": 22.8,
818
+ "eval_steps_per_second": 2.85,
819
+ "step": 540
820
+ },
821
+ {
822
+ "epoch": 7.333333333333333,
823
+ "grad_norm": 4.003049850463867,
824
+ "learning_rate": 1.4814814814814815e-05,
825
+ "loss": 1.6106,
826
+ "step": 550
827
+ },
828
+ {
829
+ "epoch": 7.333333333333333,
830
+ "eval_loss": 2.9440739154815674,
831
+ "eval_runtime": 43.8605,
832
+ "eval_samples_per_second": 22.8,
833
+ "eval_steps_per_second": 2.85,
834
+ "step": 550
835
+ },
836
+ {
837
+ "epoch": 7.466666666666667,
838
+ "grad_norm": 4.265935897827148,
839
+ "learning_rate": 1.362962962962963e-05,
840
+ "loss": 1.6241,
841
+ "step": 560
842
+ },
843
+ {
844
+ "epoch": 7.466666666666667,
845
+ "eval_loss": 2.958505630493164,
846
+ "eval_runtime": 43.8614,
847
+ "eval_samples_per_second": 22.799,
848
+ "eval_steps_per_second": 2.85,
849
+ "step": 560
850
+ },
851
+ {
852
+ "epoch": 7.6,
853
+ "grad_norm": 5.025564670562744,
854
+ "learning_rate": 1.2444444444444446e-05,
855
+ "loss": 1.6306,
856
+ "step": 570
857
+ },
858
+ {
859
+ "epoch": 7.6,
860
+ "eval_loss": 2.956601619720459,
861
+ "eval_runtime": 43.8595,
862
+ "eval_samples_per_second": 22.8,
863
+ "eval_steps_per_second": 2.85,
864
+ "step": 570
865
+ },
866
+ {
867
+ "epoch": 7.733333333333333,
868
+ "grad_norm": 4.252591133117676,
869
+ "learning_rate": 1.125925925925926e-05,
870
+ "loss": 1.5933,
871
+ "step": 580
872
+ },
873
+ {
874
+ "epoch": 7.733333333333333,
875
+ "eval_loss": 2.9567930698394775,
876
+ "eval_runtime": 43.8568,
877
+ "eval_samples_per_second": 22.801,
878
+ "eval_steps_per_second": 2.85,
879
+ "step": 580
880
+ }
881
+ ],
882
+ "logging_steps": 10,
883
+ "max_steps": 675,
884
+ "num_input_tokens_seen": 0,
885
+ "num_train_epochs": 9,
886
+ "save_steps": 10,
887
+ "stateful_callbacks": {
888
+ "TrainerControl": {
889
+ "args": {
890
+ "should_epoch_stop": false,
891
+ "should_evaluate": false,
892
+ "should_log": false,
893
+ "should_save": true,
894
+ "should_training_stop": false
895
+ },
896
+ "attributes": {}
897
+ }
898
+ },
899
+ "total_flos": 9.50392175198208e+16,
900
+ "train_batch_size": 8,
901
+ "trial_name": null,
902
+ "trial_params": null
903
+ }
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-590/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/pythia-6_9b
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-590/adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/workspace/pythia-6_9b",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.1,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 8,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "dense_h_to_4h",
24
+ "query_key_value",
25
+ "dense",
26
+ "dense_4h_to_h"
27
+ ],
28
+ "task_type": "CAUSAL_LM",
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-590/trainer_state.json ADDED
@@ -0,0 +1,918 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 2.535032033920288,
3
+ "best_model_checkpoint": "./output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-150",
4
+ "epoch": 7.866666666666667,
5
+ "eval_steps": 10,
6
+ "global_step": 590,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.13333333333333333,
13
+ "grad_norm": 0.36938729882240295,
14
+ "learning_rate": 7.881481481481482e-05,
15
+ "loss": 2.519,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.13333333333333333,
20
+ "eval_loss": 2.579638957977295,
21
+ "eval_runtime": 43.8215,
22
+ "eval_samples_per_second": 22.82,
23
+ "eval_steps_per_second": 2.852,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.26666666666666666,
28
+ "grad_norm": 0.39850670099258423,
29
+ "learning_rate": 7.762962962962963e-05,
30
+ "loss": 2.5224,
31
+ "step": 20
32
+ },
33
+ {
34
+ "epoch": 0.26666666666666666,
35
+ "eval_loss": 2.5729691982269287,
36
+ "eval_runtime": 43.8179,
37
+ "eval_samples_per_second": 22.822,
38
+ "eval_steps_per_second": 2.853,
39
+ "step": 20
40
+ },
41
+ {
42
+ "epoch": 0.4,
43
+ "grad_norm": 0.40211933851242065,
44
+ "learning_rate": 7.644444444444445e-05,
45
+ "loss": 2.5169,
46
+ "step": 30
47
+ },
48
+ {
49
+ "epoch": 0.4,
50
+ "eval_loss": 2.567735433578491,
51
+ "eval_runtime": 43.8366,
52
+ "eval_samples_per_second": 22.812,
53
+ "eval_steps_per_second": 2.851,
54
+ "step": 30
55
+ },
56
+ {
57
+ "epoch": 0.5333333333333333,
58
+ "grad_norm": 0.6892333030700684,
59
+ "learning_rate": 7.525925925925926e-05,
60
+ "loss": 2.5784,
61
+ "step": 40
62
+ },
63
+ {
64
+ "epoch": 0.5333333333333333,
65
+ "eval_loss": 2.562650442123413,
66
+ "eval_runtime": 43.8377,
67
+ "eval_samples_per_second": 22.811,
68
+ "eval_steps_per_second": 2.851,
69
+ "step": 40
70
+ },
71
+ {
72
+ "epoch": 0.6666666666666666,
73
+ "grad_norm": 0.442343533039093,
74
+ "learning_rate": 7.407407407407409e-05,
75
+ "loss": 2.5431,
76
+ "step": 50
77
+ },
78
+ {
79
+ "epoch": 0.6666666666666666,
80
+ "eval_loss": 2.556513786315918,
81
+ "eval_runtime": 43.8656,
82
+ "eval_samples_per_second": 22.797,
83
+ "eval_steps_per_second": 2.85,
84
+ "step": 50
85
+ },
86
+ {
87
+ "epoch": 0.8,
88
+ "grad_norm": 0.4059845805168152,
89
+ "learning_rate": 7.28888888888889e-05,
90
+ "loss": 2.4936,
91
+ "step": 60
92
+ },
93
+ {
94
+ "epoch": 0.8,
95
+ "eval_loss": 2.552133798599243,
96
+ "eval_runtime": 43.8403,
97
+ "eval_samples_per_second": 22.81,
98
+ "eval_steps_per_second": 2.851,
99
+ "step": 60
100
+ },
101
+ {
102
+ "epoch": 0.9333333333333333,
103
+ "grad_norm": 0.48126307129859924,
104
+ "learning_rate": 7.170370370370371e-05,
105
+ "loss": 2.4901,
106
+ "step": 70
107
+ },
108
+ {
109
+ "epoch": 0.9333333333333333,
110
+ "eval_loss": 2.5477023124694824,
111
+ "eval_runtime": 43.8351,
112
+ "eval_samples_per_second": 22.813,
113
+ "eval_steps_per_second": 2.852,
114
+ "step": 70
115
+ },
116
+ {
117
+ "epoch": 1.0666666666666667,
118
+ "grad_norm": 0.48629865050315857,
119
+ "learning_rate": 7.051851851851853e-05,
120
+ "loss": 2.5114,
121
+ "step": 80
122
+ },
123
+ {
124
+ "epoch": 1.0666666666666667,
125
+ "eval_loss": 2.543431043624878,
126
+ "eval_runtime": 43.8432,
127
+ "eval_samples_per_second": 22.809,
128
+ "eval_steps_per_second": 2.851,
129
+ "step": 80
130
+ },
131
+ {
132
+ "epoch": 1.2,
133
+ "grad_norm": 0.5880796313285828,
134
+ "learning_rate": 6.933333333333334e-05,
135
+ "loss": 2.4446,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 1.2,
140
+ "eval_loss": 2.544339418411255,
141
+ "eval_runtime": 43.8437,
142
+ "eval_samples_per_second": 22.808,
143
+ "eval_steps_per_second": 2.851,
144
+ "step": 90
145
+ },
146
+ {
147
+ "epoch": 1.3333333333333333,
148
+ "grad_norm": 0.6746829748153687,
149
+ "learning_rate": 6.814814814814815e-05,
150
+ "loss": 2.4477,
151
+ "step": 100
152
+ },
153
+ {
154
+ "epoch": 1.3333333333333333,
155
+ "eval_loss": 2.544358968734741,
156
+ "eval_runtime": 43.8613,
157
+ "eval_samples_per_second": 22.799,
158
+ "eval_steps_per_second": 2.85,
159
+ "step": 100
160
+ },
161
+ {
162
+ "epoch": 1.4666666666666668,
163
+ "grad_norm": 0.8208937048912048,
164
+ "learning_rate": 6.696296296296296e-05,
165
+ "loss": 2.4004,
166
+ "step": 110
167
+ },
168
+ {
169
+ "epoch": 1.4666666666666668,
170
+ "eval_loss": 2.54068660736084,
171
+ "eval_runtime": 43.8426,
172
+ "eval_samples_per_second": 22.809,
173
+ "eval_steps_per_second": 2.851,
174
+ "step": 110
175
+ },
176
+ {
177
+ "epoch": 1.6,
178
+ "grad_norm": 0.925931453704834,
179
+ "learning_rate": 6.577777777777777e-05,
180
+ "loss": 2.3889,
181
+ "step": 120
182
+ },
183
+ {
184
+ "epoch": 1.6,
185
+ "eval_loss": 2.5393033027648926,
186
+ "eval_runtime": 43.8383,
187
+ "eval_samples_per_second": 22.811,
188
+ "eval_steps_per_second": 2.851,
189
+ "step": 120
190
+ },
191
+ {
192
+ "epoch": 1.7333333333333334,
193
+ "grad_norm": 0.8785662055015564,
194
+ "learning_rate": 6.45925925925926e-05,
195
+ "loss": 2.3959,
196
+ "step": 130
197
+ },
198
+ {
199
+ "epoch": 1.7333333333333334,
200
+ "eval_loss": 2.5367038249969482,
201
+ "eval_runtime": 43.8508,
202
+ "eval_samples_per_second": 22.805,
203
+ "eval_steps_per_second": 2.851,
204
+ "step": 130
205
+ },
206
+ {
207
+ "epoch": 1.8666666666666667,
208
+ "grad_norm": 0.941368818283081,
209
+ "learning_rate": 6.340740740740741e-05,
210
+ "loss": 2.3924,
211
+ "step": 140
212
+ },
213
+ {
214
+ "epoch": 1.8666666666666667,
215
+ "eval_loss": 2.535139560699463,
216
+ "eval_runtime": 43.8588,
217
+ "eval_samples_per_second": 22.8,
218
+ "eval_steps_per_second": 2.85,
219
+ "step": 140
220
+ },
221
+ {
222
+ "epoch": 2.0,
223
+ "grad_norm": 0.9578835368156433,
224
+ "learning_rate": 6.222222222222223e-05,
225
+ "loss": 2.4278,
226
+ "step": 150
227
+ },
228
+ {
229
+ "epoch": 2.0,
230
+ "eval_loss": 2.535032033920288,
231
+ "eval_runtime": 43.8484,
232
+ "eval_samples_per_second": 22.806,
233
+ "eval_steps_per_second": 2.851,
234
+ "step": 150
235
+ },
236
+ {
237
+ "epoch": 2.1333333333333333,
238
+ "grad_norm": 1.1541856527328491,
239
+ "learning_rate": 6.103703703703704e-05,
240
+ "loss": 2.2895,
241
+ "step": 160
242
+ },
243
+ {
244
+ "epoch": 2.1333333333333333,
245
+ "eval_loss": 2.564768075942993,
246
+ "eval_runtime": 43.8568,
247
+ "eval_samples_per_second": 22.801,
248
+ "eval_steps_per_second": 2.85,
249
+ "step": 160
250
+ },
251
+ {
252
+ "epoch": 2.2666666666666666,
253
+ "grad_norm": 1.4076604843139648,
254
+ "learning_rate": 5.9851851851851855e-05,
255
+ "loss": 2.2107,
256
+ "step": 170
257
+ },
258
+ {
259
+ "epoch": 2.2666666666666666,
260
+ "eval_loss": 2.5832314491271973,
261
+ "eval_runtime": 43.8455,
262
+ "eval_samples_per_second": 22.807,
263
+ "eval_steps_per_second": 2.851,
264
+ "step": 170
265
+ },
266
+ {
267
+ "epoch": 2.4,
268
+ "grad_norm": 1.4847813844680786,
269
+ "learning_rate": 5.8666666666666665e-05,
270
+ "loss": 2.2588,
271
+ "step": 180
272
+ },
273
+ {
274
+ "epoch": 2.4,
275
+ "eval_loss": 2.5781586170196533,
276
+ "eval_runtime": 43.8578,
277
+ "eval_samples_per_second": 22.801,
278
+ "eval_steps_per_second": 2.85,
279
+ "step": 180
280
+ },
281
+ {
282
+ "epoch": 2.533333333333333,
283
+ "grad_norm": 1.5135377645492554,
284
+ "learning_rate": 5.748148148148149e-05,
285
+ "loss": 2.2099,
286
+ "step": 190
287
+ },
288
+ {
289
+ "epoch": 2.533333333333333,
290
+ "eval_loss": 2.5752007961273193,
291
+ "eval_runtime": 43.8521,
292
+ "eval_samples_per_second": 22.804,
293
+ "eval_steps_per_second": 2.85,
294
+ "step": 190
295
+ },
296
+ {
297
+ "epoch": 2.6666666666666665,
298
+ "grad_norm": 1.5297592878341675,
299
+ "learning_rate": 5.62962962962963e-05,
300
+ "loss": 2.2965,
301
+ "step": 200
302
+ },
303
+ {
304
+ "epoch": 2.6666666666666665,
305
+ "eval_loss": 2.579918622970581,
306
+ "eval_runtime": 43.8661,
307
+ "eval_samples_per_second": 22.797,
308
+ "eval_steps_per_second": 2.85,
309
+ "step": 200
310
+ },
311
+ {
312
+ "epoch": 2.8,
313
+ "grad_norm": 1.6282892227172852,
314
+ "learning_rate": 5.511111111111112e-05,
315
+ "loss": 2.2487,
316
+ "step": 210
317
+ },
318
+ {
319
+ "epoch": 2.8,
320
+ "eval_loss": 2.5760037899017334,
321
+ "eval_runtime": 43.8379,
322
+ "eval_samples_per_second": 22.811,
323
+ "eval_steps_per_second": 2.851,
324
+ "step": 210
325
+ },
326
+ {
327
+ "epoch": 2.9333333333333336,
328
+ "grad_norm": 1.74424409866333,
329
+ "learning_rate": 5.392592592592593e-05,
330
+ "loss": 2.2049,
331
+ "step": 220
332
+ },
333
+ {
334
+ "epoch": 2.9333333333333336,
335
+ "eval_loss": 2.576190233230591,
336
+ "eval_runtime": 43.8491,
337
+ "eval_samples_per_second": 22.805,
338
+ "eval_steps_per_second": 2.851,
339
+ "step": 220
340
+ },
341
+ {
342
+ "epoch": 3.066666666666667,
343
+ "grad_norm": 1.654069423675537,
344
+ "learning_rate": 5.274074074074074e-05,
345
+ "loss": 2.1188,
346
+ "step": 230
347
+ },
348
+ {
349
+ "epoch": 3.066666666666667,
350
+ "eval_loss": 2.5971405506134033,
351
+ "eval_runtime": 43.855,
352
+ "eval_samples_per_second": 22.802,
353
+ "eval_steps_per_second": 2.85,
354
+ "step": 230
355
+ },
356
+ {
357
+ "epoch": 3.2,
358
+ "grad_norm": 2.541767120361328,
359
+ "learning_rate": 5.155555555555556e-05,
360
+ "loss": 2.0788,
361
+ "step": 240
362
+ },
363
+ {
364
+ "epoch": 3.2,
365
+ "eval_loss": 2.6767666339874268,
366
+ "eval_runtime": 43.8368,
367
+ "eval_samples_per_second": 22.812,
368
+ "eval_steps_per_second": 2.851,
369
+ "step": 240
370
+ },
371
+ {
372
+ "epoch": 3.3333333333333335,
373
+ "grad_norm": 2.0508077144622803,
374
+ "learning_rate": 5.037037037037037e-05,
375
+ "loss": 2.0784,
376
+ "step": 250
377
+ },
378
+ {
379
+ "epoch": 3.3333333333333335,
380
+ "eval_loss": 2.6486454010009766,
381
+ "eval_runtime": 43.8529,
382
+ "eval_samples_per_second": 22.803,
383
+ "eval_steps_per_second": 2.85,
384
+ "step": 250
385
+ },
386
+ {
387
+ "epoch": 3.466666666666667,
388
+ "grad_norm": 2.1096036434173584,
389
+ "learning_rate": 4.918518518518519e-05,
390
+ "loss": 2.0633,
391
+ "step": 260
392
+ },
393
+ {
394
+ "epoch": 3.466666666666667,
395
+ "eval_loss": 2.6501405239105225,
396
+ "eval_runtime": 43.8632,
397
+ "eval_samples_per_second": 22.798,
398
+ "eval_steps_per_second": 2.85,
399
+ "step": 260
400
+ },
401
+ {
402
+ "epoch": 3.6,
403
+ "grad_norm": 2.3028736114501953,
404
+ "learning_rate": 4.8e-05,
405
+ "loss": 2.0722,
406
+ "step": 270
407
+ },
408
+ {
409
+ "epoch": 3.6,
410
+ "eval_loss": 2.657053232192993,
411
+ "eval_runtime": 43.8423,
412
+ "eval_samples_per_second": 22.809,
413
+ "eval_steps_per_second": 2.851,
414
+ "step": 270
415
+ },
416
+ {
417
+ "epoch": 3.7333333333333334,
418
+ "grad_norm": 2.1536757946014404,
419
+ "learning_rate": 4.681481481481481e-05,
420
+ "loss": 2.0155,
421
+ "step": 280
422
+ },
423
+ {
424
+ "epoch": 3.7333333333333334,
425
+ "eval_loss": 2.648275375366211,
426
+ "eval_runtime": 43.8328,
427
+ "eval_samples_per_second": 22.814,
428
+ "eval_steps_per_second": 2.852,
429
+ "step": 280
430
+ },
431
+ {
432
+ "epoch": 3.8666666666666667,
433
+ "grad_norm": 2.4079270362854004,
434
+ "learning_rate": 4.5629629629629636e-05,
435
+ "loss": 2.1111,
436
+ "step": 290
437
+ },
438
+ {
439
+ "epoch": 3.8666666666666667,
440
+ "eval_loss": 2.650322675704956,
441
+ "eval_runtime": 43.835,
442
+ "eval_samples_per_second": 22.813,
443
+ "eval_steps_per_second": 2.852,
444
+ "step": 290
445
+ },
446
+ {
447
+ "epoch": 4.0,
448
+ "grad_norm": 2.426234722137451,
449
+ "learning_rate": 4.444444444444445e-05,
450
+ "loss": 2.041,
451
+ "step": 300
452
+ },
453
+ {
454
+ "epoch": 4.0,
455
+ "eval_loss": 2.6490862369537354,
456
+ "eval_runtime": 43.845,
457
+ "eval_samples_per_second": 22.808,
458
+ "eval_steps_per_second": 2.851,
459
+ "step": 300
460
+ },
461
+ {
462
+ "epoch": 4.133333333333334,
463
+ "grad_norm": 2.8063745498657227,
464
+ "learning_rate": 4.3259259259259264e-05,
465
+ "loss": 1.9316,
466
+ "step": 310
467
+ },
468
+ {
469
+ "epoch": 4.133333333333334,
470
+ "eval_loss": 2.7609620094299316,
471
+ "eval_runtime": 43.8481,
472
+ "eval_samples_per_second": 22.806,
473
+ "eval_steps_per_second": 2.851,
474
+ "step": 310
475
+ },
476
+ {
477
+ "epoch": 4.266666666666667,
478
+ "grad_norm": 2.96854305267334,
479
+ "learning_rate": 4.2074074074074075e-05,
480
+ "loss": 1.8889,
481
+ "step": 320
482
+ },
483
+ {
484
+ "epoch": 4.266666666666667,
485
+ "eval_loss": 2.736968994140625,
486
+ "eval_runtime": 43.8633,
487
+ "eval_samples_per_second": 22.798,
488
+ "eval_steps_per_second": 2.85,
489
+ "step": 320
490
+ },
491
+ {
492
+ "epoch": 4.4,
493
+ "grad_norm": 2.637695789337158,
494
+ "learning_rate": 4.088888888888889e-05,
495
+ "loss": 1.9187,
496
+ "step": 330
497
+ },
498
+ {
499
+ "epoch": 4.4,
500
+ "eval_loss": 2.7382876873016357,
501
+ "eval_runtime": 43.8486,
502
+ "eval_samples_per_second": 22.806,
503
+ "eval_steps_per_second": 2.851,
504
+ "step": 330
505
+ },
506
+ {
507
+ "epoch": 4.533333333333333,
508
+ "grad_norm": 2.9106290340423584,
509
+ "learning_rate": 3.970370370370371e-05,
510
+ "loss": 1.9002,
511
+ "step": 340
512
+ },
513
+ {
514
+ "epoch": 4.533333333333333,
515
+ "eval_loss": 2.734544515609741,
516
+ "eval_runtime": 43.8491,
517
+ "eval_samples_per_second": 22.805,
518
+ "eval_steps_per_second": 2.851,
519
+ "step": 340
520
+ },
521
+ {
522
+ "epoch": 4.666666666666667,
523
+ "grad_norm": 2.769315481185913,
524
+ "learning_rate": 3.851851851851852e-05,
525
+ "loss": 1.9251,
526
+ "step": 350
527
+ },
528
+ {
529
+ "epoch": 4.666666666666667,
530
+ "eval_loss": 2.734708070755005,
531
+ "eval_runtime": 43.8534,
532
+ "eval_samples_per_second": 22.803,
533
+ "eval_steps_per_second": 2.85,
534
+ "step": 350
535
+ },
536
+ {
537
+ "epoch": 4.8,
538
+ "grad_norm": 2.940281867980957,
539
+ "learning_rate": 3.733333333333334e-05,
540
+ "loss": 1.9319,
541
+ "step": 360
542
+ },
543
+ {
544
+ "epoch": 4.8,
545
+ "eval_loss": 2.7300503253936768,
546
+ "eval_runtime": 43.9017,
547
+ "eval_samples_per_second": 22.778,
548
+ "eval_steps_per_second": 2.847,
549
+ "step": 360
550
+ },
551
+ {
552
+ "epoch": 4.933333333333334,
553
+ "grad_norm": 2.8305609226226807,
554
+ "learning_rate": 3.614814814814815e-05,
555
+ "loss": 1.9332,
556
+ "step": 370
557
+ },
558
+ {
559
+ "epoch": 4.933333333333334,
560
+ "eval_loss": 2.7309281826019287,
561
+ "eval_runtime": 43.8842,
562
+ "eval_samples_per_second": 22.787,
563
+ "eval_steps_per_second": 2.848,
564
+ "step": 370
565
+ },
566
+ {
567
+ "epoch": 5.066666666666666,
568
+ "grad_norm": 2.8739213943481445,
569
+ "learning_rate": 3.4962962962962965e-05,
570
+ "loss": 1.8846,
571
+ "step": 380
572
+ },
573
+ {
574
+ "epoch": 5.066666666666666,
575
+ "eval_loss": 2.76513671875,
576
+ "eval_runtime": 43.906,
577
+ "eval_samples_per_second": 22.776,
578
+ "eval_steps_per_second": 2.847,
579
+ "step": 380
580
+ },
581
+ {
582
+ "epoch": 5.2,
583
+ "grad_norm": 3.9025838375091553,
584
+ "learning_rate": 3.377777777777778e-05,
585
+ "loss": 1.7575,
586
+ "step": 390
587
+ },
588
+ {
589
+ "epoch": 5.2,
590
+ "eval_loss": 2.847782611846924,
591
+ "eval_runtime": 43.8665,
592
+ "eval_samples_per_second": 22.796,
593
+ "eval_steps_per_second": 2.85,
594
+ "step": 390
595
+ },
596
+ {
597
+ "epoch": 5.333333333333333,
598
+ "grad_norm": 3.299649715423584,
599
+ "learning_rate": 3.259259259259259e-05,
600
+ "loss": 1.7713,
601
+ "step": 400
602
+ },
603
+ {
604
+ "epoch": 5.333333333333333,
605
+ "eval_loss": 2.8094286918640137,
606
+ "eval_runtime": 43.8629,
607
+ "eval_samples_per_second": 22.798,
608
+ "eval_steps_per_second": 2.85,
609
+ "step": 400
610
+ },
611
+ {
612
+ "epoch": 5.466666666666667,
613
+ "grad_norm": 3.4474265575408936,
614
+ "learning_rate": 3.140740740740741e-05,
615
+ "loss": 1.7983,
616
+ "step": 410
617
+ },
618
+ {
619
+ "epoch": 5.466666666666667,
620
+ "eval_loss": 2.827517509460449,
621
+ "eval_runtime": 43.8611,
622
+ "eval_samples_per_second": 22.799,
623
+ "eval_steps_per_second": 2.85,
624
+ "step": 410
625
+ },
626
+ {
627
+ "epoch": 5.6,
628
+ "grad_norm": 3.1924540996551514,
629
+ "learning_rate": 3.0222222222222225e-05,
630
+ "loss": 1.8091,
631
+ "step": 420
632
+ },
633
+ {
634
+ "epoch": 5.6,
635
+ "eval_loss": 2.81618332862854,
636
+ "eval_runtime": 43.8544,
637
+ "eval_samples_per_second": 22.803,
638
+ "eval_steps_per_second": 2.85,
639
+ "step": 420
640
+ },
641
+ {
642
+ "epoch": 5.733333333333333,
643
+ "grad_norm": 3.5224015712738037,
644
+ "learning_rate": 2.9037037037037042e-05,
645
+ "loss": 1.8253,
646
+ "step": 430
647
+ },
648
+ {
649
+ "epoch": 5.733333333333333,
650
+ "eval_loss": 2.816711187362671,
651
+ "eval_runtime": 43.8685,
652
+ "eval_samples_per_second": 22.795,
653
+ "eval_steps_per_second": 2.849,
654
+ "step": 430
655
+ },
656
+ {
657
+ "epoch": 5.866666666666667,
658
+ "grad_norm": 3.60918927192688,
659
+ "learning_rate": 2.7851851851851856e-05,
660
+ "loss": 1.8013,
661
+ "step": 440
662
+ },
663
+ {
664
+ "epoch": 5.866666666666667,
665
+ "eval_loss": 2.8146169185638428,
666
+ "eval_runtime": 43.8516,
667
+ "eval_samples_per_second": 22.804,
668
+ "eval_steps_per_second": 2.851,
669
+ "step": 440
670
+ },
671
+ {
672
+ "epoch": 6.0,
673
+ "grad_norm": 3.5798070430755615,
674
+ "learning_rate": 2.6666666666666667e-05,
675
+ "loss": 1.8258,
676
+ "step": 450
677
+ },
678
+ {
679
+ "epoch": 6.0,
680
+ "eval_loss": 2.8134233951568604,
681
+ "eval_runtime": 43.8442,
682
+ "eval_samples_per_second": 22.808,
683
+ "eval_steps_per_second": 2.851,
684
+ "step": 450
685
+ },
686
+ {
687
+ "epoch": 6.133333333333334,
688
+ "grad_norm": 5.563477993011475,
689
+ "learning_rate": 2.5481481481481484e-05,
690
+ "loss": 1.6649,
691
+ "step": 460
692
+ },
693
+ {
694
+ "epoch": 6.133333333333334,
695
+ "eval_loss": 2.9189789295196533,
696
+ "eval_runtime": 43.8602,
697
+ "eval_samples_per_second": 22.8,
698
+ "eval_steps_per_second": 2.85,
699
+ "step": 460
700
+ },
701
+ {
702
+ "epoch": 6.266666666666667,
703
+ "grad_norm": 4.192393779754639,
704
+ "learning_rate": 2.4296296296296298e-05,
705
+ "loss": 1.7443,
706
+ "step": 470
707
+ },
708
+ {
709
+ "epoch": 6.266666666666667,
710
+ "eval_loss": 2.893780469894409,
711
+ "eval_runtime": 43.8434,
712
+ "eval_samples_per_second": 22.808,
713
+ "eval_steps_per_second": 2.851,
714
+ "step": 470
715
+ },
716
+ {
717
+ "epoch": 6.4,
718
+ "grad_norm": 4.8650593757629395,
719
+ "learning_rate": 2.3111111111111112e-05,
720
+ "loss": 1.6961,
721
+ "step": 480
722
+ },
723
+ {
724
+ "epoch": 6.4,
725
+ "eval_loss": 2.8861398696899414,
726
+ "eval_runtime": 43.8417,
727
+ "eval_samples_per_second": 22.809,
728
+ "eval_steps_per_second": 2.851,
729
+ "step": 480
730
+ },
731
+ {
732
+ "epoch": 6.533333333333333,
733
+ "grad_norm": 3.844482660293579,
734
+ "learning_rate": 2.192592592592593e-05,
735
+ "loss": 1.6868,
736
+ "step": 490
737
+ },
738
+ {
739
+ "epoch": 6.533333333333333,
740
+ "eval_loss": 2.900317907333374,
741
+ "eval_runtime": 43.8557,
742
+ "eval_samples_per_second": 22.802,
743
+ "eval_steps_per_second": 2.85,
744
+ "step": 490
745
+ },
746
+ {
747
+ "epoch": 6.666666666666667,
748
+ "grad_norm": 4.230032920837402,
749
+ "learning_rate": 2.074074074074074e-05,
750
+ "loss": 1.6593,
751
+ "step": 500
752
+ },
753
+ {
754
+ "epoch": 6.666666666666667,
755
+ "eval_loss": 2.892076253890991,
756
+ "eval_runtime": 43.8479,
757
+ "eval_samples_per_second": 22.806,
758
+ "eval_steps_per_second": 2.851,
759
+ "step": 500
760
+ },
761
+ {
762
+ "epoch": 6.8,
763
+ "grad_norm": 4.427380561828613,
764
+ "learning_rate": 1.9555555555555557e-05,
765
+ "loss": 1.6777,
766
+ "step": 510
767
+ },
768
+ {
769
+ "epoch": 6.8,
770
+ "eval_loss": 2.8877696990966797,
771
+ "eval_runtime": 43.8489,
772
+ "eval_samples_per_second": 22.806,
773
+ "eval_steps_per_second": 2.851,
774
+ "step": 510
775
+ },
776
+ {
777
+ "epoch": 6.933333333333334,
778
+ "grad_norm": 4.23176908493042,
779
+ "learning_rate": 1.837037037037037e-05,
780
+ "loss": 1.7331,
781
+ "step": 520
782
+ },
783
+ {
784
+ "epoch": 6.933333333333334,
785
+ "eval_loss": 2.889272928237915,
786
+ "eval_runtime": 43.8577,
787
+ "eval_samples_per_second": 22.801,
788
+ "eval_steps_per_second": 2.85,
789
+ "step": 520
790
+ },
791
+ {
792
+ "epoch": 7.066666666666666,
793
+ "grad_norm": 3.9098429679870605,
794
+ "learning_rate": 1.7185185185185185e-05,
795
+ "loss": 1.6741,
796
+ "step": 530
797
+ },
798
+ {
799
+ "epoch": 7.066666666666666,
800
+ "eval_loss": 2.9202494621276855,
801
+ "eval_runtime": 43.8571,
802
+ "eval_samples_per_second": 22.801,
803
+ "eval_steps_per_second": 2.85,
804
+ "step": 530
805
+ },
806
+ {
807
+ "epoch": 7.2,
808
+ "grad_norm": 4.320191383361816,
809
+ "learning_rate": 1.6000000000000003e-05,
810
+ "loss": 1.5711,
811
+ "step": 540
812
+ },
813
+ {
814
+ "epoch": 7.2,
815
+ "eval_loss": 2.97855806350708,
816
+ "eval_runtime": 43.8599,
817
+ "eval_samples_per_second": 22.8,
818
+ "eval_steps_per_second": 2.85,
819
+ "step": 540
820
+ },
821
+ {
822
+ "epoch": 7.333333333333333,
823
+ "grad_norm": 4.003049850463867,
824
+ "learning_rate": 1.4814814814814815e-05,
825
+ "loss": 1.6106,
826
+ "step": 550
827
+ },
828
+ {
829
+ "epoch": 7.333333333333333,
830
+ "eval_loss": 2.9440739154815674,
831
+ "eval_runtime": 43.8605,
832
+ "eval_samples_per_second": 22.8,
833
+ "eval_steps_per_second": 2.85,
834
+ "step": 550
835
+ },
836
+ {
837
+ "epoch": 7.466666666666667,
838
+ "grad_norm": 4.265935897827148,
839
+ "learning_rate": 1.362962962962963e-05,
840
+ "loss": 1.6241,
841
+ "step": 560
842
+ },
843
+ {
844
+ "epoch": 7.466666666666667,
845
+ "eval_loss": 2.958505630493164,
846
+ "eval_runtime": 43.8614,
847
+ "eval_samples_per_second": 22.799,
848
+ "eval_steps_per_second": 2.85,
849
+ "step": 560
850
+ },
851
+ {
852
+ "epoch": 7.6,
853
+ "grad_norm": 5.025564670562744,
854
+ "learning_rate": 1.2444444444444446e-05,
855
+ "loss": 1.6306,
856
+ "step": 570
857
+ },
858
+ {
859
+ "epoch": 7.6,
860
+ "eval_loss": 2.956601619720459,
861
+ "eval_runtime": 43.8595,
862
+ "eval_samples_per_second": 22.8,
863
+ "eval_steps_per_second": 2.85,
864
+ "step": 570
865
+ },
866
+ {
867
+ "epoch": 7.733333333333333,
868
+ "grad_norm": 4.252591133117676,
869
+ "learning_rate": 1.125925925925926e-05,
870
+ "loss": 1.5933,
871
+ "step": 580
872
+ },
873
+ {
874
+ "epoch": 7.733333333333333,
875
+ "eval_loss": 2.9567930698394775,
876
+ "eval_runtime": 43.8568,
877
+ "eval_samples_per_second": 22.801,
878
+ "eval_steps_per_second": 2.85,
879
+ "step": 580
880
+ },
881
+ {
882
+ "epoch": 7.866666666666667,
883
+ "grad_norm": 4.484741687774658,
884
+ "learning_rate": 1.0192592592592594e-05,
885
+ "loss": 1.6441,
886
+ "step": 590
887
+ },
888
+ {
889
+ "epoch": 7.866666666666667,
890
+ "eval_loss": 2.9549593925476074,
891
+ "eval_runtime": 43.8579,
892
+ "eval_samples_per_second": 22.801,
893
+ "eval_steps_per_second": 2.85,
894
+ "step": 590
895
+ }
896
+ ],
897
+ "logging_steps": 10,
898
+ "max_steps": 675,
899
+ "num_input_tokens_seen": 0,
900
+ "num_train_epochs": 9,
901
+ "save_steps": 10,
902
+ "stateful_callbacks": {
903
+ "TrainerControl": {
904
+ "args": {
905
+ "should_epoch_stop": false,
906
+ "should_evaluate": false,
907
+ "should_log": false,
908
+ "should_save": true,
909
+ "should_training_stop": false
910
+ },
911
+ "attributes": {}
912
+ }
913
+ },
914
+ "total_flos": 9.66778247184384e+16,
915
+ "train_batch_size": 8,
916
+ "trial_name": null,
917
+ "trial_params": null
918
+ }
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-600/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/pythia-6_9b
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-600/adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/workspace/pythia-6_9b",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.1,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 8,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "dense_h_to_4h",
24
+ "query_key_value",
25
+ "dense",
26
+ "dense_4h_to_h"
27
+ ],
28
+ "task_type": "CAUSAL_LM",
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-600/trainer_state.json ADDED
@@ -0,0 +1,933 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 2.535032033920288,
3
+ "best_model_checkpoint": "./output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-150",
4
+ "epoch": 8.0,
5
+ "eval_steps": 10,
6
+ "global_step": 600,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.13333333333333333,
13
+ "grad_norm": 0.36938729882240295,
14
+ "learning_rate": 7.881481481481482e-05,
15
+ "loss": 2.519,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.13333333333333333,
20
+ "eval_loss": 2.579638957977295,
21
+ "eval_runtime": 43.8215,
22
+ "eval_samples_per_second": 22.82,
23
+ "eval_steps_per_second": 2.852,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.26666666666666666,
28
+ "grad_norm": 0.39850670099258423,
29
+ "learning_rate": 7.762962962962963e-05,
30
+ "loss": 2.5224,
31
+ "step": 20
32
+ },
33
+ {
34
+ "epoch": 0.26666666666666666,
35
+ "eval_loss": 2.5729691982269287,
36
+ "eval_runtime": 43.8179,
37
+ "eval_samples_per_second": 22.822,
38
+ "eval_steps_per_second": 2.853,
39
+ "step": 20
40
+ },
41
+ {
42
+ "epoch": 0.4,
43
+ "grad_norm": 0.40211933851242065,
44
+ "learning_rate": 7.644444444444445e-05,
45
+ "loss": 2.5169,
46
+ "step": 30
47
+ },
48
+ {
49
+ "epoch": 0.4,
50
+ "eval_loss": 2.567735433578491,
51
+ "eval_runtime": 43.8366,
52
+ "eval_samples_per_second": 22.812,
53
+ "eval_steps_per_second": 2.851,
54
+ "step": 30
55
+ },
56
+ {
57
+ "epoch": 0.5333333333333333,
58
+ "grad_norm": 0.6892333030700684,
59
+ "learning_rate": 7.525925925925926e-05,
60
+ "loss": 2.5784,
61
+ "step": 40
62
+ },
63
+ {
64
+ "epoch": 0.5333333333333333,
65
+ "eval_loss": 2.562650442123413,
66
+ "eval_runtime": 43.8377,
67
+ "eval_samples_per_second": 22.811,
68
+ "eval_steps_per_second": 2.851,
69
+ "step": 40
70
+ },
71
+ {
72
+ "epoch": 0.6666666666666666,
73
+ "grad_norm": 0.442343533039093,
74
+ "learning_rate": 7.407407407407409e-05,
75
+ "loss": 2.5431,
76
+ "step": 50
77
+ },
78
+ {
79
+ "epoch": 0.6666666666666666,
80
+ "eval_loss": 2.556513786315918,
81
+ "eval_runtime": 43.8656,
82
+ "eval_samples_per_second": 22.797,
83
+ "eval_steps_per_second": 2.85,
84
+ "step": 50
85
+ },
86
+ {
87
+ "epoch": 0.8,
88
+ "grad_norm": 0.4059845805168152,
89
+ "learning_rate": 7.28888888888889e-05,
90
+ "loss": 2.4936,
91
+ "step": 60
92
+ },
93
+ {
94
+ "epoch": 0.8,
95
+ "eval_loss": 2.552133798599243,
96
+ "eval_runtime": 43.8403,
97
+ "eval_samples_per_second": 22.81,
98
+ "eval_steps_per_second": 2.851,
99
+ "step": 60
100
+ },
101
+ {
102
+ "epoch": 0.9333333333333333,
103
+ "grad_norm": 0.48126307129859924,
104
+ "learning_rate": 7.170370370370371e-05,
105
+ "loss": 2.4901,
106
+ "step": 70
107
+ },
108
+ {
109
+ "epoch": 0.9333333333333333,
110
+ "eval_loss": 2.5477023124694824,
111
+ "eval_runtime": 43.8351,
112
+ "eval_samples_per_second": 22.813,
113
+ "eval_steps_per_second": 2.852,
114
+ "step": 70
115
+ },
116
+ {
117
+ "epoch": 1.0666666666666667,
118
+ "grad_norm": 0.48629865050315857,
119
+ "learning_rate": 7.051851851851853e-05,
120
+ "loss": 2.5114,
121
+ "step": 80
122
+ },
123
+ {
124
+ "epoch": 1.0666666666666667,
125
+ "eval_loss": 2.543431043624878,
126
+ "eval_runtime": 43.8432,
127
+ "eval_samples_per_second": 22.809,
128
+ "eval_steps_per_second": 2.851,
129
+ "step": 80
130
+ },
131
+ {
132
+ "epoch": 1.2,
133
+ "grad_norm": 0.5880796313285828,
134
+ "learning_rate": 6.933333333333334e-05,
135
+ "loss": 2.4446,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 1.2,
140
+ "eval_loss": 2.544339418411255,
141
+ "eval_runtime": 43.8437,
142
+ "eval_samples_per_second": 22.808,
143
+ "eval_steps_per_second": 2.851,
144
+ "step": 90
145
+ },
146
+ {
147
+ "epoch": 1.3333333333333333,
148
+ "grad_norm": 0.6746829748153687,
149
+ "learning_rate": 6.814814814814815e-05,
150
+ "loss": 2.4477,
151
+ "step": 100
152
+ },
153
+ {
154
+ "epoch": 1.3333333333333333,
155
+ "eval_loss": 2.544358968734741,
156
+ "eval_runtime": 43.8613,
157
+ "eval_samples_per_second": 22.799,
158
+ "eval_steps_per_second": 2.85,
159
+ "step": 100
160
+ },
161
+ {
162
+ "epoch": 1.4666666666666668,
163
+ "grad_norm": 0.8208937048912048,
164
+ "learning_rate": 6.696296296296296e-05,
165
+ "loss": 2.4004,
166
+ "step": 110
167
+ },
168
+ {
169
+ "epoch": 1.4666666666666668,
170
+ "eval_loss": 2.54068660736084,
171
+ "eval_runtime": 43.8426,
172
+ "eval_samples_per_second": 22.809,
173
+ "eval_steps_per_second": 2.851,
174
+ "step": 110
175
+ },
176
+ {
177
+ "epoch": 1.6,
178
+ "grad_norm": 0.925931453704834,
179
+ "learning_rate": 6.577777777777777e-05,
180
+ "loss": 2.3889,
181
+ "step": 120
182
+ },
183
+ {
184
+ "epoch": 1.6,
185
+ "eval_loss": 2.5393033027648926,
186
+ "eval_runtime": 43.8383,
187
+ "eval_samples_per_second": 22.811,
188
+ "eval_steps_per_second": 2.851,
189
+ "step": 120
190
+ },
191
+ {
192
+ "epoch": 1.7333333333333334,
193
+ "grad_norm": 0.8785662055015564,
194
+ "learning_rate": 6.45925925925926e-05,
195
+ "loss": 2.3959,
196
+ "step": 130
197
+ },
198
+ {
199
+ "epoch": 1.7333333333333334,
200
+ "eval_loss": 2.5367038249969482,
201
+ "eval_runtime": 43.8508,
202
+ "eval_samples_per_second": 22.805,
203
+ "eval_steps_per_second": 2.851,
204
+ "step": 130
205
+ },
206
+ {
207
+ "epoch": 1.8666666666666667,
208
+ "grad_norm": 0.941368818283081,
209
+ "learning_rate": 6.340740740740741e-05,
210
+ "loss": 2.3924,
211
+ "step": 140
212
+ },
213
+ {
214
+ "epoch": 1.8666666666666667,
215
+ "eval_loss": 2.535139560699463,
216
+ "eval_runtime": 43.8588,
217
+ "eval_samples_per_second": 22.8,
218
+ "eval_steps_per_second": 2.85,
219
+ "step": 140
220
+ },
221
+ {
222
+ "epoch": 2.0,
223
+ "grad_norm": 0.9578835368156433,
224
+ "learning_rate": 6.222222222222223e-05,
225
+ "loss": 2.4278,
226
+ "step": 150
227
+ },
228
+ {
229
+ "epoch": 2.0,
230
+ "eval_loss": 2.535032033920288,
231
+ "eval_runtime": 43.8484,
232
+ "eval_samples_per_second": 22.806,
233
+ "eval_steps_per_second": 2.851,
234
+ "step": 150
235
+ },
236
+ {
237
+ "epoch": 2.1333333333333333,
238
+ "grad_norm": 1.1541856527328491,
239
+ "learning_rate": 6.103703703703704e-05,
240
+ "loss": 2.2895,
241
+ "step": 160
242
+ },
243
+ {
244
+ "epoch": 2.1333333333333333,
245
+ "eval_loss": 2.564768075942993,
246
+ "eval_runtime": 43.8568,
247
+ "eval_samples_per_second": 22.801,
248
+ "eval_steps_per_second": 2.85,
249
+ "step": 160
250
+ },
251
+ {
252
+ "epoch": 2.2666666666666666,
253
+ "grad_norm": 1.4076604843139648,
254
+ "learning_rate": 5.9851851851851855e-05,
255
+ "loss": 2.2107,
256
+ "step": 170
257
+ },
258
+ {
259
+ "epoch": 2.2666666666666666,
260
+ "eval_loss": 2.5832314491271973,
261
+ "eval_runtime": 43.8455,
262
+ "eval_samples_per_second": 22.807,
263
+ "eval_steps_per_second": 2.851,
264
+ "step": 170
265
+ },
266
+ {
267
+ "epoch": 2.4,
268
+ "grad_norm": 1.4847813844680786,
269
+ "learning_rate": 5.8666666666666665e-05,
270
+ "loss": 2.2588,
271
+ "step": 180
272
+ },
273
+ {
274
+ "epoch": 2.4,
275
+ "eval_loss": 2.5781586170196533,
276
+ "eval_runtime": 43.8578,
277
+ "eval_samples_per_second": 22.801,
278
+ "eval_steps_per_second": 2.85,
279
+ "step": 180
280
+ },
281
+ {
282
+ "epoch": 2.533333333333333,
283
+ "grad_norm": 1.5135377645492554,
284
+ "learning_rate": 5.748148148148149e-05,
285
+ "loss": 2.2099,
286
+ "step": 190
287
+ },
288
+ {
289
+ "epoch": 2.533333333333333,
290
+ "eval_loss": 2.5752007961273193,
291
+ "eval_runtime": 43.8521,
292
+ "eval_samples_per_second": 22.804,
293
+ "eval_steps_per_second": 2.85,
294
+ "step": 190
295
+ },
296
+ {
297
+ "epoch": 2.6666666666666665,
298
+ "grad_norm": 1.5297592878341675,
299
+ "learning_rate": 5.62962962962963e-05,
300
+ "loss": 2.2965,
301
+ "step": 200
302
+ },
303
+ {
304
+ "epoch": 2.6666666666666665,
305
+ "eval_loss": 2.579918622970581,
306
+ "eval_runtime": 43.8661,
307
+ "eval_samples_per_second": 22.797,
308
+ "eval_steps_per_second": 2.85,
309
+ "step": 200
310
+ },
311
+ {
312
+ "epoch": 2.8,
313
+ "grad_norm": 1.6282892227172852,
314
+ "learning_rate": 5.511111111111112e-05,
315
+ "loss": 2.2487,
316
+ "step": 210
317
+ },
318
+ {
319
+ "epoch": 2.8,
320
+ "eval_loss": 2.5760037899017334,
321
+ "eval_runtime": 43.8379,
322
+ "eval_samples_per_second": 22.811,
323
+ "eval_steps_per_second": 2.851,
324
+ "step": 210
325
+ },
326
+ {
327
+ "epoch": 2.9333333333333336,
328
+ "grad_norm": 1.74424409866333,
329
+ "learning_rate": 5.392592592592593e-05,
330
+ "loss": 2.2049,
331
+ "step": 220
332
+ },
333
+ {
334
+ "epoch": 2.9333333333333336,
335
+ "eval_loss": 2.576190233230591,
336
+ "eval_runtime": 43.8491,
337
+ "eval_samples_per_second": 22.805,
338
+ "eval_steps_per_second": 2.851,
339
+ "step": 220
340
+ },
341
+ {
342
+ "epoch": 3.066666666666667,
343
+ "grad_norm": 1.654069423675537,
344
+ "learning_rate": 5.274074074074074e-05,
345
+ "loss": 2.1188,
346
+ "step": 230
347
+ },
348
+ {
349
+ "epoch": 3.066666666666667,
350
+ "eval_loss": 2.5971405506134033,
351
+ "eval_runtime": 43.855,
352
+ "eval_samples_per_second": 22.802,
353
+ "eval_steps_per_second": 2.85,
354
+ "step": 230
355
+ },
356
+ {
357
+ "epoch": 3.2,
358
+ "grad_norm": 2.541767120361328,
359
+ "learning_rate": 5.155555555555556e-05,
360
+ "loss": 2.0788,
361
+ "step": 240
362
+ },
363
+ {
364
+ "epoch": 3.2,
365
+ "eval_loss": 2.6767666339874268,
366
+ "eval_runtime": 43.8368,
367
+ "eval_samples_per_second": 22.812,
368
+ "eval_steps_per_second": 2.851,
369
+ "step": 240
370
+ },
371
+ {
372
+ "epoch": 3.3333333333333335,
373
+ "grad_norm": 2.0508077144622803,
374
+ "learning_rate": 5.037037037037037e-05,
375
+ "loss": 2.0784,
376
+ "step": 250
377
+ },
378
+ {
379
+ "epoch": 3.3333333333333335,
380
+ "eval_loss": 2.6486454010009766,
381
+ "eval_runtime": 43.8529,
382
+ "eval_samples_per_second": 22.803,
383
+ "eval_steps_per_second": 2.85,
384
+ "step": 250
385
+ },
386
+ {
387
+ "epoch": 3.466666666666667,
388
+ "grad_norm": 2.1096036434173584,
389
+ "learning_rate": 4.918518518518519e-05,
390
+ "loss": 2.0633,
391
+ "step": 260
392
+ },
393
+ {
394
+ "epoch": 3.466666666666667,
395
+ "eval_loss": 2.6501405239105225,
396
+ "eval_runtime": 43.8632,
397
+ "eval_samples_per_second": 22.798,
398
+ "eval_steps_per_second": 2.85,
399
+ "step": 260
400
+ },
401
+ {
402
+ "epoch": 3.6,
403
+ "grad_norm": 2.3028736114501953,
404
+ "learning_rate": 4.8e-05,
405
+ "loss": 2.0722,
406
+ "step": 270
407
+ },
408
+ {
409
+ "epoch": 3.6,
410
+ "eval_loss": 2.657053232192993,
411
+ "eval_runtime": 43.8423,
412
+ "eval_samples_per_second": 22.809,
413
+ "eval_steps_per_second": 2.851,
414
+ "step": 270
415
+ },
416
+ {
417
+ "epoch": 3.7333333333333334,
418
+ "grad_norm": 2.1536757946014404,
419
+ "learning_rate": 4.681481481481481e-05,
420
+ "loss": 2.0155,
421
+ "step": 280
422
+ },
423
+ {
424
+ "epoch": 3.7333333333333334,
425
+ "eval_loss": 2.648275375366211,
426
+ "eval_runtime": 43.8328,
427
+ "eval_samples_per_second": 22.814,
428
+ "eval_steps_per_second": 2.852,
429
+ "step": 280
430
+ },
431
+ {
432
+ "epoch": 3.8666666666666667,
433
+ "grad_norm": 2.4079270362854004,
434
+ "learning_rate": 4.5629629629629636e-05,
435
+ "loss": 2.1111,
436
+ "step": 290
437
+ },
438
+ {
439
+ "epoch": 3.8666666666666667,
440
+ "eval_loss": 2.650322675704956,
441
+ "eval_runtime": 43.835,
442
+ "eval_samples_per_second": 22.813,
443
+ "eval_steps_per_second": 2.852,
444
+ "step": 290
445
+ },
446
+ {
447
+ "epoch": 4.0,
448
+ "grad_norm": 2.426234722137451,
449
+ "learning_rate": 4.444444444444445e-05,
450
+ "loss": 2.041,
451
+ "step": 300
452
+ },
453
+ {
454
+ "epoch": 4.0,
455
+ "eval_loss": 2.6490862369537354,
456
+ "eval_runtime": 43.845,
457
+ "eval_samples_per_second": 22.808,
458
+ "eval_steps_per_second": 2.851,
459
+ "step": 300
460
+ },
461
+ {
462
+ "epoch": 4.133333333333334,
463
+ "grad_norm": 2.8063745498657227,
464
+ "learning_rate": 4.3259259259259264e-05,
465
+ "loss": 1.9316,
466
+ "step": 310
467
+ },
468
+ {
469
+ "epoch": 4.133333333333334,
470
+ "eval_loss": 2.7609620094299316,
471
+ "eval_runtime": 43.8481,
472
+ "eval_samples_per_second": 22.806,
473
+ "eval_steps_per_second": 2.851,
474
+ "step": 310
475
+ },
476
+ {
477
+ "epoch": 4.266666666666667,
478
+ "grad_norm": 2.96854305267334,
479
+ "learning_rate": 4.2074074074074075e-05,
480
+ "loss": 1.8889,
481
+ "step": 320
482
+ },
483
+ {
484
+ "epoch": 4.266666666666667,
485
+ "eval_loss": 2.736968994140625,
486
+ "eval_runtime": 43.8633,
487
+ "eval_samples_per_second": 22.798,
488
+ "eval_steps_per_second": 2.85,
489
+ "step": 320
490
+ },
491
+ {
492
+ "epoch": 4.4,
493
+ "grad_norm": 2.637695789337158,
494
+ "learning_rate": 4.088888888888889e-05,
495
+ "loss": 1.9187,
496
+ "step": 330
497
+ },
498
+ {
499
+ "epoch": 4.4,
500
+ "eval_loss": 2.7382876873016357,
501
+ "eval_runtime": 43.8486,
502
+ "eval_samples_per_second": 22.806,
503
+ "eval_steps_per_second": 2.851,
504
+ "step": 330
505
+ },
506
+ {
507
+ "epoch": 4.533333333333333,
508
+ "grad_norm": 2.9106290340423584,
509
+ "learning_rate": 3.970370370370371e-05,
510
+ "loss": 1.9002,
511
+ "step": 340
512
+ },
513
+ {
514
+ "epoch": 4.533333333333333,
515
+ "eval_loss": 2.734544515609741,
516
+ "eval_runtime": 43.8491,
517
+ "eval_samples_per_second": 22.805,
518
+ "eval_steps_per_second": 2.851,
519
+ "step": 340
520
+ },
521
+ {
522
+ "epoch": 4.666666666666667,
523
+ "grad_norm": 2.769315481185913,
524
+ "learning_rate": 3.851851851851852e-05,
525
+ "loss": 1.9251,
526
+ "step": 350
527
+ },
528
+ {
529
+ "epoch": 4.666666666666667,
530
+ "eval_loss": 2.734708070755005,
531
+ "eval_runtime": 43.8534,
532
+ "eval_samples_per_second": 22.803,
533
+ "eval_steps_per_second": 2.85,
534
+ "step": 350
535
+ },
536
+ {
537
+ "epoch": 4.8,
538
+ "grad_norm": 2.940281867980957,
539
+ "learning_rate": 3.733333333333334e-05,
540
+ "loss": 1.9319,
541
+ "step": 360
542
+ },
543
+ {
544
+ "epoch": 4.8,
545
+ "eval_loss": 2.7300503253936768,
546
+ "eval_runtime": 43.9017,
547
+ "eval_samples_per_second": 22.778,
548
+ "eval_steps_per_second": 2.847,
549
+ "step": 360
550
+ },
551
+ {
552
+ "epoch": 4.933333333333334,
553
+ "grad_norm": 2.8305609226226807,
554
+ "learning_rate": 3.614814814814815e-05,
555
+ "loss": 1.9332,
556
+ "step": 370
557
+ },
558
+ {
559
+ "epoch": 4.933333333333334,
560
+ "eval_loss": 2.7309281826019287,
561
+ "eval_runtime": 43.8842,
562
+ "eval_samples_per_second": 22.787,
563
+ "eval_steps_per_second": 2.848,
564
+ "step": 370
565
+ },
566
+ {
567
+ "epoch": 5.066666666666666,
568
+ "grad_norm": 2.8739213943481445,
569
+ "learning_rate": 3.4962962962962965e-05,
570
+ "loss": 1.8846,
571
+ "step": 380
572
+ },
573
+ {
574
+ "epoch": 5.066666666666666,
575
+ "eval_loss": 2.76513671875,
576
+ "eval_runtime": 43.906,
577
+ "eval_samples_per_second": 22.776,
578
+ "eval_steps_per_second": 2.847,
579
+ "step": 380
580
+ },
581
+ {
582
+ "epoch": 5.2,
583
+ "grad_norm": 3.9025838375091553,
584
+ "learning_rate": 3.377777777777778e-05,
585
+ "loss": 1.7575,
586
+ "step": 390
587
+ },
588
+ {
589
+ "epoch": 5.2,
590
+ "eval_loss": 2.847782611846924,
591
+ "eval_runtime": 43.8665,
592
+ "eval_samples_per_second": 22.796,
593
+ "eval_steps_per_second": 2.85,
594
+ "step": 390
595
+ },
596
+ {
597
+ "epoch": 5.333333333333333,
598
+ "grad_norm": 3.299649715423584,
599
+ "learning_rate": 3.259259259259259e-05,
600
+ "loss": 1.7713,
601
+ "step": 400
602
+ },
603
+ {
604
+ "epoch": 5.333333333333333,
605
+ "eval_loss": 2.8094286918640137,
606
+ "eval_runtime": 43.8629,
607
+ "eval_samples_per_second": 22.798,
608
+ "eval_steps_per_second": 2.85,
609
+ "step": 400
610
+ },
611
+ {
612
+ "epoch": 5.466666666666667,
613
+ "grad_norm": 3.4474265575408936,
614
+ "learning_rate": 3.140740740740741e-05,
615
+ "loss": 1.7983,
616
+ "step": 410
617
+ },
618
+ {
619
+ "epoch": 5.466666666666667,
620
+ "eval_loss": 2.827517509460449,
621
+ "eval_runtime": 43.8611,
622
+ "eval_samples_per_second": 22.799,
623
+ "eval_steps_per_second": 2.85,
624
+ "step": 410
625
+ },
626
+ {
627
+ "epoch": 5.6,
628
+ "grad_norm": 3.1924540996551514,
629
+ "learning_rate": 3.0222222222222225e-05,
630
+ "loss": 1.8091,
631
+ "step": 420
632
+ },
633
+ {
634
+ "epoch": 5.6,
635
+ "eval_loss": 2.81618332862854,
636
+ "eval_runtime": 43.8544,
637
+ "eval_samples_per_second": 22.803,
638
+ "eval_steps_per_second": 2.85,
639
+ "step": 420
640
+ },
641
+ {
642
+ "epoch": 5.733333333333333,
643
+ "grad_norm": 3.5224015712738037,
644
+ "learning_rate": 2.9037037037037042e-05,
645
+ "loss": 1.8253,
646
+ "step": 430
647
+ },
648
+ {
649
+ "epoch": 5.733333333333333,
650
+ "eval_loss": 2.816711187362671,
651
+ "eval_runtime": 43.8685,
652
+ "eval_samples_per_second": 22.795,
653
+ "eval_steps_per_second": 2.849,
654
+ "step": 430
655
+ },
656
+ {
657
+ "epoch": 5.866666666666667,
658
+ "grad_norm": 3.60918927192688,
659
+ "learning_rate": 2.7851851851851856e-05,
660
+ "loss": 1.8013,
661
+ "step": 440
662
+ },
663
+ {
664
+ "epoch": 5.866666666666667,
665
+ "eval_loss": 2.8146169185638428,
666
+ "eval_runtime": 43.8516,
667
+ "eval_samples_per_second": 22.804,
668
+ "eval_steps_per_second": 2.851,
669
+ "step": 440
670
+ },
671
+ {
672
+ "epoch": 6.0,
673
+ "grad_norm": 3.5798070430755615,
674
+ "learning_rate": 2.6666666666666667e-05,
675
+ "loss": 1.8258,
676
+ "step": 450
677
+ },
678
+ {
679
+ "epoch": 6.0,
680
+ "eval_loss": 2.8134233951568604,
681
+ "eval_runtime": 43.8442,
682
+ "eval_samples_per_second": 22.808,
683
+ "eval_steps_per_second": 2.851,
684
+ "step": 450
685
+ },
686
+ {
687
+ "epoch": 6.133333333333334,
688
+ "grad_norm": 5.563477993011475,
689
+ "learning_rate": 2.5481481481481484e-05,
690
+ "loss": 1.6649,
691
+ "step": 460
692
+ },
693
+ {
694
+ "epoch": 6.133333333333334,
695
+ "eval_loss": 2.9189789295196533,
696
+ "eval_runtime": 43.8602,
697
+ "eval_samples_per_second": 22.8,
698
+ "eval_steps_per_second": 2.85,
699
+ "step": 460
700
+ },
701
+ {
702
+ "epoch": 6.266666666666667,
703
+ "grad_norm": 4.192393779754639,
704
+ "learning_rate": 2.4296296296296298e-05,
705
+ "loss": 1.7443,
706
+ "step": 470
707
+ },
708
+ {
709
+ "epoch": 6.266666666666667,
710
+ "eval_loss": 2.893780469894409,
711
+ "eval_runtime": 43.8434,
712
+ "eval_samples_per_second": 22.808,
713
+ "eval_steps_per_second": 2.851,
714
+ "step": 470
715
+ },
716
+ {
717
+ "epoch": 6.4,
718
+ "grad_norm": 4.8650593757629395,
719
+ "learning_rate": 2.3111111111111112e-05,
720
+ "loss": 1.6961,
721
+ "step": 480
722
+ },
723
+ {
724
+ "epoch": 6.4,
725
+ "eval_loss": 2.8861398696899414,
726
+ "eval_runtime": 43.8417,
727
+ "eval_samples_per_second": 22.809,
728
+ "eval_steps_per_second": 2.851,
729
+ "step": 480
730
+ },
731
+ {
732
+ "epoch": 6.533333333333333,
733
+ "grad_norm": 3.844482660293579,
734
+ "learning_rate": 2.192592592592593e-05,
735
+ "loss": 1.6868,
736
+ "step": 490
737
+ },
738
+ {
739
+ "epoch": 6.533333333333333,
740
+ "eval_loss": 2.900317907333374,
741
+ "eval_runtime": 43.8557,
742
+ "eval_samples_per_second": 22.802,
743
+ "eval_steps_per_second": 2.85,
744
+ "step": 490
745
+ },
746
+ {
747
+ "epoch": 6.666666666666667,
748
+ "grad_norm": 4.230032920837402,
749
+ "learning_rate": 2.074074074074074e-05,
750
+ "loss": 1.6593,
751
+ "step": 500
752
+ },
753
+ {
754
+ "epoch": 6.666666666666667,
755
+ "eval_loss": 2.892076253890991,
756
+ "eval_runtime": 43.8479,
757
+ "eval_samples_per_second": 22.806,
758
+ "eval_steps_per_second": 2.851,
759
+ "step": 500
760
+ },
761
+ {
762
+ "epoch": 6.8,
763
+ "grad_norm": 4.427380561828613,
764
+ "learning_rate": 1.9555555555555557e-05,
765
+ "loss": 1.6777,
766
+ "step": 510
767
+ },
768
+ {
769
+ "epoch": 6.8,
770
+ "eval_loss": 2.8877696990966797,
771
+ "eval_runtime": 43.8489,
772
+ "eval_samples_per_second": 22.806,
773
+ "eval_steps_per_second": 2.851,
774
+ "step": 510
775
+ },
776
+ {
777
+ "epoch": 6.933333333333334,
778
+ "grad_norm": 4.23176908493042,
779
+ "learning_rate": 1.837037037037037e-05,
780
+ "loss": 1.7331,
781
+ "step": 520
782
+ },
783
+ {
784
+ "epoch": 6.933333333333334,
785
+ "eval_loss": 2.889272928237915,
786
+ "eval_runtime": 43.8577,
787
+ "eval_samples_per_second": 22.801,
788
+ "eval_steps_per_second": 2.85,
789
+ "step": 520
790
+ },
791
+ {
792
+ "epoch": 7.066666666666666,
793
+ "grad_norm": 3.9098429679870605,
794
+ "learning_rate": 1.7185185185185185e-05,
795
+ "loss": 1.6741,
796
+ "step": 530
797
+ },
798
+ {
799
+ "epoch": 7.066666666666666,
800
+ "eval_loss": 2.9202494621276855,
801
+ "eval_runtime": 43.8571,
802
+ "eval_samples_per_second": 22.801,
803
+ "eval_steps_per_second": 2.85,
804
+ "step": 530
805
+ },
806
+ {
807
+ "epoch": 7.2,
808
+ "grad_norm": 4.320191383361816,
809
+ "learning_rate": 1.6000000000000003e-05,
810
+ "loss": 1.5711,
811
+ "step": 540
812
+ },
813
+ {
814
+ "epoch": 7.2,
815
+ "eval_loss": 2.97855806350708,
816
+ "eval_runtime": 43.8599,
817
+ "eval_samples_per_second": 22.8,
818
+ "eval_steps_per_second": 2.85,
819
+ "step": 540
820
+ },
821
+ {
822
+ "epoch": 7.333333333333333,
823
+ "grad_norm": 4.003049850463867,
824
+ "learning_rate": 1.4814814814814815e-05,
825
+ "loss": 1.6106,
826
+ "step": 550
827
+ },
828
+ {
829
+ "epoch": 7.333333333333333,
830
+ "eval_loss": 2.9440739154815674,
831
+ "eval_runtime": 43.8605,
832
+ "eval_samples_per_second": 22.8,
833
+ "eval_steps_per_second": 2.85,
834
+ "step": 550
835
+ },
836
+ {
837
+ "epoch": 7.466666666666667,
838
+ "grad_norm": 4.265935897827148,
839
+ "learning_rate": 1.362962962962963e-05,
840
+ "loss": 1.6241,
841
+ "step": 560
842
+ },
843
+ {
844
+ "epoch": 7.466666666666667,
845
+ "eval_loss": 2.958505630493164,
846
+ "eval_runtime": 43.8614,
847
+ "eval_samples_per_second": 22.799,
848
+ "eval_steps_per_second": 2.85,
849
+ "step": 560
850
+ },
851
+ {
852
+ "epoch": 7.6,
853
+ "grad_norm": 5.025564670562744,
854
+ "learning_rate": 1.2444444444444446e-05,
855
+ "loss": 1.6306,
856
+ "step": 570
857
+ },
858
+ {
859
+ "epoch": 7.6,
860
+ "eval_loss": 2.956601619720459,
861
+ "eval_runtime": 43.8595,
862
+ "eval_samples_per_second": 22.8,
863
+ "eval_steps_per_second": 2.85,
864
+ "step": 570
865
+ },
866
+ {
867
+ "epoch": 7.733333333333333,
868
+ "grad_norm": 4.252591133117676,
869
+ "learning_rate": 1.125925925925926e-05,
870
+ "loss": 1.5933,
871
+ "step": 580
872
+ },
873
+ {
874
+ "epoch": 7.733333333333333,
875
+ "eval_loss": 2.9567930698394775,
876
+ "eval_runtime": 43.8568,
877
+ "eval_samples_per_second": 22.801,
878
+ "eval_steps_per_second": 2.85,
879
+ "step": 580
880
+ },
881
+ {
882
+ "epoch": 7.866666666666667,
883
+ "grad_norm": 4.484741687774658,
884
+ "learning_rate": 1.0192592592592594e-05,
885
+ "loss": 1.6441,
886
+ "step": 590
887
+ },
888
+ {
889
+ "epoch": 7.866666666666667,
890
+ "eval_loss": 2.9549593925476074,
891
+ "eval_runtime": 43.8579,
892
+ "eval_samples_per_second": 22.801,
893
+ "eval_steps_per_second": 2.85,
894
+ "step": 590
895
+ },
896
+ {
897
+ "epoch": 8.0,
898
+ "grad_norm": 4.397695064544678,
899
+ "learning_rate": 9.007407407407408e-06,
900
+ "loss": 1.5878,
901
+ "step": 600
902
+ },
903
+ {
904
+ "epoch": 8.0,
905
+ "eval_loss": 2.948493480682373,
906
+ "eval_runtime": 43.8666,
907
+ "eval_samples_per_second": 22.796,
908
+ "eval_steps_per_second": 2.85,
909
+ "step": 600
910
+ }
911
+ ],
912
+ "logging_steps": 10,
913
+ "max_steps": 675,
914
+ "num_input_tokens_seen": 0,
915
+ "num_train_epochs": 9,
916
+ "save_steps": 10,
917
+ "stateful_callbacks": {
918
+ "TrainerControl": {
919
+ "args": {
920
+ "should_epoch_stop": false,
921
+ "should_evaluate": false,
922
+ "should_log": false,
923
+ "should_save": true,
924
+ "should_training_stop": false
925
+ },
926
+ "attributes": {}
927
+ }
928
+ },
929
+ "total_flos": 9.8316431917056e+16,
930
+ "train_batch_size": 8,
931
+ "trial_name": null,
932
+ "trial_params": null
933
+ }
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-610/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/pythia-6_9b
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-610/adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/workspace/pythia-6_9b",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.1,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 8,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "dense_h_to_4h",
24
+ "query_key_value",
25
+ "dense",
26
+ "dense_4h_to_h"
27
+ ],
28
+ "task_type": "CAUSAL_LM",
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-610/trainer_state.json ADDED
@@ -0,0 +1,948 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 2.535032033920288,
3
+ "best_model_checkpoint": "./output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-150",
4
+ "epoch": 8.133333333333333,
5
+ "eval_steps": 10,
6
+ "global_step": 610,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.13333333333333333,
13
+ "grad_norm": 0.36938729882240295,
14
+ "learning_rate": 7.881481481481482e-05,
15
+ "loss": 2.519,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.13333333333333333,
20
+ "eval_loss": 2.579638957977295,
21
+ "eval_runtime": 43.8215,
22
+ "eval_samples_per_second": 22.82,
23
+ "eval_steps_per_second": 2.852,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.26666666666666666,
28
+ "grad_norm": 0.39850670099258423,
29
+ "learning_rate": 7.762962962962963e-05,
30
+ "loss": 2.5224,
31
+ "step": 20
32
+ },
33
+ {
34
+ "epoch": 0.26666666666666666,
35
+ "eval_loss": 2.5729691982269287,
36
+ "eval_runtime": 43.8179,
37
+ "eval_samples_per_second": 22.822,
38
+ "eval_steps_per_second": 2.853,
39
+ "step": 20
40
+ },
41
+ {
42
+ "epoch": 0.4,
43
+ "grad_norm": 0.40211933851242065,
44
+ "learning_rate": 7.644444444444445e-05,
45
+ "loss": 2.5169,
46
+ "step": 30
47
+ },
48
+ {
49
+ "epoch": 0.4,
50
+ "eval_loss": 2.567735433578491,
51
+ "eval_runtime": 43.8366,
52
+ "eval_samples_per_second": 22.812,
53
+ "eval_steps_per_second": 2.851,
54
+ "step": 30
55
+ },
56
+ {
57
+ "epoch": 0.5333333333333333,
58
+ "grad_norm": 0.6892333030700684,
59
+ "learning_rate": 7.525925925925926e-05,
60
+ "loss": 2.5784,
61
+ "step": 40
62
+ },
63
+ {
64
+ "epoch": 0.5333333333333333,
65
+ "eval_loss": 2.562650442123413,
66
+ "eval_runtime": 43.8377,
67
+ "eval_samples_per_second": 22.811,
68
+ "eval_steps_per_second": 2.851,
69
+ "step": 40
70
+ },
71
+ {
72
+ "epoch": 0.6666666666666666,
73
+ "grad_norm": 0.442343533039093,
74
+ "learning_rate": 7.407407407407409e-05,
75
+ "loss": 2.5431,
76
+ "step": 50
77
+ },
78
+ {
79
+ "epoch": 0.6666666666666666,
80
+ "eval_loss": 2.556513786315918,
81
+ "eval_runtime": 43.8656,
82
+ "eval_samples_per_second": 22.797,
83
+ "eval_steps_per_second": 2.85,
84
+ "step": 50
85
+ },
86
+ {
87
+ "epoch": 0.8,
88
+ "grad_norm": 0.4059845805168152,
89
+ "learning_rate": 7.28888888888889e-05,
90
+ "loss": 2.4936,
91
+ "step": 60
92
+ },
93
+ {
94
+ "epoch": 0.8,
95
+ "eval_loss": 2.552133798599243,
96
+ "eval_runtime": 43.8403,
97
+ "eval_samples_per_second": 22.81,
98
+ "eval_steps_per_second": 2.851,
99
+ "step": 60
100
+ },
101
+ {
102
+ "epoch": 0.9333333333333333,
103
+ "grad_norm": 0.48126307129859924,
104
+ "learning_rate": 7.170370370370371e-05,
105
+ "loss": 2.4901,
106
+ "step": 70
107
+ },
108
+ {
109
+ "epoch": 0.9333333333333333,
110
+ "eval_loss": 2.5477023124694824,
111
+ "eval_runtime": 43.8351,
112
+ "eval_samples_per_second": 22.813,
113
+ "eval_steps_per_second": 2.852,
114
+ "step": 70
115
+ },
116
+ {
117
+ "epoch": 1.0666666666666667,
118
+ "grad_norm": 0.48629865050315857,
119
+ "learning_rate": 7.051851851851853e-05,
120
+ "loss": 2.5114,
121
+ "step": 80
122
+ },
123
+ {
124
+ "epoch": 1.0666666666666667,
125
+ "eval_loss": 2.543431043624878,
126
+ "eval_runtime": 43.8432,
127
+ "eval_samples_per_second": 22.809,
128
+ "eval_steps_per_second": 2.851,
129
+ "step": 80
130
+ },
131
+ {
132
+ "epoch": 1.2,
133
+ "grad_norm": 0.5880796313285828,
134
+ "learning_rate": 6.933333333333334e-05,
135
+ "loss": 2.4446,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 1.2,
140
+ "eval_loss": 2.544339418411255,
141
+ "eval_runtime": 43.8437,
142
+ "eval_samples_per_second": 22.808,
143
+ "eval_steps_per_second": 2.851,
144
+ "step": 90
145
+ },
146
+ {
147
+ "epoch": 1.3333333333333333,
148
+ "grad_norm": 0.6746829748153687,
149
+ "learning_rate": 6.814814814814815e-05,
150
+ "loss": 2.4477,
151
+ "step": 100
152
+ },
153
+ {
154
+ "epoch": 1.3333333333333333,
155
+ "eval_loss": 2.544358968734741,
156
+ "eval_runtime": 43.8613,
157
+ "eval_samples_per_second": 22.799,
158
+ "eval_steps_per_second": 2.85,
159
+ "step": 100
160
+ },
161
+ {
162
+ "epoch": 1.4666666666666668,
163
+ "grad_norm": 0.8208937048912048,
164
+ "learning_rate": 6.696296296296296e-05,
165
+ "loss": 2.4004,
166
+ "step": 110
167
+ },
168
+ {
169
+ "epoch": 1.4666666666666668,
170
+ "eval_loss": 2.54068660736084,
171
+ "eval_runtime": 43.8426,
172
+ "eval_samples_per_second": 22.809,
173
+ "eval_steps_per_second": 2.851,
174
+ "step": 110
175
+ },
176
+ {
177
+ "epoch": 1.6,
178
+ "grad_norm": 0.925931453704834,
179
+ "learning_rate": 6.577777777777777e-05,
180
+ "loss": 2.3889,
181
+ "step": 120
182
+ },
183
+ {
184
+ "epoch": 1.6,
185
+ "eval_loss": 2.5393033027648926,
186
+ "eval_runtime": 43.8383,
187
+ "eval_samples_per_second": 22.811,
188
+ "eval_steps_per_second": 2.851,
189
+ "step": 120
190
+ },
191
+ {
192
+ "epoch": 1.7333333333333334,
193
+ "grad_norm": 0.8785662055015564,
194
+ "learning_rate": 6.45925925925926e-05,
195
+ "loss": 2.3959,
196
+ "step": 130
197
+ },
198
+ {
199
+ "epoch": 1.7333333333333334,
200
+ "eval_loss": 2.5367038249969482,
201
+ "eval_runtime": 43.8508,
202
+ "eval_samples_per_second": 22.805,
203
+ "eval_steps_per_second": 2.851,
204
+ "step": 130
205
+ },
206
+ {
207
+ "epoch": 1.8666666666666667,
208
+ "grad_norm": 0.941368818283081,
209
+ "learning_rate": 6.340740740740741e-05,
210
+ "loss": 2.3924,
211
+ "step": 140
212
+ },
213
+ {
214
+ "epoch": 1.8666666666666667,
215
+ "eval_loss": 2.535139560699463,
216
+ "eval_runtime": 43.8588,
217
+ "eval_samples_per_second": 22.8,
218
+ "eval_steps_per_second": 2.85,
219
+ "step": 140
220
+ },
221
+ {
222
+ "epoch": 2.0,
223
+ "grad_norm": 0.9578835368156433,
224
+ "learning_rate": 6.222222222222223e-05,
225
+ "loss": 2.4278,
226
+ "step": 150
227
+ },
228
+ {
229
+ "epoch": 2.0,
230
+ "eval_loss": 2.535032033920288,
231
+ "eval_runtime": 43.8484,
232
+ "eval_samples_per_second": 22.806,
233
+ "eval_steps_per_second": 2.851,
234
+ "step": 150
235
+ },
236
+ {
237
+ "epoch": 2.1333333333333333,
238
+ "grad_norm": 1.1541856527328491,
239
+ "learning_rate": 6.103703703703704e-05,
240
+ "loss": 2.2895,
241
+ "step": 160
242
+ },
243
+ {
244
+ "epoch": 2.1333333333333333,
245
+ "eval_loss": 2.564768075942993,
246
+ "eval_runtime": 43.8568,
247
+ "eval_samples_per_second": 22.801,
248
+ "eval_steps_per_second": 2.85,
249
+ "step": 160
250
+ },
251
+ {
252
+ "epoch": 2.2666666666666666,
253
+ "grad_norm": 1.4076604843139648,
254
+ "learning_rate": 5.9851851851851855e-05,
255
+ "loss": 2.2107,
256
+ "step": 170
257
+ },
258
+ {
259
+ "epoch": 2.2666666666666666,
260
+ "eval_loss": 2.5832314491271973,
261
+ "eval_runtime": 43.8455,
262
+ "eval_samples_per_second": 22.807,
263
+ "eval_steps_per_second": 2.851,
264
+ "step": 170
265
+ },
266
+ {
267
+ "epoch": 2.4,
268
+ "grad_norm": 1.4847813844680786,
269
+ "learning_rate": 5.8666666666666665e-05,
270
+ "loss": 2.2588,
271
+ "step": 180
272
+ },
273
+ {
274
+ "epoch": 2.4,
275
+ "eval_loss": 2.5781586170196533,
276
+ "eval_runtime": 43.8578,
277
+ "eval_samples_per_second": 22.801,
278
+ "eval_steps_per_second": 2.85,
279
+ "step": 180
280
+ },
281
+ {
282
+ "epoch": 2.533333333333333,
283
+ "grad_norm": 1.5135377645492554,
284
+ "learning_rate": 5.748148148148149e-05,
285
+ "loss": 2.2099,
286
+ "step": 190
287
+ },
288
+ {
289
+ "epoch": 2.533333333333333,
290
+ "eval_loss": 2.5752007961273193,
291
+ "eval_runtime": 43.8521,
292
+ "eval_samples_per_second": 22.804,
293
+ "eval_steps_per_second": 2.85,
294
+ "step": 190
295
+ },
296
+ {
297
+ "epoch": 2.6666666666666665,
298
+ "grad_norm": 1.5297592878341675,
299
+ "learning_rate": 5.62962962962963e-05,
300
+ "loss": 2.2965,
301
+ "step": 200
302
+ },
303
+ {
304
+ "epoch": 2.6666666666666665,
305
+ "eval_loss": 2.579918622970581,
306
+ "eval_runtime": 43.8661,
307
+ "eval_samples_per_second": 22.797,
308
+ "eval_steps_per_second": 2.85,
309
+ "step": 200
310
+ },
311
+ {
312
+ "epoch": 2.8,
313
+ "grad_norm": 1.6282892227172852,
314
+ "learning_rate": 5.511111111111112e-05,
315
+ "loss": 2.2487,
316
+ "step": 210
317
+ },
318
+ {
319
+ "epoch": 2.8,
320
+ "eval_loss": 2.5760037899017334,
321
+ "eval_runtime": 43.8379,
322
+ "eval_samples_per_second": 22.811,
323
+ "eval_steps_per_second": 2.851,
324
+ "step": 210
325
+ },
326
+ {
327
+ "epoch": 2.9333333333333336,
328
+ "grad_norm": 1.74424409866333,
329
+ "learning_rate": 5.392592592592593e-05,
330
+ "loss": 2.2049,
331
+ "step": 220
332
+ },
333
+ {
334
+ "epoch": 2.9333333333333336,
335
+ "eval_loss": 2.576190233230591,
336
+ "eval_runtime": 43.8491,
337
+ "eval_samples_per_second": 22.805,
338
+ "eval_steps_per_second": 2.851,
339
+ "step": 220
340
+ },
341
+ {
342
+ "epoch": 3.066666666666667,
343
+ "grad_norm": 1.654069423675537,
344
+ "learning_rate": 5.274074074074074e-05,
345
+ "loss": 2.1188,
346
+ "step": 230
347
+ },
348
+ {
349
+ "epoch": 3.066666666666667,
350
+ "eval_loss": 2.5971405506134033,
351
+ "eval_runtime": 43.855,
352
+ "eval_samples_per_second": 22.802,
353
+ "eval_steps_per_second": 2.85,
354
+ "step": 230
355
+ },
356
+ {
357
+ "epoch": 3.2,
358
+ "grad_norm": 2.541767120361328,
359
+ "learning_rate": 5.155555555555556e-05,
360
+ "loss": 2.0788,
361
+ "step": 240
362
+ },
363
+ {
364
+ "epoch": 3.2,
365
+ "eval_loss": 2.6767666339874268,
366
+ "eval_runtime": 43.8368,
367
+ "eval_samples_per_second": 22.812,
368
+ "eval_steps_per_second": 2.851,
369
+ "step": 240
370
+ },
371
+ {
372
+ "epoch": 3.3333333333333335,
373
+ "grad_norm": 2.0508077144622803,
374
+ "learning_rate": 5.037037037037037e-05,
375
+ "loss": 2.0784,
376
+ "step": 250
377
+ },
378
+ {
379
+ "epoch": 3.3333333333333335,
380
+ "eval_loss": 2.6486454010009766,
381
+ "eval_runtime": 43.8529,
382
+ "eval_samples_per_second": 22.803,
383
+ "eval_steps_per_second": 2.85,
384
+ "step": 250
385
+ },
386
+ {
387
+ "epoch": 3.466666666666667,
388
+ "grad_norm": 2.1096036434173584,
389
+ "learning_rate": 4.918518518518519e-05,
390
+ "loss": 2.0633,
391
+ "step": 260
392
+ },
393
+ {
394
+ "epoch": 3.466666666666667,
395
+ "eval_loss": 2.6501405239105225,
396
+ "eval_runtime": 43.8632,
397
+ "eval_samples_per_second": 22.798,
398
+ "eval_steps_per_second": 2.85,
399
+ "step": 260
400
+ },
401
+ {
402
+ "epoch": 3.6,
403
+ "grad_norm": 2.3028736114501953,
404
+ "learning_rate": 4.8e-05,
405
+ "loss": 2.0722,
406
+ "step": 270
407
+ },
408
+ {
409
+ "epoch": 3.6,
410
+ "eval_loss": 2.657053232192993,
411
+ "eval_runtime": 43.8423,
412
+ "eval_samples_per_second": 22.809,
413
+ "eval_steps_per_second": 2.851,
414
+ "step": 270
415
+ },
416
+ {
417
+ "epoch": 3.7333333333333334,
418
+ "grad_norm": 2.1536757946014404,
419
+ "learning_rate": 4.681481481481481e-05,
420
+ "loss": 2.0155,
421
+ "step": 280
422
+ },
423
+ {
424
+ "epoch": 3.7333333333333334,
425
+ "eval_loss": 2.648275375366211,
426
+ "eval_runtime": 43.8328,
427
+ "eval_samples_per_second": 22.814,
428
+ "eval_steps_per_second": 2.852,
429
+ "step": 280
430
+ },
431
+ {
432
+ "epoch": 3.8666666666666667,
433
+ "grad_norm": 2.4079270362854004,
434
+ "learning_rate": 4.5629629629629636e-05,
435
+ "loss": 2.1111,
436
+ "step": 290
437
+ },
438
+ {
439
+ "epoch": 3.8666666666666667,
440
+ "eval_loss": 2.650322675704956,
441
+ "eval_runtime": 43.835,
442
+ "eval_samples_per_second": 22.813,
443
+ "eval_steps_per_second": 2.852,
444
+ "step": 290
445
+ },
446
+ {
447
+ "epoch": 4.0,
448
+ "grad_norm": 2.426234722137451,
449
+ "learning_rate": 4.444444444444445e-05,
450
+ "loss": 2.041,
451
+ "step": 300
452
+ },
453
+ {
454
+ "epoch": 4.0,
455
+ "eval_loss": 2.6490862369537354,
456
+ "eval_runtime": 43.845,
457
+ "eval_samples_per_second": 22.808,
458
+ "eval_steps_per_second": 2.851,
459
+ "step": 300
460
+ },
461
+ {
462
+ "epoch": 4.133333333333334,
463
+ "grad_norm": 2.8063745498657227,
464
+ "learning_rate": 4.3259259259259264e-05,
465
+ "loss": 1.9316,
466
+ "step": 310
467
+ },
468
+ {
469
+ "epoch": 4.133333333333334,
470
+ "eval_loss": 2.7609620094299316,
471
+ "eval_runtime": 43.8481,
472
+ "eval_samples_per_second": 22.806,
473
+ "eval_steps_per_second": 2.851,
474
+ "step": 310
475
+ },
476
+ {
477
+ "epoch": 4.266666666666667,
478
+ "grad_norm": 2.96854305267334,
479
+ "learning_rate": 4.2074074074074075e-05,
480
+ "loss": 1.8889,
481
+ "step": 320
482
+ },
483
+ {
484
+ "epoch": 4.266666666666667,
485
+ "eval_loss": 2.736968994140625,
486
+ "eval_runtime": 43.8633,
487
+ "eval_samples_per_second": 22.798,
488
+ "eval_steps_per_second": 2.85,
489
+ "step": 320
490
+ },
491
+ {
492
+ "epoch": 4.4,
493
+ "grad_norm": 2.637695789337158,
494
+ "learning_rate": 4.088888888888889e-05,
495
+ "loss": 1.9187,
496
+ "step": 330
497
+ },
498
+ {
499
+ "epoch": 4.4,
500
+ "eval_loss": 2.7382876873016357,
501
+ "eval_runtime": 43.8486,
502
+ "eval_samples_per_second": 22.806,
503
+ "eval_steps_per_second": 2.851,
504
+ "step": 330
505
+ },
506
+ {
507
+ "epoch": 4.533333333333333,
508
+ "grad_norm": 2.9106290340423584,
509
+ "learning_rate": 3.970370370370371e-05,
510
+ "loss": 1.9002,
511
+ "step": 340
512
+ },
513
+ {
514
+ "epoch": 4.533333333333333,
515
+ "eval_loss": 2.734544515609741,
516
+ "eval_runtime": 43.8491,
517
+ "eval_samples_per_second": 22.805,
518
+ "eval_steps_per_second": 2.851,
519
+ "step": 340
520
+ },
521
+ {
522
+ "epoch": 4.666666666666667,
523
+ "grad_norm": 2.769315481185913,
524
+ "learning_rate": 3.851851851851852e-05,
525
+ "loss": 1.9251,
526
+ "step": 350
527
+ },
528
+ {
529
+ "epoch": 4.666666666666667,
530
+ "eval_loss": 2.734708070755005,
531
+ "eval_runtime": 43.8534,
532
+ "eval_samples_per_second": 22.803,
533
+ "eval_steps_per_second": 2.85,
534
+ "step": 350
535
+ },
536
+ {
537
+ "epoch": 4.8,
538
+ "grad_norm": 2.940281867980957,
539
+ "learning_rate": 3.733333333333334e-05,
540
+ "loss": 1.9319,
541
+ "step": 360
542
+ },
543
+ {
544
+ "epoch": 4.8,
545
+ "eval_loss": 2.7300503253936768,
546
+ "eval_runtime": 43.9017,
547
+ "eval_samples_per_second": 22.778,
548
+ "eval_steps_per_second": 2.847,
549
+ "step": 360
550
+ },
551
+ {
552
+ "epoch": 4.933333333333334,
553
+ "grad_norm": 2.8305609226226807,
554
+ "learning_rate": 3.614814814814815e-05,
555
+ "loss": 1.9332,
556
+ "step": 370
557
+ },
558
+ {
559
+ "epoch": 4.933333333333334,
560
+ "eval_loss": 2.7309281826019287,
561
+ "eval_runtime": 43.8842,
562
+ "eval_samples_per_second": 22.787,
563
+ "eval_steps_per_second": 2.848,
564
+ "step": 370
565
+ },
566
+ {
567
+ "epoch": 5.066666666666666,
568
+ "grad_norm": 2.8739213943481445,
569
+ "learning_rate": 3.4962962962962965e-05,
570
+ "loss": 1.8846,
571
+ "step": 380
572
+ },
573
+ {
574
+ "epoch": 5.066666666666666,
575
+ "eval_loss": 2.76513671875,
576
+ "eval_runtime": 43.906,
577
+ "eval_samples_per_second": 22.776,
578
+ "eval_steps_per_second": 2.847,
579
+ "step": 380
580
+ },
581
+ {
582
+ "epoch": 5.2,
583
+ "grad_norm": 3.9025838375091553,
584
+ "learning_rate": 3.377777777777778e-05,
585
+ "loss": 1.7575,
586
+ "step": 390
587
+ },
588
+ {
589
+ "epoch": 5.2,
590
+ "eval_loss": 2.847782611846924,
591
+ "eval_runtime": 43.8665,
592
+ "eval_samples_per_second": 22.796,
593
+ "eval_steps_per_second": 2.85,
594
+ "step": 390
595
+ },
596
+ {
597
+ "epoch": 5.333333333333333,
598
+ "grad_norm": 3.299649715423584,
599
+ "learning_rate": 3.259259259259259e-05,
600
+ "loss": 1.7713,
601
+ "step": 400
602
+ },
603
+ {
604
+ "epoch": 5.333333333333333,
605
+ "eval_loss": 2.8094286918640137,
606
+ "eval_runtime": 43.8629,
607
+ "eval_samples_per_second": 22.798,
608
+ "eval_steps_per_second": 2.85,
609
+ "step": 400
610
+ },
611
+ {
612
+ "epoch": 5.466666666666667,
613
+ "grad_norm": 3.4474265575408936,
614
+ "learning_rate": 3.140740740740741e-05,
615
+ "loss": 1.7983,
616
+ "step": 410
617
+ },
618
+ {
619
+ "epoch": 5.466666666666667,
620
+ "eval_loss": 2.827517509460449,
621
+ "eval_runtime": 43.8611,
622
+ "eval_samples_per_second": 22.799,
623
+ "eval_steps_per_second": 2.85,
624
+ "step": 410
625
+ },
626
+ {
627
+ "epoch": 5.6,
628
+ "grad_norm": 3.1924540996551514,
629
+ "learning_rate": 3.0222222222222225e-05,
630
+ "loss": 1.8091,
631
+ "step": 420
632
+ },
633
+ {
634
+ "epoch": 5.6,
635
+ "eval_loss": 2.81618332862854,
636
+ "eval_runtime": 43.8544,
637
+ "eval_samples_per_second": 22.803,
638
+ "eval_steps_per_second": 2.85,
639
+ "step": 420
640
+ },
641
+ {
642
+ "epoch": 5.733333333333333,
643
+ "grad_norm": 3.5224015712738037,
644
+ "learning_rate": 2.9037037037037042e-05,
645
+ "loss": 1.8253,
646
+ "step": 430
647
+ },
648
+ {
649
+ "epoch": 5.733333333333333,
650
+ "eval_loss": 2.816711187362671,
651
+ "eval_runtime": 43.8685,
652
+ "eval_samples_per_second": 22.795,
653
+ "eval_steps_per_second": 2.849,
654
+ "step": 430
655
+ },
656
+ {
657
+ "epoch": 5.866666666666667,
658
+ "grad_norm": 3.60918927192688,
659
+ "learning_rate": 2.7851851851851856e-05,
660
+ "loss": 1.8013,
661
+ "step": 440
662
+ },
663
+ {
664
+ "epoch": 5.866666666666667,
665
+ "eval_loss": 2.8146169185638428,
666
+ "eval_runtime": 43.8516,
667
+ "eval_samples_per_second": 22.804,
668
+ "eval_steps_per_second": 2.851,
669
+ "step": 440
670
+ },
671
+ {
672
+ "epoch": 6.0,
673
+ "grad_norm": 3.5798070430755615,
674
+ "learning_rate": 2.6666666666666667e-05,
675
+ "loss": 1.8258,
676
+ "step": 450
677
+ },
678
+ {
679
+ "epoch": 6.0,
680
+ "eval_loss": 2.8134233951568604,
681
+ "eval_runtime": 43.8442,
682
+ "eval_samples_per_second": 22.808,
683
+ "eval_steps_per_second": 2.851,
684
+ "step": 450
685
+ },
686
+ {
687
+ "epoch": 6.133333333333334,
688
+ "grad_norm": 5.563477993011475,
689
+ "learning_rate": 2.5481481481481484e-05,
690
+ "loss": 1.6649,
691
+ "step": 460
692
+ },
693
+ {
694
+ "epoch": 6.133333333333334,
695
+ "eval_loss": 2.9189789295196533,
696
+ "eval_runtime": 43.8602,
697
+ "eval_samples_per_second": 22.8,
698
+ "eval_steps_per_second": 2.85,
699
+ "step": 460
700
+ },
701
+ {
702
+ "epoch": 6.266666666666667,
703
+ "grad_norm": 4.192393779754639,
704
+ "learning_rate": 2.4296296296296298e-05,
705
+ "loss": 1.7443,
706
+ "step": 470
707
+ },
708
+ {
709
+ "epoch": 6.266666666666667,
710
+ "eval_loss": 2.893780469894409,
711
+ "eval_runtime": 43.8434,
712
+ "eval_samples_per_second": 22.808,
713
+ "eval_steps_per_second": 2.851,
714
+ "step": 470
715
+ },
716
+ {
717
+ "epoch": 6.4,
718
+ "grad_norm": 4.8650593757629395,
719
+ "learning_rate": 2.3111111111111112e-05,
720
+ "loss": 1.6961,
721
+ "step": 480
722
+ },
723
+ {
724
+ "epoch": 6.4,
725
+ "eval_loss": 2.8861398696899414,
726
+ "eval_runtime": 43.8417,
727
+ "eval_samples_per_second": 22.809,
728
+ "eval_steps_per_second": 2.851,
729
+ "step": 480
730
+ },
731
+ {
732
+ "epoch": 6.533333333333333,
733
+ "grad_norm": 3.844482660293579,
734
+ "learning_rate": 2.192592592592593e-05,
735
+ "loss": 1.6868,
736
+ "step": 490
737
+ },
738
+ {
739
+ "epoch": 6.533333333333333,
740
+ "eval_loss": 2.900317907333374,
741
+ "eval_runtime": 43.8557,
742
+ "eval_samples_per_second": 22.802,
743
+ "eval_steps_per_second": 2.85,
744
+ "step": 490
745
+ },
746
+ {
747
+ "epoch": 6.666666666666667,
748
+ "grad_norm": 4.230032920837402,
749
+ "learning_rate": 2.074074074074074e-05,
750
+ "loss": 1.6593,
751
+ "step": 500
752
+ },
753
+ {
754
+ "epoch": 6.666666666666667,
755
+ "eval_loss": 2.892076253890991,
756
+ "eval_runtime": 43.8479,
757
+ "eval_samples_per_second": 22.806,
758
+ "eval_steps_per_second": 2.851,
759
+ "step": 500
760
+ },
761
+ {
762
+ "epoch": 6.8,
763
+ "grad_norm": 4.427380561828613,
764
+ "learning_rate": 1.9555555555555557e-05,
765
+ "loss": 1.6777,
766
+ "step": 510
767
+ },
768
+ {
769
+ "epoch": 6.8,
770
+ "eval_loss": 2.8877696990966797,
771
+ "eval_runtime": 43.8489,
772
+ "eval_samples_per_second": 22.806,
773
+ "eval_steps_per_second": 2.851,
774
+ "step": 510
775
+ },
776
+ {
777
+ "epoch": 6.933333333333334,
778
+ "grad_norm": 4.23176908493042,
779
+ "learning_rate": 1.837037037037037e-05,
780
+ "loss": 1.7331,
781
+ "step": 520
782
+ },
783
+ {
784
+ "epoch": 6.933333333333334,
785
+ "eval_loss": 2.889272928237915,
786
+ "eval_runtime": 43.8577,
787
+ "eval_samples_per_second": 22.801,
788
+ "eval_steps_per_second": 2.85,
789
+ "step": 520
790
+ },
791
+ {
792
+ "epoch": 7.066666666666666,
793
+ "grad_norm": 3.9098429679870605,
794
+ "learning_rate": 1.7185185185185185e-05,
795
+ "loss": 1.6741,
796
+ "step": 530
797
+ },
798
+ {
799
+ "epoch": 7.066666666666666,
800
+ "eval_loss": 2.9202494621276855,
801
+ "eval_runtime": 43.8571,
802
+ "eval_samples_per_second": 22.801,
803
+ "eval_steps_per_second": 2.85,
804
+ "step": 530
805
+ },
806
+ {
807
+ "epoch": 7.2,
808
+ "grad_norm": 4.320191383361816,
809
+ "learning_rate": 1.6000000000000003e-05,
810
+ "loss": 1.5711,
811
+ "step": 540
812
+ },
813
+ {
814
+ "epoch": 7.2,
815
+ "eval_loss": 2.97855806350708,
816
+ "eval_runtime": 43.8599,
817
+ "eval_samples_per_second": 22.8,
818
+ "eval_steps_per_second": 2.85,
819
+ "step": 540
820
+ },
821
+ {
822
+ "epoch": 7.333333333333333,
823
+ "grad_norm": 4.003049850463867,
824
+ "learning_rate": 1.4814814814814815e-05,
825
+ "loss": 1.6106,
826
+ "step": 550
827
+ },
828
+ {
829
+ "epoch": 7.333333333333333,
830
+ "eval_loss": 2.9440739154815674,
831
+ "eval_runtime": 43.8605,
832
+ "eval_samples_per_second": 22.8,
833
+ "eval_steps_per_second": 2.85,
834
+ "step": 550
835
+ },
836
+ {
837
+ "epoch": 7.466666666666667,
838
+ "grad_norm": 4.265935897827148,
839
+ "learning_rate": 1.362962962962963e-05,
840
+ "loss": 1.6241,
841
+ "step": 560
842
+ },
843
+ {
844
+ "epoch": 7.466666666666667,
845
+ "eval_loss": 2.958505630493164,
846
+ "eval_runtime": 43.8614,
847
+ "eval_samples_per_second": 22.799,
848
+ "eval_steps_per_second": 2.85,
849
+ "step": 560
850
+ },
851
+ {
852
+ "epoch": 7.6,
853
+ "grad_norm": 5.025564670562744,
854
+ "learning_rate": 1.2444444444444446e-05,
855
+ "loss": 1.6306,
856
+ "step": 570
857
+ },
858
+ {
859
+ "epoch": 7.6,
860
+ "eval_loss": 2.956601619720459,
861
+ "eval_runtime": 43.8595,
862
+ "eval_samples_per_second": 22.8,
863
+ "eval_steps_per_second": 2.85,
864
+ "step": 570
865
+ },
866
+ {
867
+ "epoch": 7.733333333333333,
868
+ "grad_norm": 4.252591133117676,
869
+ "learning_rate": 1.125925925925926e-05,
870
+ "loss": 1.5933,
871
+ "step": 580
872
+ },
873
+ {
874
+ "epoch": 7.733333333333333,
875
+ "eval_loss": 2.9567930698394775,
876
+ "eval_runtime": 43.8568,
877
+ "eval_samples_per_second": 22.801,
878
+ "eval_steps_per_second": 2.85,
879
+ "step": 580
880
+ },
881
+ {
882
+ "epoch": 7.866666666666667,
883
+ "grad_norm": 4.484741687774658,
884
+ "learning_rate": 1.0192592592592594e-05,
885
+ "loss": 1.6441,
886
+ "step": 590
887
+ },
888
+ {
889
+ "epoch": 7.866666666666667,
890
+ "eval_loss": 2.9549593925476074,
891
+ "eval_runtime": 43.8579,
892
+ "eval_samples_per_second": 22.801,
893
+ "eval_steps_per_second": 2.85,
894
+ "step": 590
895
+ },
896
+ {
897
+ "epoch": 8.0,
898
+ "grad_norm": 4.397695064544678,
899
+ "learning_rate": 9.007407407407408e-06,
900
+ "loss": 1.5878,
901
+ "step": 600
902
+ },
903
+ {
904
+ "epoch": 8.0,
905
+ "eval_loss": 2.948493480682373,
906
+ "eval_runtime": 43.8666,
907
+ "eval_samples_per_second": 22.796,
908
+ "eval_steps_per_second": 2.85,
909
+ "step": 600
910
+ },
911
+ {
912
+ "epoch": 8.133333333333333,
913
+ "grad_norm": 5.092386245727539,
914
+ "learning_rate": 7.822222222222224e-06,
915
+ "loss": 1.5588,
916
+ "step": 610
917
+ },
918
+ {
919
+ "epoch": 8.133333333333333,
920
+ "eval_loss": 2.9865269660949707,
921
+ "eval_runtime": 43.8606,
922
+ "eval_samples_per_second": 22.8,
923
+ "eval_steps_per_second": 2.85,
924
+ "step": 610
925
+ }
926
+ ],
927
+ "logging_steps": 10,
928
+ "max_steps": 675,
929
+ "num_input_tokens_seen": 0,
930
+ "num_train_epochs": 9,
931
+ "save_steps": 10,
932
+ "stateful_callbacks": {
933
+ "TrainerControl": {
934
+ "args": {
935
+ "should_epoch_stop": false,
936
+ "should_evaluate": false,
937
+ "should_log": false,
938
+ "should_save": true,
939
+ "should_training_stop": false
940
+ },
941
+ "attributes": {}
942
+ }
943
+ },
944
+ "total_flos": 9.99550391156736e+16,
945
+ "train_batch_size": 8,
946
+ "trial_name": null,
947
+ "trial_params": null
948
+ }
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-620/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/pythia-6_9b
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-620/adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/workspace/pythia-6_9b",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.1,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 8,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "dense_h_to_4h",
24
+ "query_key_value",
25
+ "dense",
26
+ "dense_4h_to_h"
27
+ ],
28
+ "task_type": "CAUSAL_LM",
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-620/trainer_state.json ADDED
@@ -0,0 +1,963 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 2.535032033920288,
3
+ "best_model_checkpoint": "./output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-150",
4
+ "epoch": 8.266666666666667,
5
+ "eval_steps": 10,
6
+ "global_step": 620,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.13333333333333333,
13
+ "grad_norm": 0.36938729882240295,
14
+ "learning_rate": 7.881481481481482e-05,
15
+ "loss": 2.519,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.13333333333333333,
20
+ "eval_loss": 2.579638957977295,
21
+ "eval_runtime": 43.8215,
22
+ "eval_samples_per_second": 22.82,
23
+ "eval_steps_per_second": 2.852,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.26666666666666666,
28
+ "grad_norm": 0.39850670099258423,
29
+ "learning_rate": 7.762962962962963e-05,
30
+ "loss": 2.5224,
31
+ "step": 20
32
+ },
33
+ {
34
+ "epoch": 0.26666666666666666,
35
+ "eval_loss": 2.5729691982269287,
36
+ "eval_runtime": 43.8179,
37
+ "eval_samples_per_second": 22.822,
38
+ "eval_steps_per_second": 2.853,
39
+ "step": 20
40
+ },
41
+ {
42
+ "epoch": 0.4,
43
+ "grad_norm": 0.40211933851242065,
44
+ "learning_rate": 7.644444444444445e-05,
45
+ "loss": 2.5169,
46
+ "step": 30
47
+ },
48
+ {
49
+ "epoch": 0.4,
50
+ "eval_loss": 2.567735433578491,
51
+ "eval_runtime": 43.8366,
52
+ "eval_samples_per_second": 22.812,
53
+ "eval_steps_per_second": 2.851,
54
+ "step": 30
55
+ },
56
+ {
57
+ "epoch": 0.5333333333333333,
58
+ "grad_norm": 0.6892333030700684,
59
+ "learning_rate": 7.525925925925926e-05,
60
+ "loss": 2.5784,
61
+ "step": 40
62
+ },
63
+ {
64
+ "epoch": 0.5333333333333333,
65
+ "eval_loss": 2.562650442123413,
66
+ "eval_runtime": 43.8377,
67
+ "eval_samples_per_second": 22.811,
68
+ "eval_steps_per_second": 2.851,
69
+ "step": 40
70
+ },
71
+ {
72
+ "epoch": 0.6666666666666666,
73
+ "grad_norm": 0.442343533039093,
74
+ "learning_rate": 7.407407407407409e-05,
75
+ "loss": 2.5431,
76
+ "step": 50
77
+ },
78
+ {
79
+ "epoch": 0.6666666666666666,
80
+ "eval_loss": 2.556513786315918,
81
+ "eval_runtime": 43.8656,
82
+ "eval_samples_per_second": 22.797,
83
+ "eval_steps_per_second": 2.85,
84
+ "step": 50
85
+ },
86
+ {
87
+ "epoch": 0.8,
88
+ "grad_norm": 0.4059845805168152,
89
+ "learning_rate": 7.28888888888889e-05,
90
+ "loss": 2.4936,
91
+ "step": 60
92
+ },
93
+ {
94
+ "epoch": 0.8,
95
+ "eval_loss": 2.552133798599243,
96
+ "eval_runtime": 43.8403,
97
+ "eval_samples_per_second": 22.81,
98
+ "eval_steps_per_second": 2.851,
99
+ "step": 60
100
+ },
101
+ {
102
+ "epoch": 0.9333333333333333,
103
+ "grad_norm": 0.48126307129859924,
104
+ "learning_rate": 7.170370370370371e-05,
105
+ "loss": 2.4901,
106
+ "step": 70
107
+ },
108
+ {
109
+ "epoch": 0.9333333333333333,
110
+ "eval_loss": 2.5477023124694824,
111
+ "eval_runtime": 43.8351,
112
+ "eval_samples_per_second": 22.813,
113
+ "eval_steps_per_second": 2.852,
114
+ "step": 70
115
+ },
116
+ {
117
+ "epoch": 1.0666666666666667,
118
+ "grad_norm": 0.48629865050315857,
119
+ "learning_rate": 7.051851851851853e-05,
120
+ "loss": 2.5114,
121
+ "step": 80
122
+ },
123
+ {
124
+ "epoch": 1.0666666666666667,
125
+ "eval_loss": 2.543431043624878,
126
+ "eval_runtime": 43.8432,
127
+ "eval_samples_per_second": 22.809,
128
+ "eval_steps_per_second": 2.851,
129
+ "step": 80
130
+ },
131
+ {
132
+ "epoch": 1.2,
133
+ "grad_norm": 0.5880796313285828,
134
+ "learning_rate": 6.933333333333334e-05,
135
+ "loss": 2.4446,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 1.2,
140
+ "eval_loss": 2.544339418411255,
141
+ "eval_runtime": 43.8437,
142
+ "eval_samples_per_second": 22.808,
143
+ "eval_steps_per_second": 2.851,
144
+ "step": 90
145
+ },
146
+ {
147
+ "epoch": 1.3333333333333333,
148
+ "grad_norm": 0.6746829748153687,
149
+ "learning_rate": 6.814814814814815e-05,
150
+ "loss": 2.4477,
151
+ "step": 100
152
+ },
153
+ {
154
+ "epoch": 1.3333333333333333,
155
+ "eval_loss": 2.544358968734741,
156
+ "eval_runtime": 43.8613,
157
+ "eval_samples_per_second": 22.799,
158
+ "eval_steps_per_second": 2.85,
159
+ "step": 100
160
+ },
161
+ {
162
+ "epoch": 1.4666666666666668,
163
+ "grad_norm": 0.8208937048912048,
164
+ "learning_rate": 6.696296296296296e-05,
165
+ "loss": 2.4004,
166
+ "step": 110
167
+ },
168
+ {
169
+ "epoch": 1.4666666666666668,
170
+ "eval_loss": 2.54068660736084,
171
+ "eval_runtime": 43.8426,
172
+ "eval_samples_per_second": 22.809,
173
+ "eval_steps_per_second": 2.851,
174
+ "step": 110
175
+ },
176
+ {
177
+ "epoch": 1.6,
178
+ "grad_norm": 0.925931453704834,
179
+ "learning_rate": 6.577777777777777e-05,
180
+ "loss": 2.3889,
181
+ "step": 120
182
+ },
183
+ {
184
+ "epoch": 1.6,
185
+ "eval_loss": 2.5393033027648926,
186
+ "eval_runtime": 43.8383,
187
+ "eval_samples_per_second": 22.811,
188
+ "eval_steps_per_second": 2.851,
189
+ "step": 120
190
+ },
191
+ {
192
+ "epoch": 1.7333333333333334,
193
+ "grad_norm": 0.8785662055015564,
194
+ "learning_rate": 6.45925925925926e-05,
195
+ "loss": 2.3959,
196
+ "step": 130
197
+ },
198
+ {
199
+ "epoch": 1.7333333333333334,
200
+ "eval_loss": 2.5367038249969482,
201
+ "eval_runtime": 43.8508,
202
+ "eval_samples_per_second": 22.805,
203
+ "eval_steps_per_second": 2.851,
204
+ "step": 130
205
+ },
206
+ {
207
+ "epoch": 1.8666666666666667,
208
+ "grad_norm": 0.941368818283081,
209
+ "learning_rate": 6.340740740740741e-05,
210
+ "loss": 2.3924,
211
+ "step": 140
212
+ },
213
+ {
214
+ "epoch": 1.8666666666666667,
215
+ "eval_loss": 2.535139560699463,
216
+ "eval_runtime": 43.8588,
217
+ "eval_samples_per_second": 22.8,
218
+ "eval_steps_per_second": 2.85,
219
+ "step": 140
220
+ },
221
+ {
222
+ "epoch": 2.0,
223
+ "grad_norm": 0.9578835368156433,
224
+ "learning_rate": 6.222222222222223e-05,
225
+ "loss": 2.4278,
226
+ "step": 150
227
+ },
228
+ {
229
+ "epoch": 2.0,
230
+ "eval_loss": 2.535032033920288,
231
+ "eval_runtime": 43.8484,
232
+ "eval_samples_per_second": 22.806,
233
+ "eval_steps_per_second": 2.851,
234
+ "step": 150
235
+ },
236
+ {
237
+ "epoch": 2.1333333333333333,
238
+ "grad_norm": 1.1541856527328491,
239
+ "learning_rate": 6.103703703703704e-05,
240
+ "loss": 2.2895,
241
+ "step": 160
242
+ },
243
+ {
244
+ "epoch": 2.1333333333333333,
245
+ "eval_loss": 2.564768075942993,
246
+ "eval_runtime": 43.8568,
247
+ "eval_samples_per_second": 22.801,
248
+ "eval_steps_per_second": 2.85,
249
+ "step": 160
250
+ },
251
+ {
252
+ "epoch": 2.2666666666666666,
253
+ "grad_norm": 1.4076604843139648,
254
+ "learning_rate": 5.9851851851851855e-05,
255
+ "loss": 2.2107,
256
+ "step": 170
257
+ },
258
+ {
259
+ "epoch": 2.2666666666666666,
260
+ "eval_loss": 2.5832314491271973,
261
+ "eval_runtime": 43.8455,
262
+ "eval_samples_per_second": 22.807,
263
+ "eval_steps_per_second": 2.851,
264
+ "step": 170
265
+ },
266
+ {
267
+ "epoch": 2.4,
268
+ "grad_norm": 1.4847813844680786,
269
+ "learning_rate": 5.8666666666666665e-05,
270
+ "loss": 2.2588,
271
+ "step": 180
272
+ },
273
+ {
274
+ "epoch": 2.4,
275
+ "eval_loss": 2.5781586170196533,
276
+ "eval_runtime": 43.8578,
277
+ "eval_samples_per_second": 22.801,
278
+ "eval_steps_per_second": 2.85,
279
+ "step": 180
280
+ },
281
+ {
282
+ "epoch": 2.533333333333333,
283
+ "grad_norm": 1.5135377645492554,
284
+ "learning_rate": 5.748148148148149e-05,
285
+ "loss": 2.2099,
286
+ "step": 190
287
+ },
288
+ {
289
+ "epoch": 2.533333333333333,
290
+ "eval_loss": 2.5752007961273193,
291
+ "eval_runtime": 43.8521,
292
+ "eval_samples_per_second": 22.804,
293
+ "eval_steps_per_second": 2.85,
294
+ "step": 190
295
+ },
296
+ {
297
+ "epoch": 2.6666666666666665,
298
+ "grad_norm": 1.5297592878341675,
299
+ "learning_rate": 5.62962962962963e-05,
300
+ "loss": 2.2965,
301
+ "step": 200
302
+ },
303
+ {
304
+ "epoch": 2.6666666666666665,
305
+ "eval_loss": 2.579918622970581,
306
+ "eval_runtime": 43.8661,
307
+ "eval_samples_per_second": 22.797,
308
+ "eval_steps_per_second": 2.85,
309
+ "step": 200
310
+ },
311
+ {
312
+ "epoch": 2.8,
313
+ "grad_norm": 1.6282892227172852,
314
+ "learning_rate": 5.511111111111112e-05,
315
+ "loss": 2.2487,
316
+ "step": 210
317
+ },
318
+ {
319
+ "epoch": 2.8,
320
+ "eval_loss": 2.5760037899017334,
321
+ "eval_runtime": 43.8379,
322
+ "eval_samples_per_second": 22.811,
323
+ "eval_steps_per_second": 2.851,
324
+ "step": 210
325
+ },
326
+ {
327
+ "epoch": 2.9333333333333336,
328
+ "grad_norm": 1.74424409866333,
329
+ "learning_rate": 5.392592592592593e-05,
330
+ "loss": 2.2049,
331
+ "step": 220
332
+ },
333
+ {
334
+ "epoch": 2.9333333333333336,
335
+ "eval_loss": 2.576190233230591,
336
+ "eval_runtime": 43.8491,
337
+ "eval_samples_per_second": 22.805,
338
+ "eval_steps_per_second": 2.851,
339
+ "step": 220
340
+ },
341
+ {
342
+ "epoch": 3.066666666666667,
343
+ "grad_norm": 1.654069423675537,
344
+ "learning_rate": 5.274074074074074e-05,
345
+ "loss": 2.1188,
346
+ "step": 230
347
+ },
348
+ {
349
+ "epoch": 3.066666666666667,
350
+ "eval_loss": 2.5971405506134033,
351
+ "eval_runtime": 43.855,
352
+ "eval_samples_per_second": 22.802,
353
+ "eval_steps_per_second": 2.85,
354
+ "step": 230
355
+ },
356
+ {
357
+ "epoch": 3.2,
358
+ "grad_norm": 2.541767120361328,
359
+ "learning_rate": 5.155555555555556e-05,
360
+ "loss": 2.0788,
361
+ "step": 240
362
+ },
363
+ {
364
+ "epoch": 3.2,
365
+ "eval_loss": 2.6767666339874268,
366
+ "eval_runtime": 43.8368,
367
+ "eval_samples_per_second": 22.812,
368
+ "eval_steps_per_second": 2.851,
369
+ "step": 240
370
+ },
371
+ {
372
+ "epoch": 3.3333333333333335,
373
+ "grad_norm": 2.0508077144622803,
374
+ "learning_rate": 5.037037037037037e-05,
375
+ "loss": 2.0784,
376
+ "step": 250
377
+ },
378
+ {
379
+ "epoch": 3.3333333333333335,
380
+ "eval_loss": 2.6486454010009766,
381
+ "eval_runtime": 43.8529,
382
+ "eval_samples_per_second": 22.803,
383
+ "eval_steps_per_second": 2.85,
384
+ "step": 250
385
+ },
386
+ {
387
+ "epoch": 3.466666666666667,
388
+ "grad_norm": 2.1096036434173584,
389
+ "learning_rate": 4.918518518518519e-05,
390
+ "loss": 2.0633,
391
+ "step": 260
392
+ },
393
+ {
394
+ "epoch": 3.466666666666667,
395
+ "eval_loss": 2.6501405239105225,
396
+ "eval_runtime": 43.8632,
397
+ "eval_samples_per_second": 22.798,
398
+ "eval_steps_per_second": 2.85,
399
+ "step": 260
400
+ },
401
+ {
402
+ "epoch": 3.6,
403
+ "grad_norm": 2.3028736114501953,
404
+ "learning_rate": 4.8e-05,
405
+ "loss": 2.0722,
406
+ "step": 270
407
+ },
408
+ {
409
+ "epoch": 3.6,
410
+ "eval_loss": 2.657053232192993,
411
+ "eval_runtime": 43.8423,
412
+ "eval_samples_per_second": 22.809,
413
+ "eval_steps_per_second": 2.851,
414
+ "step": 270
415
+ },
416
+ {
417
+ "epoch": 3.7333333333333334,
418
+ "grad_norm": 2.1536757946014404,
419
+ "learning_rate": 4.681481481481481e-05,
420
+ "loss": 2.0155,
421
+ "step": 280
422
+ },
423
+ {
424
+ "epoch": 3.7333333333333334,
425
+ "eval_loss": 2.648275375366211,
426
+ "eval_runtime": 43.8328,
427
+ "eval_samples_per_second": 22.814,
428
+ "eval_steps_per_second": 2.852,
429
+ "step": 280
430
+ },
431
+ {
432
+ "epoch": 3.8666666666666667,
433
+ "grad_norm": 2.4079270362854004,
434
+ "learning_rate": 4.5629629629629636e-05,
435
+ "loss": 2.1111,
436
+ "step": 290
437
+ },
438
+ {
439
+ "epoch": 3.8666666666666667,
440
+ "eval_loss": 2.650322675704956,
441
+ "eval_runtime": 43.835,
442
+ "eval_samples_per_second": 22.813,
443
+ "eval_steps_per_second": 2.852,
444
+ "step": 290
445
+ },
446
+ {
447
+ "epoch": 4.0,
448
+ "grad_norm": 2.426234722137451,
449
+ "learning_rate": 4.444444444444445e-05,
450
+ "loss": 2.041,
451
+ "step": 300
452
+ },
453
+ {
454
+ "epoch": 4.0,
455
+ "eval_loss": 2.6490862369537354,
456
+ "eval_runtime": 43.845,
457
+ "eval_samples_per_second": 22.808,
458
+ "eval_steps_per_second": 2.851,
459
+ "step": 300
460
+ },
461
+ {
462
+ "epoch": 4.133333333333334,
463
+ "grad_norm": 2.8063745498657227,
464
+ "learning_rate": 4.3259259259259264e-05,
465
+ "loss": 1.9316,
466
+ "step": 310
467
+ },
468
+ {
469
+ "epoch": 4.133333333333334,
470
+ "eval_loss": 2.7609620094299316,
471
+ "eval_runtime": 43.8481,
472
+ "eval_samples_per_second": 22.806,
473
+ "eval_steps_per_second": 2.851,
474
+ "step": 310
475
+ },
476
+ {
477
+ "epoch": 4.266666666666667,
478
+ "grad_norm": 2.96854305267334,
479
+ "learning_rate": 4.2074074074074075e-05,
480
+ "loss": 1.8889,
481
+ "step": 320
482
+ },
483
+ {
484
+ "epoch": 4.266666666666667,
485
+ "eval_loss": 2.736968994140625,
486
+ "eval_runtime": 43.8633,
487
+ "eval_samples_per_second": 22.798,
488
+ "eval_steps_per_second": 2.85,
489
+ "step": 320
490
+ },
491
+ {
492
+ "epoch": 4.4,
493
+ "grad_norm": 2.637695789337158,
494
+ "learning_rate": 4.088888888888889e-05,
495
+ "loss": 1.9187,
496
+ "step": 330
497
+ },
498
+ {
499
+ "epoch": 4.4,
500
+ "eval_loss": 2.7382876873016357,
501
+ "eval_runtime": 43.8486,
502
+ "eval_samples_per_second": 22.806,
503
+ "eval_steps_per_second": 2.851,
504
+ "step": 330
505
+ },
506
+ {
507
+ "epoch": 4.533333333333333,
508
+ "grad_norm": 2.9106290340423584,
509
+ "learning_rate": 3.970370370370371e-05,
510
+ "loss": 1.9002,
511
+ "step": 340
512
+ },
513
+ {
514
+ "epoch": 4.533333333333333,
515
+ "eval_loss": 2.734544515609741,
516
+ "eval_runtime": 43.8491,
517
+ "eval_samples_per_second": 22.805,
518
+ "eval_steps_per_second": 2.851,
519
+ "step": 340
520
+ },
521
+ {
522
+ "epoch": 4.666666666666667,
523
+ "grad_norm": 2.769315481185913,
524
+ "learning_rate": 3.851851851851852e-05,
525
+ "loss": 1.9251,
526
+ "step": 350
527
+ },
528
+ {
529
+ "epoch": 4.666666666666667,
530
+ "eval_loss": 2.734708070755005,
531
+ "eval_runtime": 43.8534,
532
+ "eval_samples_per_second": 22.803,
533
+ "eval_steps_per_second": 2.85,
534
+ "step": 350
535
+ },
536
+ {
537
+ "epoch": 4.8,
538
+ "grad_norm": 2.940281867980957,
539
+ "learning_rate": 3.733333333333334e-05,
540
+ "loss": 1.9319,
541
+ "step": 360
542
+ },
543
+ {
544
+ "epoch": 4.8,
545
+ "eval_loss": 2.7300503253936768,
546
+ "eval_runtime": 43.9017,
547
+ "eval_samples_per_second": 22.778,
548
+ "eval_steps_per_second": 2.847,
549
+ "step": 360
550
+ },
551
+ {
552
+ "epoch": 4.933333333333334,
553
+ "grad_norm": 2.8305609226226807,
554
+ "learning_rate": 3.614814814814815e-05,
555
+ "loss": 1.9332,
556
+ "step": 370
557
+ },
558
+ {
559
+ "epoch": 4.933333333333334,
560
+ "eval_loss": 2.7309281826019287,
561
+ "eval_runtime": 43.8842,
562
+ "eval_samples_per_second": 22.787,
563
+ "eval_steps_per_second": 2.848,
564
+ "step": 370
565
+ },
566
+ {
567
+ "epoch": 5.066666666666666,
568
+ "grad_norm": 2.8739213943481445,
569
+ "learning_rate": 3.4962962962962965e-05,
570
+ "loss": 1.8846,
571
+ "step": 380
572
+ },
573
+ {
574
+ "epoch": 5.066666666666666,
575
+ "eval_loss": 2.76513671875,
576
+ "eval_runtime": 43.906,
577
+ "eval_samples_per_second": 22.776,
578
+ "eval_steps_per_second": 2.847,
579
+ "step": 380
580
+ },
581
+ {
582
+ "epoch": 5.2,
583
+ "grad_norm": 3.9025838375091553,
584
+ "learning_rate": 3.377777777777778e-05,
585
+ "loss": 1.7575,
586
+ "step": 390
587
+ },
588
+ {
589
+ "epoch": 5.2,
590
+ "eval_loss": 2.847782611846924,
591
+ "eval_runtime": 43.8665,
592
+ "eval_samples_per_second": 22.796,
593
+ "eval_steps_per_second": 2.85,
594
+ "step": 390
595
+ },
596
+ {
597
+ "epoch": 5.333333333333333,
598
+ "grad_norm": 3.299649715423584,
599
+ "learning_rate": 3.259259259259259e-05,
600
+ "loss": 1.7713,
601
+ "step": 400
602
+ },
603
+ {
604
+ "epoch": 5.333333333333333,
605
+ "eval_loss": 2.8094286918640137,
606
+ "eval_runtime": 43.8629,
607
+ "eval_samples_per_second": 22.798,
608
+ "eval_steps_per_second": 2.85,
609
+ "step": 400
610
+ },
611
+ {
612
+ "epoch": 5.466666666666667,
613
+ "grad_norm": 3.4474265575408936,
614
+ "learning_rate": 3.140740740740741e-05,
615
+ "loss": 1.7983,
616
+ "step": 410
617
+ },
618
+ {
619
+ "epoch": 5.466666666666667,
620
+ "eval_loss": 2.827517509460449,
621
+ "eval_runtime": 43.8611,
622
+ "eval_samples_per_second": 22.799,
623
+ "eval_steps_per_second": 2.85,
624
+ "step": 410
625
+ },
626
+ {
627
+ "epoch": 5.6,
628
+ "grad_norm": 3.1924540996551514,
629
+ "learning_rate": 3.0222222222222225e-05,
630
+ "loss": 1.8091,
631
+ "step": 420
632
+ },
633
+ {
634
+ "epoch": 5.6,
635
+ "eval_loss": 2.81618332862854,
636
+ "eval_runtime": 43.8544,
637
+ "eval_samples_per_second": 22.803,
638
+ "eval_steps_per_second": 2.85,
639
+ "step": 420
640
+ },
641
+ {
642
+ "epoch": 5.733333333333333,
643
+ "grad_norm": 3.5224015712738037,
644
+ "learning_rate": 2.9037037037037042e-05,
645
+ "loss": 1.8253,
646
+ "step": 430
647
+ },
648
+ {
649
+ "epoch": 5.733333333333333,
650
+ "eval_loss": 2.816711187362671,
651
+ "eval_runtime": 43.8685,
652
+ "eval_samples_per_second": 22.795,
653
+ "eval_steps_per_second": 2.849,
654
+ "step": 430
655
+ },
656
+ {
657
+ "epoch": 5.866666666666667,
658
+ "grad_norm": 3.60918927192688,
659
+ "learning_rate": 2.7851851851851856e-05,
660
+ "loss": 1.8013,
661
+ "step": 440
662
+ },
663
+ {
664
+ "epoch": 5.866666666666667,
665
+ "eval_loss": 2.8146169185638428,
666
+ "eval_runtime": 43.8516,
667
+ "eval_samples_per_second": 22.804,
668
+ "eval_steps_per_second": 2.851,
669
+ "step": 440
670
+ },
671
+ {
672
+ "epoch": 6.0,
673
+ "grad_norm": 3.5798070430755615,
674
+ "learning_rate": 2.6666666666666667e-05,
675
+ "loss": 1.8258,
676
+ "step": 450
677
+ },
678
+ {
679
+ "epoch": 6.0,
680
+ "eval_loss": 2.8134233951568604,
681
+ "eval_runtime": 43.8442,
682
+ "eval_samples_per_second": 22.808,
683
+ "eval_steps_per_second": 2.851,
684
+ "step": 450
685
+ },
686
+ {
687
+ "epoch": 6.133333333333334,
688
+ "grad_norm": 5.563477993011475,
689
+ "learning_rate": 2.5481481481481484e-05,
690
+ "loss": 1.6649,
691
+ "step": 460
692
+ },
693
+ {
694
+ "epoch": 6.133333333333334,
695
+ "eval_loss": 2.9189789295196533,
696
+ "eval_runtime": 43.8602,
697
+ "eval_samples_per_second": 22.8,
698
+ "eval_steps_per_second": 2.85,
699
+ "step": 460
700
+ },
701
+ {
702
+ "epoch": 6.266666666666667,
703
+ "grad_norm": 4.192393779754639,
704
+ "learning_rate": 2.4296296296296298e-05,
705
+ "loss": 1.7443,
706
+ "step": 470
707
+ },
708
+ {
709
+ "epoch": 6.266666666666667,
710
+ "eval_loss": 2.893780469894409,
711
+ "eval_runtime": 43.8434,
712
+ "eval_samples_per_second": 22.808,
713
+ "eval_steps_per_second": 2.851,
714
+ "step": 470
715
+ },
716
+ {
717
+ "epoch": 6.4,
718
+ "grad_norm": 4.8650593757629395,
719
+ "learning_rate": 2.3111111111111112e-05,
720
+ "loss": 1.6961,
721
+ "step": 480
722
+ },
723
+ {
724
+ "epoch": 6.4,
725
+ "eval_loss": 2.8861398696899414,
726
+ "eval_runtime": 43.8417,
727
+ "eval_samples_per_second": 22.809,
728
+ "eval_steps_per_second": 2.851,
729
+ "step": 480
730
+ },
731
+ {
732
+ "epoch": 6.533333333333333,
733
+ "grad_norm": 3.844482660293579,
734
+ "learning_rate": 2.192592592592593e-05,
735
+ "loss": 1.6868,
736
+ "step": 490
737
+ },
738
+ {
739
+ "epoch": 6.533333333333333,
740
+ "eval_loss": 2.900317907333374,
741
+ "eval_runtime": 43.8557,
742
+ "eval_samples_per_second": 22.802,
743
+ "eval_steps_per_second": 2.85,
744
+ "step": 490
745
+ },
746
+ {
747
+ "epoch": 6.666666666666667,
748
+ "grad_norm": 4.230032920837402,
749
+ "learning_rate": 2.074074074074074e-05,
750
+ "loss": 1.6593,
751
+ "step": 500
752
+ },
753
+ {
754
+ "epoch": 6.666666666666667,
755
+ "eval_loss": 2.892076253890991,
756
+ "eval_runtime": 43.8479,
757
+ "eval_samples_per_second": 22.806,
758
+ "eval_steps_per_second": 2.851,
759
+ "step": 500
760
+ },
761
+ {
762
+ "epoch": 6.8,
763
+ "grad_norm": 4.427380561828613,
764
+ "learning_rate": 1.9555555555555557e-05,
765
+ "loss": 1.6777,
766
+ "step": 510
767
+ },
768
+ {
769
+ "epoch": 6.8,
770
+ "eval_loss": 2.8877696990966797,
771
+ "eval_runtime": 43.8489,
772
+ "eval_samples_per_second": 22.806,
773
+ "eval_steps_per_second": 2.851,
774
+ "step": 510
775
+ },
776
+ {
777
+ "epoch": 6.933333333333334,
778
+ "grad_norm": 4.23176908493042,
779
+ "learning_rate": 1.837037037037037e-05,
780
+ "loss": 1.7331,
781
+ "step": 520
782
+ },
783
+ {
784
+ "epoch": 6.933333333333334,
785
+ "eval_loss": 2.889272928237915,
786
+ "eval_runtime": 43.8577,
787
+ "eval_samples_per_second": 22.801,
788
+ "eval_steps_per_second": 2.85,
789
+ "step": 520
790
+ },
791
+ {
792
+ "epoch": 7.066666666666666,
793
+ "grad_norm": 3.9098429679870605,
794
+ "learning_rate": 1.7185185185185185e-05,
795
+ "loss": 1.6741,
796
+ "step": 530
797
+ },
798
+ {
799
+ "epoch": 7.066666666666666,
800
+ "eval_loss": 2.9202494621276855,
801
+ "eval_runtime": 43.8571,
802
+ "eval_samples_per_second": 22.801,
803
+ "eval_steps_per_second": 2.85,
804
+ "step": 530
805
+ },
806
+ {
807
+ "epoch": 7.2,
808
+ "grad_norm": 4.320191383361816,
809
+ "learning_rate": 1.6000000000000003e-05,
810
+ "loss": 1.5711,
811
+ "step": 540
812
+ },
813
+ {
814
+ "epoch": 7.2,
815
+ "eval_loss": 2.97855806350708,
816
+ "eval_runtime": 43.8599,
817
+ "eval_samples_per_second": 22.8,
818
+ "eval_steps_per_second": 2.85,
819
+ "step": 540
820
+ },
821
+ {
822
+ "epoch": 7.333333333333333,
823
+ "grad_norm": 4.003049850463867,
824
+ "learning_rate": 1.4814814814814815e-05,
825
+ "loss": 1.6106,
826
+ "step": 550
827
+ },
828
+ {
829
+ "epoch": 7.333333333333333,
830
+ "eval_loss": 2.9440739154815674,
831
+ "eval_runtime": 43.8605,
832
+ "eval_samples_per_second": 22.8,
833
+ "eval_steps_per_second": 2.85,
834
+ "step": 550
835
+ },
836
+ {
837
+ "epoch": 7.466666666666667,
838
+ "grad_norm": 4.265935897827148,
839
+ "learning_rate": 1.362962962962963e-05,
840
+ "loss": 1.6241,
841
+ "step": 560
842
+ },
843
+ {
844
+ "epoch": 7.466666666666667,
845
+ "eval_loss": 2.958505630493164,
846
+ "eval_runtime": 43.8614,
847
+ "eval_samples_per_second": 22.799,
848
+ "eval_steps_per_second": 2.85,
849
+ "step": 560
850
+ },
851
+ {
852
+ "epoch": 7.6,
853
+ "grad_norm": 5.025564670562744,
854
+ "learning_rate": 1.2444444444444446e-05,
855
+ "loss": 1.6306,
856
+ "step": 570
857
+ },
858
+ {
859
+ "epoch": 7.6,
860
+ "eval_loss": 2.956601619720459,
861
+ "eval_runtime": 43.8595,
862
+ "eval_samples_per_second": 22.8,
863
+ "eval_steps_per_second": 2.85,
864
+ "step": 570
865
+ },
866
+ {
867
+ "epoch": 7.733333333333333,
868
+ "grad_norm": 4.252591133117676,
869
+ "learning_rate": 1.125925925925926e-05,
870
+ "loss": 1.5933,
871
+ "step": 580
872
+ },
873
+ {
874
+ "epoch": 7.733333333333333,
875
+ "eval_loss": 2.9567930698394775,
876
+ "eval_runtime": 43.8568,
877
+ "eval_samples_per_second": 22.801,
878
+ "eval_steps_per_second": 2.85,
879
+ "step": 580
880
+ },
881
+ {
882
+ "epoch": 7.866666666666667,
883
+ "grad_norm": 4.484741687774658,
884
+ "learning_rate": 1.0192592592592594e-05,
885
+ "loss": 1.6441,
886
+ "step": 590
887
+ },
888
+ {
889
+ "epoch": 7.866666666666667,
890
+ "eval_loss": 2.9549593925476074,
891
+ "eval_runtime": 43.8579,
892
+ "eval_samples_per_second": 22.801,
893
+ "eval_steps_per_second": 2.85,
894
+ "step": 590
895
+ },
896
+ {
897
+ "epoch": 8.0,
898
+ "grad_norm": 4.397695064544678,
899
+ "learning_rate": 9.007407407407408e-06,
900
+ "loss": 1.5878,
901
+ "step": 600
902
+ },
903
+ {
904
+ "epoch": 8.0,
905
+ "eval_loss": 2.948493480682373,
906
+ "eval_runtime": 43.8666,
907
+ "eval_samples_per_second": 22.796,
908
+ "eval_steps_per_second": 2.85,
909
+ "step": 600
910
+ },
911
+ {
912
+ "epoch": 8.133333333333333,
913
+ "grad_norm": 5.092386245727539,
914
+ "learning_rate": 7.822222222222224e-06,
915
+ "loss": 1.5588,
916
+ "step": 610
917
+ },
918
+ {
919
+ "epoch": 8.133333333333333,
920
+ "eval_loss": 2.9865269660949707,
921
+ "eval_runtime": 43.8606,
922
+ "eval_samples_per_second": 22.8,
923
+ "eval_steps_per_second": 2.85,
924
+ "step": 610
925
+ },
926
+ {
927
+ "epoch": 8.266666666666667,
928
+ "grad_norm": 4.463871479034424,
929
+ "learning_rate": 6.637037037037037e-06,
930
+ "loss": 1.5338,
931
+ "step": 620
932
+ },
933
+ {
934
+ "epoch": 8.266666666666667,
935
+ "eval_loss": 3.0131285190582275,
936
+ "eval_runtime": 43.8679,
937
+ "eval_samples_per_second": 22.796,
938
+ "eval_steps_per_second": 2.849,
939
+ "step": 620
940
+ }
941
+ ],
942
+ "logging_steps": 10,
943
+ "max_steps": 675,
944
+ "num_input_tokens_seen": 0,
945
+ "num_train_epochs": 9,
946
+ "save_steps": 10,
947
+ "stateful_callbacks": {
948
+ "TrainerControl": {
949
+ "args": {
950
+ "should_epoch_stop": false,
951
+ "should_evaluate": false,
952
+ "should_log": false,
953
+ "should_save": true,
954
+ "should_training_stop": false
955
+ },
956
+ "attributes": {}
957
+ }
958
+ },
959
+ "total_flos": 1.015936463142912e+17,
960
+ "train_batch_size": 8,
961
+ "trial_name": null,
962
+ "trial_params": null
963
+ }
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-630/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/pythia-6_9b
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-630/adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/workspace/pythia-6_9b",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.1,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 8,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "dense_h_to_4h",
24
+ "query_key_value",
25
+ "dense",
26
+ "dense_4h_to_h"
27
+ ],
28
+ "task_type": "CAUSAL_LM",
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-630/trainer_state.json ADDED
@@ -0,0 +1,978 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 2.535032033920288,
3
+ "best_model_checkpoint": "./output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-150",
4
+ "epoch": 8.4,
5
+ "eval_steps": 10,
6
+ "global_step": 630,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.13333333333333333,
13
+ "grad_norm": 0.36938729882240295,
14
+ "learning_rate": 7.881481481481482e-05,
15
+ "loss": 2.519,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.13333333333333333,
20
+ "eval_loss": 2.579638957977295,
21
+ "eval_runtime": 43.8215,
22
+ "eval_samples_per_second": 22.82,
23
+ "eval_steps_per_second": 2.852,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.26666666666666666,
28
+ "grad_norm": 0.39850670099258423,
29
+ "learning_rate": 7.762962962962963e-05,
30
+ "loss": 2.5224,
31
+ "step": 20
32
+ },
33
+ {
34
+ "epoch": 0.26666666666666666,
35
+ "eval_loss": 2.5729691982269287,
36
+ "eval_runtime": 43.8179,
37
+ "eval_samples_per_second": 22.822,
38
+ "eval_steps_per_second": 2.853,
39
+ "step": 20
40
+ },
41
+ {
42
+ "epoch": 0.4,
43
+ "grad_norm": 0.40211933851242065,
44
+ "learning_rate": 7.644444444444445e-05,
45
+ "loss": 2.5169,
46
+ "step": 30
47
+ },
48
+ {
49
+ "epoch": 0.4,
50
+ "eval_loss": 2.567735433578491,
51
+ "eval_runtime": 43.8366,
52
+ "eval_samples_per_second": 22.812,
53
+ "eval_steps_per_second": 2.851,
54
+ "step": 30
55
+ },
56
+ {
57
+ "epoch": 0.5333333333333333,
58
+ "grad_norm": 0.6892333030700684,
59
+ "learning_rate": 7.525925925925926e-05,
60
+ "loss": 2.5784,
61
+ "step": 40
62
+ },
63
+ {
64
+ "epoch": 0.5333333333333333,
65
+ "eval_loss": 2.562650442123413,
66
+ "eval_runtime": 43.8377,
67
+ "eval_samples_per_second": 22.811,
68
+ "eval_steps_per_second": 2.851,
69
+ "step": 40
70
+ },
71
+ {
72
+ "epoch": 0.6666666666666666,
73
+ "grad_norm": 0.442343533039093,
74
+ "learning_rate": 7.407407407407409e-05,
75
+ "loss": 2.5431,
76
+ "step": 50
77
+ },
78
+ {
79
+ "epoch": 0.6666666666666666,
80
+ "eval_loss": 2.556513786315918,
81
+ "eval_runtime": 43.8656,
82
+ "eval_samples_per_second": 22.797,
83
+ "eval_steps_per_second": 2.85,
84
+ "step": 50
85
+ },
86
+ {
87
+ "epoch": 0.8,
88
+ "grad_norm": 0.4059845805168152,
89
+ "learning_rate": 7.28888888888889e-05,
90
+ "loss": 2.4936,
91
+ "step": 60
92
+ },
93
+ {
94
+ "epoch": 0.8,
95
+ "eval_loss": 2.552133798599243,
96
+ "eval_runtime": 43.8403,
97
+ "eval_samples_per_second": 22.81,
98
+ "eval_steps_per_second": 2.851,
99
+ "step": 60
100
+ },
101
+ {
102
+ "epoch": 0.9333333333333333,
103
+ "grad_norm": 0.48126307129859924,
104
+ "learning_rate": 7.170370370370371e-05,
105
+ "loss": 2.4901,
106
+ "step": 70
107
+ },
108
+ {
109
+ "epoch": 0.9333333333333333,
110
+ "eval_loss": 2.5477023124694824,
111
+ "eval_runtime": 43.8351,
112
+ "eval_samples_per_second": 22.813,
113
+ "eval_steps_per_second": 2.852,
114
+ "step": 70
115
+ },
116
+ {
117
+ "epoch": 1.0666666666666667,
118
+ "grad_norm": 0.48629865050315857,
119
+ "learning_rate": 7.051851851851853e-05,
120
+ "loss": 2.5114,
121
+ "step": 80
122
+ },
123
+ {
124
+ "epoch": 1.0666666666666667,
125
+ "eval_loss": 2.543431043624878,
126
+ "eval_runtime": 43.8432,
127
+ "eval_samples_per_second": 22.809,
128
+ "eval_steps_per_second": 2.851,
129
+ "step": 80
130
+ },
131
+ {
132
+ "epoch": 1.2,
133
+ "grad_norm": 0.5880796313285828,
134
+ "learning_rate": 6.933333333333334e-05,
135
+ "loss": 2.4446,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 1.2,
140
+ "eval_loss": 2.544339418411255,
141
+ "eval_runtime": 43.8437,
142
+ "eval_samples_per_second": 22.808,
143
+ "eval_steps_per_second": 2.851,
144
+ "step": 90
145
+ },
146
+ {
147
+ "epoch": 1.3333333333333333,
148
+ "grad_norm": 0.6746829748153687,
149
+ "learning_rate": 6.814814814814815e-05,
150
+ "loss": 2.4477,
151
+ "step": 100
152
+ },
153
+ {
154
+ "epoch": 1.3333333333333333,
155
+ "eval_loss": 2.544358968734741,
156
+ "eval_runtime": 43.8613,
157
+ "eval_samples_per_second": 22.799,
158
+ "eval_steps_per_second": 2.85,
159
+ "step": 100
160
+ },
161
+ {
162
+ "epoch": 1.4666666666666668,
163
+ "grad_norm": 0.8208937048912048,
164
+ "learning_rate": 6.696296296296296e-05,
165
+ "loss": 2.4004,
166
+ "step": 110
167
+ },
168
+ {
169
+ "epoch": 1.4666666666666668,
170
+ "eval_loss": 2.54068660736084,
171
+ "eval_runtime": 43.8426,
172
+ "eval_samples_per_second": 22.809,
173
+ "eval_steps_per_second": 2.851,
174
+ "step": 110
175
+ },
176
+ {
177
+ "epoch": 1.6,
178
+ "grad_norm": 0.925931453704834,
179
+ "learning_rate": 6.577777777777777e-05,
180
+ "loss": 2.3889,
181
+ "step": 120
182
+ },
183
+ {
184
+ "epoch": 1.6,
185
+ "eval_loss": 2.5393033027648926,
186
+ "eval_runtime": 43.8383,
187
+ "eval_samples_per_second": 22.811,
188
+ "eval_steps_per_second": 2.851,
189
+ "step": 120
190
+ },
191
+ {
192
+ "epoch": 1.7333333333333334,
193
+ "grad_norm": 0.8785662055015564,
194
+ "learning_rate": 6.45925925925926e-05,
195
+ "loss": 2.3959,
196
+ "step": 130
197
+ },
198
+ {
199
+ "epoch": 1.7333333333333334,
200
+ "eval_loss": 2.5367038249969482,
201
+ "eval_runtime": 43.8508,
202
+ "eval_samples_per_second": 22.805,
203
+ "eval_steps_per_second": 2.851,
204
+ "step": 130
205
+ },
206
+ {
207
+ "epoch": 1.8666666666666667,
208
+ "grad_norm": 0.941368818283081,
209
+ "learning_rate": 6.340740740740741e-05,
210
+ "loss": 2.3924,
211
+ "step": 140
212
+ },
213
+ {
214
+ "epoch": 1.8666666666666667,
215
+ "eval_loss": 2.535139560699463,
216
+ "eval_runtime": 43.8588,
217
+ "eval_samples_per_second": 22.8,
218
+ "eval_steps_per_second": 2.85,
219
+ "step": 140
220
+ },
221
+ {
222
+ "epoch": 2.0,
223
+ "grad_norm": 0.9578835368156433,
224
+ "learning_rate": 6.222222222222223e-05,
225
+ "loss": 2.4278,
226
+ "step": 150
227
+ },
228
+ {
229
+ "epoch": 2.0,
230
+ "eval_loss": 2.535032033920288,
231
+ "eval_runtime": 43.8484,
232
+ "eval_samples_per_second": 22.806,
233
+ "eval_steps_per_second": 2.851,
234
+ "step": 150
235
+ },
236
+ {
237
+ "epoch": 2.1333333333333333,
238
+ "grad_norm": 1.1541856527328491,
239
+ "learning_rate": 6.103703703703704e-05,
240
+ "loss": 2.2895,
241
+ "step": 160
242
+ },
243
+ {
244
+ "epoch": 2.1333333333333333,
245
+ "eval_loss": 2.564768075942993,
246
+ "eval_runtime": 43.8568,
247
+ "eval_samples_per_second": 22.801,
248
+ "eval_steps_per_second": 2.85,
249
+ "step": 160
250
+ },
251
+ {
252
+ "epoch": 2.2666666666666666,
253
+ "grad_norm": 1.4076604843139648,
254
+ "learning_rate": 5.9851851851851855e-05,
255
+ "loss": 2.2107,
256
+ "step": 170
257
+ },
258
+ {
259
+ "epoch": 2.2666666666666666,
260
+ "eval_loss": 2.5832314491271973,
261
+ "eval_runtime": 43.8455,
262
+ "eval_samples_per_second": 22.807,
263
+ "eval_steps_per_second": 2.851,
264
+ "step": 170
265
+ },
266
+ {
267
+ "epoch": 2.4,
268
+ "grad_norm": 1.4847813844680786,
269
+ "learning_rate": 5.8666666666666665e-05,
270
+ "loss": 2.2588,
271
+ "step": 180
272
+ },
273
+ {
274
+ "epoch": 2.4,
275
+ "eval_loss": 2.5781586170196533,
276
+ "eval_runtime": 43.8578,
277
+ "eval_samples_per_second": 22.801,
278
+ "eval_steps_per_second": 2.85,
279
+ "step": 180
280
+ },
281
+ {
282
+ "epoch": 2.533333333333333,
283
+ "grad_norm": 1.5135377645492554,
284
+ "learning_rate": 5.748148148148149e-05,
285
+ "loss": 2.2099,
286
+ "step": 190
287
+ },
288
+ {
289
+ "epoch": 2.533333333333333,
290
+ "eval_loss": 2.5752007961273193,
291
+ "eval_runtime": 43.8521,
292
+ "eval_samples_per_second": 22.804,
293
+ "eval_steps_per_second": 2.85,
294
+ "step": 190
295
+ },
296
+ {
297
+ "epoch": 2.6666666666666665,
298
+ "grad_norm": 1.5297592878341675,
299
+ "learning_rate": 5.62962962962963e-05,
300
+ "loss": 2.2965,
301
+ "step": 200
302
+ },
303
+ {
304
+ "epoch": 2.6666666666666665,
305
+ "eval_loss": 2.579918622970581,
306
+ "eval_runtime": 43.8661,
307
+ "eval_samples_per_second": 22.797,
308
+ "eval_steps_per_second": 2.85,
309
+ "step": 200
310
+ },
311
+ {
312
+ "epoch": 2.8,
313
+ "grad_norm": 1.6282892227172852,
314
+ "learning_rate": 5.511111111111112e-05,
315
+ "loss": 2.2487,
316
+ "step": 210
317
+ },
318
+ {
319
+ "epoch": 2.8,
320
+ "eval_loss": 2.5760037899017334,
321
+ "eval_runtime": 43.8379,
322
+ "eval_samples_per_second": 22.811,
323
+ "eval_steps_per_second": 2.851,
324
+ "step": 210
325
+ },
326
+ {
327
+ "epoch": 2.9333333333333336,
328
+ "grad_norm": 1.74424409866333,
329
+ "learning_rate": 5.392592592592593e-05,
330
+ "loss": 2.2049,
331
+ "step": 220
332
+ },
333
+ {
334
+ "epoch": 2.9333333333333336,
335
+ "eval_loss": 2.576190233230591,
336
+ "eval_runtime": 43.8491,
337
+ "eval_samples_per_second": 22.805,
338
+ "eval_steps_per_second": 2.851,
339
+ "step": 220
340
+ },
341
+ {
342
+ "epoch": 3.066666666666667,
343
+ "grad_norm": 1.654069423675537,
344
+ "learning_rate": 5.274074074074074e-05,
345
+ "loss": 2.1188,
346
+ "step": 230
347
+ },
348
+ {
349
+ "epoch": 3.066666666666667,
350
+ "eval_loss": 2.5971405506134033,
351
+ "eval_runtime": 43.855,
352
+ "eval_samples_per_second": 22.802,
353
+ "eval_steps_per_second": 2.85,
354
+ "step": 230
355
+ },
356
+ {
357
+ "epoch": 3.2,
358
+ "grad_norm": 2.541767120361328,
359
+ "learning_rate": 5.155555555555556e-05,
360
+ "loss": 2.0788,
361
+ "step": 240
362
+ },
363
+ {
364
+ "epoch": 3.2,
365
+ "eval_loss": 2.6767666339874268,
366
+ "eval_runtime": 43.8368,
367
+ "eval_samples_per_second": 22.812,
368
+ "eval_steps_per_second": 2.851,
369
+ "step": 240
370
+ },
371
+ {
372
+ "epoch": 3.3333333333333335,
373
+ "grad_norm": 2.0508077144622803,
374
+ "learning_rate": 5.037037037037037e-05,
375
+ "loss": 2.0784,
376
+ "step": 250
377
+ },
378
+ {
379
+ "epoch": 3.3333333333333335,
380
+ "eval_loss": 2.6486454010009766,
381
+ "eval_runtime": 43.8529,
382
+ "eval_samples_per_second": 22.803,
383
+ "eval_steps_per_second": 2.85,
384
+ "step": 250
385
+ },
386
+ {
387
+ "epoch": 3.466666666666667,
388
+ "grad_norm": 2.1096036434173584,
389
+ "learning_rate": 4.918518518518519e-05,
390
+ "loss": 2.0633,
391
+ "step": 260
392
+ },
393
+ {
394
+ "epoch": 3.466666666666667,
395
+ "eval_loss": 2.6501405239105225,
396
+ "eval_runtime": 43.8632,
397
+ "eval_samples_per_second": 22.798,
398
+ "eval_steps_per_second": 2.85,
399
+ "step": 260
400
+ },
401
+ {
402
+ "epoch": 3.6,
403
+ "grad_norm": 2.3028736114501953,
404
+ "learning_rate": 4.8e-05,
405
+ "loss": 2.0722,
406
+ "step": 270
407
+ },
408
+ {
409
+ "epoch": 3.6,
410
+ "eval_loss": 2.657053232192993,
411
+ "eval_runtime": 43.8423,
412
+ "eval_samples_per_second": 22.809,
413
+ "eval_steps_per_second": 2.851,
414
+ "step": 270
415
+ },
416
+ {
417
+ "epoch": 3.7333333333333334,
418
+ "grad_norm": 2.1536757946014404,
419
+ "learning_rate": 4.681481481481481e-05,
420
+ "loss": 2.0155,
421
+ "step": 280
422
+ },
423
+ {
424
+ "epoch": 3.7333333333333334,
425
+ "eval_loss": 2.648275375366211,
426
+ "eval_runtime": 43.8328,
427
+ "eval_samples_per_second": 22.814,
428
+ "eval_steps_per_second": 2.852,
429
+ "step": 280
430
+ },
431
+ {
432
+ "epoch": 3.8666666666666667,
433
+ "grad_norm": 2.4079270362854004,
434
+ "learning_rate": 4.5629629629629636e-05,
435
+ "loss": 2.1111,
436
+ "step": 290
437
+ },
438
+ {
439
+ "epoch": 3.8666666666666667,
440
+ "eval_loss": 2.650322675704956,
441
+ "eval_runtime": 43.835,
442
+ "eval_samples_per_second": 22.813,
443
+ "eval_steps_per_second": 2.852,
444
+ "step": 290
445
+ },
446
+ {
447
+ "epoch": 4.0,
448
+ "grad_norm": 2.426234722137451,
449
+ "learning_rate": 4.444444444444445e-05,
450
+ "loss": 2.041,
451
+ "step": 300
452
+ },
453
+ {
454
+ "epoch": 4.0,
455
+ "eval_loss": 2.6490862369537354,
456
+ "eval_runtime": 43.845,
457
+ "eval_samples_per_second": 22.808,
458
+ "eval_steps_per_second": 2.851,
459
+ "step": 300
460
+ },
461
+ {
462
+ "epoch": 4.133333333333334,
463
+ "grad_norm": 2.8063745498657227,
464
+ "learning_rate": 4.3259259259259264e-05,
465
+ "loss": 1.9316,
466
+ "step": 310
467
+ },
468
+ {
469
+ "epoch": 4.133333333333334,
470
+ "eval_loss": 2.7609620094299316,
471
+ "eval_runtime": 43.8481,
472
+ "eval_samples_per_second": 22.806,
473
+ "eval_steps_per_second": 2.851,
474
+ "step": 310
475
+ },
476
+ {
477
+ "epoch": 4.266666666666667,
478
+ "grad_norm": 2.96854305267334,
479
+ "learning_rate": 4.2074074074074075e-05,
480
+ "loss": 1.8889,
481
+ "step": 320
482
+ },
483
+ {
484
+ "epoch": 4.266666666666667,
485
+ "eval_loss": 2.736968994140625,
486
+ "eval_runtime": 43.8633,
487
+ "eval_samples_per_second": 22.798,
488
+ "eval_steps_per_second": 2.85,
489
+ "step": 320
490
+ },
491
+ {
492
+ "epoch": 4.4,
493
+ "grad_norm": 2.637695789337158,
494
+ "learning_rate": 4.088888888888889e-05,
495
+ "loss": 1.9187,
496
+ "step": 330
497
+ },
498
+ {
499
+ "epoch": 4.4,
500
+ "eval_loss": 2.7382876873016357,
501
+ "eval_runtime": 43.8486,
502
+ "eval_samples_per_second": 22.806,
503
+ "eval_steps_per_second": 2.851,
504
+ "step": 330
505
+ },
506
+ {
507
+ "epoch": 4.533333333333333,
508
+ "grad_norm": 2.9106290340423584,
509
+ "learning_rate": 3.970370370370371e-05,
510
+ "loss": 1.9002,
511
+ "step": 340
512
+ },
513
+ {
514
+ "epoch": 4.533333333333333,
515
+ "eval_loss": 2.734544515609741,
516
+ "eval_runtime": 43.8491,
517
+ "eval_samples_per_second": 22.805,
518
+ "eval_steps_per_second": 2.851,
519
+ "step": 340
520
+ },
521
+ {
522
+ "epoch": 4.666666666666667,
523
+ "grad_norm": 2.769315481185913,
524
+ "learning_rate": 3.851851851851852e-05,
525
+ "loss": 1.9251,
526
+ "step": 350
527
+ },
528
+ {
529
+ "epoch": 4.666666666666667,
530
+ "eval_loss": 2.734708070755005,
531
+ "eval_runtime": 43.8534,
532
+ "eval_samples_per_second": 22.803,
533
+ "eval_steps_per_second": 2.85,
534
+ "step": 350
535
+ },
536
+ {
537
+ "epoch": 4.8,
538
+ "grad_norm": 2.940281867980957,
539
+ "learning_rate": 3.733333333333334e-05,
540
+ "loss": 1.9319,
541
+ "step": 360
542
+ },
543
+ {
544
+ "epoch": 4.8,
545
+ "eval_loss": 2.7300503253936768,
546
+ "eval_runtime": 43.9017,
547
+ "eval_samples_per_second": 22.778,
548
+ "eval_steps_per_second": 2.847,
549
+ "step": 360
550
+ },
551
+ {
552
+ "epoch": 4.933333333333334,
553
+ "grad_norm": 2.8305609226226807,
554
+ "learning_rate": 3.614814814814815e-05,
555
+ "loss": 1.9332,
556
+ "step": 370
557
+ },
558
+ {
559
+ "epoch": 4.933333333333334,
560
+ "eval_loss": 2.7309281826019287,
561
+ "eval_runtime": 43.8842,
562
+ "eval_samples_per_second": 22.787,
563
+ "eval_steps_per_second": 2.848,
564
+ "step": 370
565
+ },
566
+ {
567
+ "epoch": 5.066666666666666,
568
+ "grad_norm": 2.8739213943481445,
569
+ "learning_rate": 3.4962962962962965e-05,
570
+ "loss": 1.8846,
571
+ "step": 380
572
+ },
573
+ {
574
+ "epoch": 5.066666666666666,
575
+ "eval_loss": 2.76513671875,
576
+ "eval_runtime": 43.906,
577
+ "eval_samples_per_second": 22.776,
578
+ "eval_steps_per_second": 2.847,
579
+ "step": 380
580
+ },
581
+ {
582
+ "epoch": 5.2,
583
+ "grad_norm": 3.9025838375091553,
584
+ "learning_rate": 3.377777777777778e-05,
585
+ "loss": 1.7575,
586
+ "step": 390
587
+ },
588
+ {
589
+ "epoch": 5.2,
590
+ "eval_loss": 2.847782611846924,
591
+ "eval_runtime": 43.8665,
592
+ "eval_samples_per_second": 22.796,
593
+ "eval_steps_per_second": 2.85,
594
+ "step": 390
595
+ },
596
+ {
597
+ "epoch": 5.333333333333333,
598
+ "grad_norm": 3.299649715423584,
599
+ "learning_rate": 3.259259259259259e-05,
600
+ "loss": 1.7713,
601
+ "step": 400
602
+ },
603
+ {
604
+ "epoch": 5.333333333333333,
605
+ "eval_loss": 2.8094286918640137,
606
+ "eval_runtime": 43.8629,
607
+ "eval_samples_per_second": 22.798,
608
+ "eval_steps_per_second": 2.85,
609
+ "step": 400
610
+ },
611
+ {
612
+ "epoch": 5.466666666666667,
613
+ "grad_norm": 3.4474265575408936,
614
+ "learning_rate": 3.140740740740741e-05,
615
+ "loss": 1.7983,
616
+ "step": 410
617
+ },
618
+ {
619
+ "epoch": 5.466666666666667,
620
+ "eval_loss": 2.827517509460449,
621
+ "eval_runtime": 43.8611,
622
+ "eval_samples_per_second": 22.799,
623
+ "eval_steps_per_second": 2.85,
624
+ "step": 410
625
+ },
626
+ {
627
+ "epoch": 5.6,
628
+ "grad_norm": 3.1924540996551514,
629
+ "learning_rate": 3.0222222222222225e-05,
630
+ "loss": 1.8091,
631
+ "step": 420
632
+ },
633
+ {
634
+ "epoch": 5.6,
635
+ "eval_loss": 2.81618332862854,
636
+ "eval_runtime": 43.8544,
637
+ "eval_samples_per_second": 22.803,
638
+ "eval_steps_per_second": 2.85,
639
+ "step": 420
640
+ },
641
+ {
642
+ "epoch": 5.733333333333333,
643
+ "grad_norm": 3.5224015712738037,
644
+ "learning_rate": 2.9037037037037042e-05,
645
+ "loss": 1.8253,
646
+ "step": 430
647
+ },
648
+ {
649
+ "epoch": 5.733333333333333,
650
+ "eval_loss": 2.816711187362671,
651
+ "eval_runtime": 43.8685,
652
+ "eval_samples_per_second": 22.795,
653
+ "eval_steps_per_second": 2.849,
654
+ "step": 430
655
+ },
656
+ {
657
+ "epoch": 5.866666666666667,
658
+ "grad_norm": 3.60918927192688,
659
+ "learning_rate": 2.7851851851851856e-05,
660
+ "loss": 1.8013,
661
+ "step": 440
662
+ },
663
+ {
664
+ "epoch": 5.866666666666667,
665
+ "eval_loss": 2.8146169185638428,
666
+ "eval_runtime": 43.8516,
667
+ "eval_samples_per_second": 22.804,
668
+ "eval_steps_per_second": 2.851,
669
+ "step": 440
670
+ },
671
+ {
672
+ "epoch": 6.0,
673
+ "grad_norm": 3.5798070430755615,
674
+ "learning_rate": 2.6666666666666667e-05,
675
+ "loss": 1.8258,
676
+ "step": 450
677
+ },
678
+ {
679
+ "epoch": 6.0,
680
+ "eval_loss": 2.8134233951568604,
681
+ "eval_runtime": 43.8442,
682
+ "eval_samples_per_second": 22.808,
683
+ "eval_steps_per_second": 2.851,
684
+ "step": 450
685
+ },
686
+ {
687
+ "epoch": 6.133333333333334,
688
+ "grad_norm": 5.563477993011475,
689
+ "learning_rate": 2.5481481481481484e-05,
690
+ "loss": 1.6649,
691
+ "step": 460
692
+ },
693
+ {
694
+ "epoch": 6.133333333333334,
695
+ "eval_loss": 2.9189789295196533,
696
+ "eval_runtime": 43.8602,
697
+ "eval_samples_per_second": 22.8,
698
+ "eval_steps_per_second": 2.85,
699
+ "step": 460
700
+ },
701
+ {
702
+ "epoch": 6.266666666666667,
703
+ "grad_norm": 4.192393779754639,
704
+ "learning_rate": 2.4296296296296298e-05,
705
+ "loss": 1.7443,
706
+ "step": 470
707
+ },
708
+ {
709
+ "epoch": 6.266666666666667,
710
+ "eval_loss": 2.893780469894409,
711
+ "eval_runtime": 43.8434,
712
+ "eval_samples_per_second": 22.808,
713
+ "eval_steps_per_second": 2.851,
714
+ "step": 470
715
+ },
716
+ {
717
+ "epoch": 6.4,
718
+ "grad_norm": 4.8650593757629395,
719
+ "learning_rate": 2.3111111111111112e-05,
720
+ "loss": 1.6961,
721
+ "step": 480
722
+ },
723
+ {
724
+ "epoch": 6.4,
725
+ "eval_loss": 2.8861398696899414,
726
+ "eval_runtime": 43.8417,
727
+ "eval_samples_per_second": 22.809,
728
+ "eval_steps_per_second": 2.851,
729
+ "step": 480
730
+ },
731
+ {
732
+ "epoch": 6.533333333333333,
733
+ "grad_norm": 3.844482660293579,
734
+ "learning_rate": 2.192592592592593e-05,
735
+ "loss": 1.6868,
736
+ "step": 490
737
+ },
738
+ {
739
+ "epoch": 6.533333333333333,
740
+ "eval_loss": 2.900317907333374,
741
+ "eval_runtime": 43.8557,
742
+ "eval_samples_per_second": 22.802,
743
+ "eval_steps_per_second": 2.85,
744
+ "step": 490
745
+ },
746
+ {
747
+ "epoch": 6.666666666666667,
748
+ "grad_norm": 4.230032920837402,
749
+ "learning_rate": 2.074074074074074e-05,
750
+ "loss": 1.6593,
751
+ "step": 500
752
+ },
753
+ {
754
+ "epoch": 6.666666666666667,
755
+ "eval_loss": 2.892076253890991,
756
+ "eval_runtime": 43.8479,
757
+ "eval_samples_per_second": 22.806,
758
+ "eval_steps_per_second": 2.851,
759
+ "step": 500
760
+ },
761
+ {
762
+ "epoch": 6.8,
763
+ "grad_norm": 4.427380561828613,
764
+ "learning_rate": 1.9555555555555557e-05,
765
+ "loss": 1.6777,
766
+ "step": 510
767
+ },
768
+ {
769
+ "epoch": 6.8,
770
+ "eval_loss": 2.8877696990966797,
771
+ "eval_runtime": 43.8489,
772
+ "eval_samples_per_second": 22.806,
773
+ "eval_steps_per_second": 2.851,
774
+ "step": 510
775
+ },
776
+ {
777
+ "epoch": 6.933333333333334,
778
+ "grad_norm": 4.23176908493042,
779
+ "learning_rate": 1.837037037037037e-05,
780
+ "loss": 1.7331,
781
+ "step": 520
782
+ },
783
+ {
784
+ "epoch": 6.933333333333334,
785
+ "eval_loss": 2.889272928237915,
786
+ "eval_runtime": 43.8577,
787
+ "eval_samples_per_second": 22.801,
788
+ "eval_steps_per_second": 2.85,
789
+ "step": 520
790
+ },
791
+ {
792
+ "epoch": 7.066666666666666,
793
+ "grad_norm": 3.9098429679870605,
794
+ "learning_rate": 1.7185185185185185e-05,
795
+ "loss": 1.6741,
796
+ "step": 530
797
+ },
798
+ {
799
+ "epoch": 7.066666666666666,
800
+ "eval_loss": 2.9202494621276855,
801
+ "eval_runtime": 43.8571,
802
+ "eval_samples_per_second": 22.801,
803
+ "eval_steps_per_second": 2.85,
804
+ "step": 530
805
+ },
806
+ {
807
+ "epoch": 7.2,
808
+ "grad_norm": 4.320191383361816,
809
+ "learning_rate": 1.6000000000000003e-05,
810
+ "loss": 1.5711,
811
+ "step": 540
812
+ },
813
+ {
814
+ "epoch": 7.2,
815
+ "eval_loss": 2.97855806350708,
816
+ "eval_runtime": 43.8599,
817
+ "eval_samples_per_second": 22.8,
818
+ "eval_steps_per_second": 2.85,
819
+ "step": 540
820
+ },
821
+ {
822
+ "epoch": 7.333333333333333,
823
+ "grad_norm": 4.003049850463867,
824
+ "learning_rate": 1.4814814814814815e-05,
825
+ "loss": 1.6106,
826
+ "step": 550
827
+ },
828
+ {
829
+ "epoch": 7.333333333333333,
830
+ "eval_loss": 2.9440739154815674,
831
+ "eval_runtime": 43.8605,
832
+ "eval_samples_per_second": 22.8,
833
+ "eval_steps_per_second": 2.85,
834
+ "step": 550
835
+ },
836
+ {
837
+ "epoch": 7.466666666666667,
838
+ "grad_norm": 4.265935897827148,
839
+ "learning_rate": 1.362962962962963e-05,
840
+ "loss": 1.6241,
841
+ "step": 560
842
+ },
843
+ {
844
+ "epoch": 7.466666666666667,
845
+ "eval_loss": 2.958505630493164,
846
+ "eval_runtime": 43.8614,
847
+ "eval_samples_per_second": 22.799,
848
+ "eval_steps_per_second": 2.85,
849
+ "step": 560
850
+ },
851
+ {
852
+ "epoch": 7.6,
853
+ "grad_norm": 5.025564670562744,
854
+ "learning_rate": 1.2444444444444446e-05,
855
+ "loss": 1.6306,
856
+ "step": 570
857
+ },
858
+ {
859
+ "epoch": 7.6,
860
+ "eval_loss": 2.956601619720459,
861
+ "eval_runtime": 43.8595,
862
+ "eval_samples_per_second": 22.8,
863
+ "eval_steps_per_second": 2.85,
864
+ "step": 570
865
+ },
866
+ {
867
+ "epoch": 7.733333333333333,
868
+ "grad_norm": 4.252591133117676,
869
+ "learning_rate": 1.125925925925926e-05,
870
+ "loss": 1.5933,
871
+ "step": 580
872
+ },
873
+ {
874
+ "epoch": 7.733333333333333,
875
+ "eval_loss": 2.9567930698394775,
876
+ "eval_runtime": 43.8568,
877
+ "eval_samples_per_second": 22.801,
878
+ "eval_steps_per_second": 2.85,
879
+ "step": 580
880
+ },
881
+ {
882
+ "epoch": 7.866666666666667,
883
+ "grad_norm": 4.484741687774658,
884
+ "learning_rate": 1.0192592592592594e-05,
885
+ "loss": 1.6441,
886
+ "step": 590
887
+ },
888
+ {
889
+ "epoch": 7.866666666666667,
890
+ "eval_loss": 2.9549593925476074,
891
+ "eval_runtime": 43.8579,
892
+ "eval_samples_per_second": 22.801,
893
+ "eval_steps_per_second": 2.85,
894
+ "step": 590
895
+ },
896
+ {
897
+ "epoch": 8.0,
898
+ "grad_norm": 4.397695064544678,
899
+ "learning_rate": 9.007407407407408e-06,
900
+ "loss": 1.5878,
901
+ "step": 600
902
+ },
903
+ {
904
+ "epoch": 8.0,
905
+ "eval_loss": 2.948493480682373,
906
+ "eval_runtime": 43.8666,
907
+ "eval_samples_per_second": 22.796,
908
+ "eval_steps_per_second": 2.85,
909
+ "step": 600
910
+ },
911
+ {
912
+ "epoch": 8.133333333333333,
913
+ "grad_norm": 5.092386245727539,
914
+ "learning_rate": 7.822222222222224e-06,
915
+ "loss": 1.5588,
916
+ "step": 610
917
+ },
918
+ {
919
+ "epoch": 8.133333333333333,
920
+ "eval_loss": 2.9865269660949707,
921
+ "eval_runtime": 43.8606,
922
+ "eval_samples_per_second": 22.8,
923
+ "eval_steps_per_second": 2.85,
924
+ "step": 610
925
+ },
926
+ {
927
+ "epoch": 8.266666666666667,
928
+ "grad_norm": 4.463871479034424,
929
+ "learning_rate": 6.637037037037037e-06,
930
+ "loss": 1.5338,
931
+ "step": 620
932
+ },
933
+ {
934
+ "epoch": 8.266666666666667,
935
+ "eval_loss": 3.0131285190582275,
936
+ "eval_runtime": 43.8679,
937
+ "eval_samples_per_second": 22.796,
938
+ "eval_steps_per_second": 2.849,
939
+ "step": 620
940
+ },
941
+ {
942
+ "epoch": 8.4,
943
+ "grad_norm": 4.507328033447266,
944
+ "learning_rate": 5.451851851851853e-06,
945
+ "loss": 1.5481,
946
+ "step": 630
947
+ },
948
+ {
949
+ "epoch": 8.4,
950
+ "eval_loss": 3.003377914428711,
951
+ "eval_runtime": 43.8617,
952
+ "eval_samples_per_second": 22.799,
953
+ "eval_steps_per_second": 2.85,
954
+ "step": 630
955
+ }
956
+ ],
957
+ "logging_steps": 10,
958
+ "max_steps": 675,
959
+ "num_input_tokens_seen": 0,
960
+ "num_train_epochs": 9,
961
+ "save_steps": 10,
962
+ "stateful_callbacks": {
963
+ "TrainerControl": {
964
+ "args": {
965
+ "should_epoch_stop": false,
966
+ "should_evaluate": false,
967
+ "should_log": false,
968
+ "should_save": true,
969
+ "should_training_stop": false
970
+ },
971
+ "attributes": {}
972
+ }
973
+ },
974
+ "total_flos": 1.032322535129088e+17,
975
+ "train_batch_size": 8,
976
+ "trial_name": null,
977
+ "trial_params": null
978
+ }
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-640/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/pythia-6_9b
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-640/adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/workspace/pythia-6_9b",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.1,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 8,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "dense_h_to_4h",
24
+ "query_key_value",
25
+ "dense",
26
+ "dense_4h_to_h"
27
+ ],
28
+ "task_type": "CAUSAL_LM",
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-640/trainer_state.json ADDED
@@ -0,0 +1,993 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 2.535032033920288,
3
+ "best_model_checkpoint": "./output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-150",
4
+ "epoch": 8.533333333333333,
5
+ "eval_steps": 10,
6
+ "global_step": 640,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.13333333333333333,
13
+ "grad_norm": 0.36938729882240295,
14
+ "learning_rate": 7.881481481481482e-05,
15
+ "loss": 2.519,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.13333333333333333,
20
+ "eval_loss": 2.579638957977295,
21
+ "eval_runtime": 43.8215,
22
+ "eval_samples_per_second": 22.82,
23
+ "eval_steps_per_second": 2.852,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.26666666666666666,
28
+ "grad_norm": 0.39850670099258423,
29
+ "learning_rate": 7.762962962962963e-05,
30
+ "loss": 2.5224,
31
+ "step": 20
32
+ },
33
+ {
34
+ "epoch": 0.26666666666666666,
35
+ "eval_loss": 2.5729691982269287,
36
+ "eval_runtime": 43.8179,
37
+ "eval_samples_per_second": 22.822,
38
+ "eval_steps_per_second": 2.853,
39
+ "step": 20
40
+ },
41
+ {
42
+ "epoch": 0.4,
43
+ "grad_norm": 0.40211933851242065,
44
+ "learning_rate": 7.644444444444445e-05,
45
+ "loss": 2.5169,
46
+ "step": 30
47
+ },
48
+ {
49
+ "epoch": 0.4,
50
+ "eval_loss": 2.567735433578491,
51
+ "eval_runtime": 43.8366,
52
+ "eval_samples_per_second": 22.812,
53
+ "eval_steps_per_second": 2.851,
54
+ "step": 30
55
+ },
56
+ {
57
+ "epoch": 0.5333333333333333,
58
+ "grad_norm": 0.6892333030700684,
59
+ "learning_rate": 7.525925925925926e-05,
60
+ "loss": 2.5784,
61
+ "step": 40
62
+ },
63
+ {
64
+ "epoch": 0.5333333333333333,
65
+ "eval_loss": 2.562650442123413,
66
+ "eval_runtime": 43.8377,
67
+ "eval_samples_per_second": 22.811,
68
+ "eval_steps_per_second": 2.851,
69
+ "step": 40
70
+ },
71
+ {
72
+ "epoch": 0.6666666666666666,
73
+ "grad_norm": 0.442343533039093,
74
+ "learning_rate": 7.407407407407409e-05,
75
+ "loss": 2.5431,
76
+ "step": 50
77
+ },
78
+ {
79
+ "epoch": 0.6666666666666666,
80
+ "eval_loss": 2.556513786315918,
81
+ "eval_runtime": 43.8656,
82
+ "eval_samples_per_second": 22.797,
83
+ "eval_steps_per_second": 2.85,
84
+ "step": 50
85
+ },
86
+ {
87
+ "epoch": 0.8,
88
+ "grad_norm": 0.4059845805168152,
89
+ "learning_rate": 7.28888888888889e-05,
90
+ "loss": 2.4936,
91
+ "step": 60
92
+ },
93
+ {
94
+ "epoch": 0.8,
95
+ "eval_loss": 2.552133798599243,
96
+ "eval_runtime": 43.8403,
97
+ "eval_samples_per_second": 22.81,
98
+ "eval_steps_per_second": 2.851,
99
+ "step": 60
100
+ },
101
+ {
102
+ "epoch": 0.9333333333333333,
103
+ "grad_norm": 0.48126307129859924,
104
+ "learning_rate": 7.170370370370371e-05,
105
+ "loss": 2.4901,
106
+ "step": 70
107
+ },
108
+ {
109
+ "epoch": 0.9333333333333333,
110
+ "eval_loss": 2.5477023124694824,
111
+ "eval_runtime": 43.8351,
112
+ "eval_samples_per_second": 22.813,
113
+ "eval_steps_per_second": 2.852,
114
+ "step": 70
115
+ },
116
+ {
117
+ "epoch": 1.0666666666666667,
118
+ "grad_norm": 0.48629865050315857,
119
+ "learning_rate": 7.051851851851853e-05,
120
+ "loss": 2.5114,
121
+ "step": 80
122
+ },
123
+ {
124
+ "epoch": 1.0666666666666667,
125
+ "eval_loss": 2.543431043624878,
126
+ "eval_runtime": 43.8432,
127
+ "eval_samples_per_second": 22.809,
128
+ "eval_steps_per_second": 2.851,
129
+ "step": 80
130
+ },
131
+ {
132
+ "epoch": 1.2,
133
+ "grad_norm": 0.5880796313285828,
134
+ "learning_rate": 6.933333333333334e-05,
135
+ "loss": 2.4446,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 1.2,
140
+ "eval_loss": 2.544339418411255,
141
+ "eval_runtime": 43.8437,
142
+ "eval_samples_per_second": 22.808,
143
+ "eval_steps_per_second": 2.851,
144
+ "step": 90
145
+ },
146
+ {
147
+ "epoch": 1.3333333333333333,
148
+ "grad_norm": 0.6746829748153687,
149
+ "learning_rate": 6.814814814814815e-05,
150
+ "loss": 2.4477,
151
+ "step": 100
152
+ },
153
+ {
154
+ "epoch": 1.3333333333333333,
155
+ "eval_loss": 2.544358968734741,
156
+ "eval_runtime": 43.8613,
157
+ "eval_samples_per_second": 22.799,
158
+ "eval_steps_per_second": 2.85,
159
+ "step": 100
160
+ },
161
+ {
162
+ "epoch": 1.4666666666666668,
163
+ "grad_norm": 0.8208937048912048,
164
+ "learning_rate": 6.696296296296296e-05,
165
+ "loss": 2.4004,
166
+ "step": 110
167
+ },
168
+ {
169
+ "epoch": 1.4666666666666668,
170
+ "eval_loss": 2.54068660736084,
171
+ "eval_runtime": 43.8426,
172
+ "eval_samples_per_second": 22.809,
173
+ "eval_steps_per_second": 2.851,
174
+ "step": 110
175
+ },
176
+ {
177
+ "epoch": 1.6,
178
+ "grad_norm": 0.925931453704834,
179
+ "learning_rate": 6.577777777777777e-05,
180
+ "loss": 2.3889,
181
+ "step": 120
182
+ },
183
+ {
184
+ "epoch": 1.6,
185
+ "eval_loss": 2.5393033027648926,
186
+ "eval_runtime": 43.8383,
187
+ "eval_samples_per_second": 22.811,
188
+ "eval_steps_per_second": 2.851,
189
+ "step": 120
190
+ },
191
+ {
192
+ "epoch": 1.7333333333333334,
193
+ "grad_norm": 0.8785662055015564,
194
+ "learning_rate": 6.45925925925926e-05,
195
+ "loss": 2.3959,
196
+ "step": 130
197
+ },
198
+ {
199
+ "epoch": 1.7333333333333334,
200
+ "eval_loss": 2.5367038249969482,
201
+ "eval_runtime": 43.8508,
202
+ "eval_samples_per_second": 22.805,
203
+ "eval_steps_per_second": 2.851,
204
+ "step": 130
205
+ },
206
+ {
207
+ "epoch": 1.8666666666666667,
208
+ "grad_norm": 0.941368818283081,
209
+ "learning_rate": 6.340740740740741e-05,
210
+ "loss": 2.3924,
211
+ "step": 140
212
+ },
213
+ {
214
+ "epoch": 1.8666666666666667,
215
+ "eval_loss": 2.535139560699463,
216
+ "eval_runtime": 43.8588,
217
+ "eval_samples_per_second": 22.8,
218
+ "eval_steps_per_second": 2.85,
219
+ "step": 140
220
+ },
221
+ {
222
+ "epoch": 2.0,
223
+ "grad_norm": 0.9578835368156433,
224
+ "learning_rate": 6.222222222222223e-05,
225
+ "loss": 2.4278,
226
+ "step": 150
227
+ },
228
+ {
229
+ "epoch": 2.0,
230
+ "eval_loss": 2.535032033920288,
231
+ "eval_runtime": 43.8484,
232
+ "eval_samples_per_second": 22.806,
233
+ "eval_steps_per_second": 2.851,
234
+ "step": 150
235
+ },
236
+ {
237
+ "epoch": 2.1333333333333333,
238
+ "grad_norm": 1.1541856527328491,
239
+ "learning_rate": 6.103703703703704e-05,
240
+ "loss": 2.2895,
241
+ "step": 160
242
+ },
243
+ {
244
+ "epoch": 2.1333333333333333,
245
+ "eval_loss": 2.564768075942993,
246
+ "eval_runtime": 43.8568,
247
+ "eval_samples_per_second": 22.801,
248
+ "eval_steps_per_second": 2.85,
249
+ "step": 160
250
+ },
251
+ {
252
+ "epoch": 2.2666666666666666,
253
+ "grad_norm": 1.4076604843139648,
254
+ "learning_rate": 5.9851851851851855e-05,
255
+ "loss": 2.2107,
256
+ "step": 170
257
+ },
258
+ {
259
+ "epoch": 2.2666666666666666,
260
+ "eval_loss": 2.5832314491271973,
261
+ "eval_runtime": 43.8455,
262
+ "eval_samples_per_second": 22.807,
263
+ "eval_steps_per_second": 2.851,
264
+ "step": 170
265
+ },
266
+ {
267
+ "epoch": 2.4,
268
+ "grad_norm": 1.4847813844680786,
269
+ "learning_rate": 5.8666666666666665e-05,
270
+ "loss": 2.2588,
271
+ "step": 180
272
+ },
273
+ {
274
+ "epoch": 2.4,
275
+ "eval_loss": 2.5781586170196533,
276
+ "eval_runtime": 43.8578,
277
+ "eval_samples_per_second": 22.801,
278
+ "eval_steps_per_second": 2.85,
279
+ "step": 180
280
+ },
281
+ {
282
+ "epoch": 2.533333333333333,
283
+ "grad_norm": 1.5135377645492554,
284
+ "learning_rate": 5.748148148148149e-05,
285
+ "loss": 2.2099,
286
+ "step": 190
287
+ },
288
+ {
289
+ "epoch": 2.533333333333333,
290
+ "eval_loss": 2.5752007961273193,
291
+ "eval_runtime": 43.8521,
292
+ "eval_samples_per_second": 22.804,
293
+ "eval_steps_per_second": 2.85,
294
+ "step": 190
295
+ },
296
+ {
297
+ "epoch": 2.6666666666666665,
298
+ "grad_norm": 1.5297592878341675,
299
+ "learning_rate": 5.62962962962963e-05,
300
+ "loss": 2.2965,
301
+ "step": 200
302
+ },
303
+ {
304
+ "epoch": 2.6666666666666665,
305
+ "eval_loss": 2.579918622970581,
306
+ "eval_runtime": 43.8661,
307
+ "eval_samples_per_second": 22.797,
308
+ "eval_steps_per_second": 2.85,
309
+ "step": 200
310
+ },
311
+ {
312
+ "epoch": 2.8,
313
+ "grad_norm": 1.6282892227172852,
314
+ "learning_rate": 5.511111111111112e-05,
315
+ "loss": 2.2487,
316
+ "step": 210
317
+ },
318
+ {
319
+ "epoch": 2.8,
320
+ "eval_loss": 2.5760037899017334,
321
+ "eval_runtime": 43.8379,
322
+ "eval_samples_per_second": 22.811,
323
+ "eval_steps_per_second": 2.851,
324
+ "step": 210
325
+ },
326
+ {
327
+ "epoch": 2.9333333333333336,
328
+ "grad_norm": 1.74424409866333,
329
+ "learning_rate": 5.392592592592593e-05,
330
+ "loss": 2.2049,
331
+ "step": 220
332
+ },
333
+ {
334
+ "epoch": 2.9333333333333336,
335
+ "eval_loss": 2.576190233230591,
336
+ "eval_runtime": 43.8491,
337
+ "eval_samples_per_second": 22.805,
338
+ "eval_steps_per_second": 2.851,
339
+ "step": 220
340
+ },
341
+ {
342
+ "epoch": 3.066666666666667,
343
+ "grad_norm": 1.654069423675537,
344
+ "learning_rate": 5.274074074074074e-05,
345
+ "loss": 2.1188,
346
+ "step": 230
347
+ },
348
+ {
349
+ "epoch": 3.066666666666667,
350
+ "eval_loss": 2.5971405506134033,
351
+ "eval_runtime": 43.855,
352
+ "eval_samples_per_second": 22.802,
353
+ "eval_steps_per_second": 2.85,
354
+ "step": 230
355
+ },
356
+ {
357
+ "epoch": 3.2,
358
+ "grad_norm": 2.541767120361328,
359
+ "learning_rate": 5.155555555555556e-05,
360
+ "loss": 2.0788,
361
+ "step": 240
362
+ },
363
+ {
364
+ "epoch": 3.2,
365
+ "eval_loss": 2.6767666339874268,
366
+ "eval_runtime": 43.8368,
367
+ "eval_samples_per_second": 22.812,
368
+ "eval_steps_per_second": 2.851,
369
+ "step": 240
370
+ },
371
+ {
372
+ "epoch": 3.3333333333333335,
373
+ "grad_norm": 2.0508077144622803,
374
+ "learning_rate": 5.037037037037037e-05,
375
+ "loss": 2.0784,
376
+ "step": 250
377
+ },
378
+ {
379
+ "epoch": 3.3333333333333335,
380
+ "eval_loss": 2.6486454010009766,
381
+ "eval_runtime": 43.8529,
382
+ "eval_samples_per_second": 22.803,
383
+ "eval_steps_per_second": 2.85,
384
+ "step": 250
385
+ },
386
+ {
387
+ "epoch": 3.466666666666667,
388
+ "grad_norm": 2.1096036434173584,
389
+ "learning_rate": 4.918518518518519e-05,
390
+ "loss": 2.0633,
391
+ "step": 260
392
+ },
393
+ {
394
+ "epoch": 3.466666666666667,
395
+ "eval_loss": 2.6501405239105225,
396
+ "eval_runtime": 43.8632,
397
+ "eval_samples_per_second": 22.798,
398
+ "eval_steps_per_second": 2.85,
399
+ "step": 260
400
+ },
401
+ {
402
+ "epoch": 3.6,
403
+ "grad_norm": 2.3028736114501953,
404
+ "learning_rate": 4.8e-05,
405
+ "loss": 2.0722,
406
+ "step": 270
407
+ },
408
+ {
409
+ "epoch": 3.6,
410
+ "eval_loss": 2.657053232192993,
411
+ "eval_runtime": 43.8423,
412
+ "eval_samples_per_second": 22.809,
413
+ "eval_steps_per_second": 2.851,
414
+ "step": 270
415
+ },
416
+ {
417
+ "epoch": 3.7333333333333334,
418
+ "grad_norm": 2.1536757946014404,
419
+ "learning_rate": 4.681481481481481e-05,
420
+ "loss": 2.0155,
421
+ "step": 280
422
+ },
423
+ {
424
+ "epoch": 3.7333333333333334,
425
+ "eval_loss": 2.648275375366211,
426
+ "eval_runtime": 43.8328,
427
+ "eval_samples_per_second": 22.814,
428
+ "eval_steps_per_second": 2.852,
429
+ "step": 280
430
+ },
431
+ {
432
+ "epoch": 3.8666666666666667,
433
+ "grad_norm": 2.4079270362854004,
434
+ "learning_rate": 4.5629629629629636e-05,
435
+ "loss": 2.1111,
436
+ "step": 290
437
+ },
438
+ {
439
+ "epoch": 3.8666666666666667,
440
+ "eval_loss": 2.650322675704956,
441
+ "eval_runtime": 43.835,
442
+ "eval_samples_per_second": 22.813,
443
+ "eval_steps_per_second": 2.852,
444
+ "step": 290
445
+ },
446
+ {
447
+ "epoch": 4.0,
448
+ "grad_norm": 2.426234722137451,
449
+ "learning_rate": 4.444444444444445e-05,
450
+ "loss": 2.041,
451
+ "step": 300
452
+ },
453
+ {
454
+ "epoch": 4.0,
455
+ "eval_loss": 2.6490862369537354,
456
+ "eval_runtime": 43.845,
457
+ "eval_samples_per_second": 22.808,
458
+ "eval_steps_per_second": 2.851,
459
+ "step": 300
460
+ },
461
+ {
462
+ "epoch": 4.133333333333334,
463
+ "grad_norm": 2.8063745498657227,
464
+ "learning_rate": 4.3259259259259264e-05,
465
+ "loss": 1.9316,
466
+ "step": 310
467
+ },
468
+ {
469
+ "epoch": 4.133333333333334,
470
+ "eval_loss": 2.7609620094299316,
471
+ "eval_runtime": 43.8481,
472
+ "eval_samples_per_second": 22.806,
473
+ "eval_steps_per_second": 2.851,
474
+ "step": 310
475
+ },
476
+ {
477
+ "epoch": 4.266666666666667,
478
+ "grad_norm": 2.96854305267334,
479
+ "learning_rate": 4.2074074074074075e-05,
480
+ "loss": 1.8889,
481
+ "step": 320
482
+ },
483
+ {
484
+ "epoch": 4.266666666666667,
485
+ "eval_loss": 2.736968994140625,
486
+ "eval_runtime": 43.8633,
487
+ "eval_samples_per_second": 22.798,
488
+ "eval_steps_per_second": 2.85,
489
+ "step": 320
490
+ },
491
+ {
492
+ "epoch": 4.4,
493
+ "grad_norm": 2.637695789337158,
494
+ "learning_rate": 4.088888888888889e-05,
495
+ "loss": 1.9187,
496
+ "step": 330
497
+ },
498
+ {
499
+ "epoch": 4.4,
500
+ "eval_loss": 2.7382876873016357,
501
+ "eval_runtime": 43.8486,
502
+ "eval_samples_per_second": 22.806,
503
+ "eval_steps_per_second": 2.851,
504
+ "step": 330
505
+ },
506
+ {
507
+ "epoch": 4.533333333333333,
508
+ "grad_norm": 2.9106290340423584,
509
+ "learning_rate": 3.970370370370371e-05,
510
+ "loss": 1.9002,
511
+ "step": 340
512
+ },
513
+ {
514
+ "epoch": 4.533333333333333,
515
+ "eval_loss": 2.734544515609741,
516
+ "eval_runtime": 43.8491,
517
+ "eval_samples_per_second": 22.805,
518
+ "eval_steps_per_second": 2.851,
519
+ "step": 340
520
+ },
521
+ {
522
+ "epoch": 4.666666666666667,
523
+ "grad_norm": 2.769315481185913,
524
+ "learning_rate": 3.851851851851852e-05,
525
+ "loss": 1.9251,
526
+ "step": 350
527
+ },
528
+ {
529
+ "epoch": 4.666666666666667,
530
+ "eval_loss": 2.734708070755005,
531
+ "eval_runtime": 43.8534,
532
+ "eval_samples_per_second": 22.803,
533
+ "eval_steps_per_second": 2.85,
534
+ "step": 350
535
+ },
536
+ {
537
+ "epoch": 4.8,
538
+ "grad_norm": 2.940281867980957,
539
+ "learning_rate": 3.733333333333334e-05,
540
+ "loss": 1.9319,
541
+ "step": 360
542
+ },
543
+ {
544
+ "epoch": 4.8,
545
+ "eval_loss": 2.7300503253936768,
546
+ "eval_runtime": 43.9017,
547
+ "eval_samples_per_second": 22.778,
548
+ "eval_steps_per_second": 2.847,
549
+ "step": 360
550
+ },
551
+ {
552
+ "epoch": 4.933333333333334,
553
+ "grad_norm": 2.8305609226226807,
554
+ "learning_rate": 3.614814814814815e-05,
555
+ "loss": 1.9332,
556
+ "step": 370
557
+ },
558
+ {
559
+ "epoch": 4.933333333333334,
560
+ "eval_loss": 2.7309281826019287,
561
+ "eval_runtime": 43.8842,
562
+ "eval_samples_per_second": 22.787,
563
+ "eval_steps_per_second": 2.848,
564
+ "step": 370
565
+ },
566
+ {
567
+ "epoch": 5.066666666666666,
568
+ "grad_norm": 2.8739213943481445,
569
+ "learning_rate": 3.4962962962962965e-05,
570
+ "loss": 1.8846,
571
+ "step": 380
572
+ },
573
+ {
574
+ "epoch": 5.066666666666666,
575
+ "eval_loss": 2.76513671875,
576
+ "eval_runtime": 43.906,
577
+ "eval_samples_per_second": 22.776,
578
+ "eval_steps_per_second": 2.847,
579
+ "step": 380
580
+ },
581
+ {
582
+ "epoch": 5.2,
583
+ "grad_norm": 3.9025838375091553,
584
+ "learning_rate": 3.377777777777778e-05,
585
+ "loss": 1.7575,
586
+ "step": 390
587
+ },
588
+ {
589
+ "epoch": 5.2,
590
+ "eval_loss": 2.847782611846924,
591
+ "eval_runtime": 43.8665,
592
+ "eval_samples_per_second": 22.796,
593
+ "eval_steps_per_second": 2.85,
594
+ "step": 390
595
+ },
596
+ {
597
+ "epoch": 5.333333333333333,
598
+ "grad_norm": 3.299649715423584,
599
+ "learning_rate": 3.259259259259259e-05,
600
+ "loss": 1.7713,
601
+ "step": 400
602
+ },
603
+ {
604
+ "epoch": 5.333333333333333,
605
+ "eval_loss": 2.8094286918640137,
606
+ "eval_runtime": 43.8629,
607
+ "eval_samples_per_second": 22.798,
608
+ "eval_steps_per_second": 2.85,
609
+ "step": 400
610
+ },
611
+ {
612
+ "epoch": 5.466666666666667,
613
+ "grad_norm": 3.4474265575408936,
614
+ "learning_rate": 3.140740740740741e-05,
615
+ "loss": 1.7983,
616
+ "step": 410
617
+ },
618
+ {
619
+ "epoch": 5.466666666666667,
620
+ "eval_loss": 2.827517509460449,
621
+ "eval_runtime": 43.8611,
622
+ "eval_samples_per_second": 22.799,
623
+ "eval_steps_per_second": 2.85,
624
+ "step": 410
625
+ },
626
+ {
627
+ "epoch": 5.6,
628
+ "grad_norm": 3.1924540996551514,
629
+ "learning_rate": 3.0222222222222225e-05,
630
+ "loss": 1.8091,
631
+ "step": 420
632
+ },
633
+ {
634
+ "epoch": 5.6,
635
+ "eval_loss": 2.81618332862854,
636
+ "eval_runtime": 43.8544,
637
+ "eval_samples_per_second": 22.803,
638
+ "eval_steps_per_second": 2.85,
639
+ "step": 420
640
+ },
641
+ {
642
+ "epoch": 5.733333333333333,
643
+ "grad_norm": 3.5224015712738037,
644
+ "learning_rate": 2.9037037037037042e-05,
645
+ "loss": 1.8253,
646
+ "step": 430
647
+ },
648
+ {
649
+ "epoch": 5.733333333333333,
650
+ "eval_loss": 2.816711187362671,
651
+ "eval_runtime": 43.8685,
652
+ "eval_samples_per_second": 22.795,
653
+ "eval_steps_per_second": 2.849,
654
+ "step": 430
655
+ },
656
+ {
657
+ "epoch": 5.866666666666667,
658
+ "grad_norm": 3.60918927192688,
659
+ "learning_rate": 2.7851851851851856e-05,
660
+ "loss": 1.8013,
661
+ "step": 440
662
+ },
663
+ {
664
+ "epoch": 5.866666666666667,
665
+ "eval_loss": 2.8146169185638428,
666
+ "eval_runtime": 43.8516,
667
+ "eval_samples_per_second": 22.804,
668
+ "eval_steps_per_second": 2.851,
669
+ "step": 440
670
+ },
671
+ {
672
+ "epoch": 6.0,
673
+ "grad_norm": 3.5798070430755615,
674
+ "learning_rate": 2.6666666666666667e-05,
675
+ "loss": 1.8258,
676
+ "step": 450
677
+ },
678
+ {
679
+ "epoch": 6.0,
680
+ "eval_loss": 2.8134233951568604,
681
+ "eval_runtime": 43.8442,
682
+ "eval_samples_per_second": 22.808,
683
+ "eval_steps_per_second": 2.851,
684
+ "step": 450
685
+ },
686
+ {
687
+ "epoch": 6.133333333333334,
688
+ "grad_norm": 5.563477993011475,
689
+ "learning_rate": 2.5481481481481484e-05,
690
+ "loss": 1.6649,
691
+ "step": 460
692
+ },
693
+ {
694
+ "epoch": 6.133333333333334,
695
+ "eval_loss": 2.9189789295196533,
696
+ "eval_runtime": 43.8602,
697
+ "eval_samples_per_second": 22.8,
698
+ "eval_steps_per_second": 2.85,
699
+ "step": 460
700
+ },
701
+ {
702
+ "epoch": 6.266666666666667,
703
+ "grad_norm": 4.192393779754639,
704
+ "learning_rate": 2.4296296296296298e-05,
705
+ "loss": 1.7443,
706
+ "step": 470
707
+ },
708
+ {
709
+ "epoch": 6.266666666666667,
710
+ "eval_loss": 2.893780469894409,
711
+ "eval_runtime": 43.8434,
712
+ "eval_samples_per_second": 22.808,
713
+ "eval_steps_per_second": 2.851,
714
+ "step": 470
715
+ },
716
+ {
717
+ "epoch": 6.4,
718
+ "grad_norm": 4.8650593757629395,
719
+ "learning_rate": 2.3111111111111112e-05,
720
+ "loss": 1.6961,
721
+ "step": 480
722
+ },
723
+ {
724
+ "epoch": 6.4,
725
+ "eval_loss": 2.8861398696899414,
726
+ "eval_runtime": 43.8417,
727
+ "eval_samples_per_second": 22.809,
728
+ "eval_steps_per_second": 2.851,
729
+ "step": 480
730
+ },
731
+ {
732
+ "epoch": 6.533333333333333,
733
+ "grad_norm": 3.844482660293579,
734
+ "learning_rate": 2.192592592592593e-05,
735
+ "loss": 1.6868,
736
+ "step": 490
737
+ },
738
+ {
739
+ "epoch": 6.533333333333333,
740
+ "eval_loss": 2.900317907333374,
741
+ "eval_runtime": 43.8557,
742
+ "eval_samples_per_second": 22.802,
743
+ "eval_steps_per_second": 2.85,
744
+ "step": 490
745
+ },
746
+ {
747
+ "epoch": 6.666666666666667,
748
+ "grad_norm": 4.230032920837402,
749
+ "learning_rate": 2.074074074074074e-05,
750
+ "loss": 1.6593,
751
+ "step": 500
752
+ },
753
+ {
754
+ "epoch": 6.666666666666667,
755
+ "eval_loss": 2.892076253890991,
756
+ "eval_runtime": 43.8479,
757
+ "eval_samples_per_second": 22.806,
758
+ "eval_steps_per_second": 2.851,
759
+ "step": 500
760
+ },
761
+ {
762
+ "epoch": 6.8,
763
+ "grad_norm": 4.427380561828613,
764
+ "learning_rate": 1.9555555555555557e-05,
765
+ "loss": 1.6777,
766
+ "step": 510
767
+ },
768
+ {
769
+ "epoch": 6.8,
770
+ "eval_loss": 2.8877696990966797,
771
+ "eval_runtime": 43.8489,
772
+ "eval_samples_per_second": 22.806,
773
+ "eval_steps_per_second": 2.851,
774
+ "step": 510
775
+ },
776
+ {
777
+ "epoch": 6.933333333333334,
778
+ "grad_norm": 4.23176908493042,
779
+ "learning_rate": 1.837037037037037e-05,
780
+ "loss": 1.7331,
781
+ "step": 520
782
+ },
783
+ {
784
+ "epoch": 6.933333333333334,
785
+ "eval_loss": 2.889272928237915,
786
+ "eval_runtime": 43.8577,
787
+ "eval_samples_per_second": 22.801,
788
+ "eval_steps_per_second": 2.85,
789
+ "step": 520
790
+ },
791
+ {
792
+ "epoch": 7.066666666666666,
793
+ "grad_norm": 3.9098429679870605,
794
+ "learning_rate": 1.7185185185185185e-05,
795
+ "loss": 1.6741,
796
+ "step": 530
797
+ },
798
+ {
799
+ "epoch": 7.066666666666666,
800
+ "eval_loss": 2.9202494621276855,
801
+ "eval_runtime": 43.8571,
802
+ "eval_samples_per_second": 22.801,
803
+ "eval_steps_per_second": 2.85,
804
+ "step": 530
805
+ },
806
+ {
807
+ "epoch": 7.2,
808
+ "grad_norm": 4.320191383361816,
809
+ "learning_rate": 1.6000000000000003e-05,
810
+ "loss": 1.5711,
811
+ "step": 540
812
+ },
813
+ {
814
+ "epoch": 7.2,
815
+ "eval_loss": 2.97855806350708,
816
+ "eval_runtime": 43.8599,
817
+ "eval_samples_per_second": 22.8,
818
+ "eval_steps_per_second": 2.85,
819
+ "step": 540
820
+ },
821
+ {
822
+ "epoch": 7.333333333333333,
823
+ "grad_norm": 4.003049850463867,
824
+ "learning_rate": 1.4814814814814815e-05,
825
+ "loss": 1.6106,
826
+ "step": 550
827
+ },
828
+ {
829
+ "epoch": 7.333333333333333,
830
+ "eval_loss": 2.9440739154815674,
831
+ "eval_runtime": 43.8605,
832
+ "eval_samples_per_second": 22.8,
833
+ "eval_steps_per_second": 2.85,
834
+ "step": 550
835
+ },
836
+ {
837
+ "epoch": 7.466666666666667,
838
+ "grad_norm": 4.265935897827148,
839
+ "learning_rate": 1.362962962962963e-05,
840
+ "loss": 1.6241,
841
+ "step": 560
842
+ },
843
+ {
844
+ "epoch": 7.466666666666667,
845
+ "eval_loss": 2.958505630493164,
846
+ "eval_runtime": 43.8614,
847
+ "eval_samples_per_second": 22.799,
848
+ "eval_steps_per_second": 2.85,
849
+ "step": 560
850
+ },
851
+ {
852
+ "epoch": 7.6,
853
+ "grad_norm": 5.025564670562744,
854
+ "learning_rate": 1.2444444444444446e-05,
855
+ "loss": 1.6306,
856
+ "step": 570
857
+ },
858
+ {
859
+ "epoch": 7.6,
860
+ "eval_loss": 2.956601619720459,
861
+ "eval_runtime": 43.8595,
862
+ "eval_samples_per_second": 22.8,
863
+ "eval_steps_per_second": 2.85,
864
+ "step": 570
865
+ },
866
+ {
867
+ "epoch": 7.733333333333333,
868
+ "grad_norm": 4.252591133117676,
869
+ "learning_rate": 1.125925925925926e-05,
870
+ "loss": 1.5933,
871
+ "step": 580
872
+ },
873
+ {
874
+ "epoch": 7.733333333333333,
875
+ "eval_loss": 2.9567930698394775,
876
+ "eval_runtime": 43.8568,
877
+ "eval_samples_per_second": 22.801,
878
+ "eval_steps_per_second": 2.85,
879
+ "step": 580
880
+ },
881
+ {
882
+ "epoch": 7.866666666666667,
883
+ "grad_norm": 4.484741687774658,
884
+ "learning_rate": 1.0192592592592594e-05,
885
+ "loss": 1.6441,
886
+ "step": 590
887
+ },
888
+ {
889
+ "epoch": 7.866666666666667,
890
+ "eval_loss": 2.9549593925476074,
891
+ "eval_runtime": 43.8579,
892
+ "eval_samples_per_second": 22.801,
893
+ "eval_steps_per_second": 2.85,
894
+ "step": 590
895
+ },
896
+ {
897
+ "epoch": 8.0,
898
+ "grad_norm": 4.397695064544678,
899
+ "learning_rate": 9.007407407407408e-06,
900
+ "loss": 1.5878,
901
+ "step": 600
902
+ },
903
+ {
904
+ "epoch": 8.0,
905
+ "eval_loss": 2.948493480682373,
906
+ "eval_runtime": 43.8666,
907
+ "eval_samples_per_second": 22.796,
908
+ "eval_steps_per_second": 2.85,
909
+ "step": 600
910
+ },
911
+ {
912
+ "epoch": 8.133333333333333,
913
+ "grad_norm": 5.092386245727539,
914
+ "learning_rate": 7.822222222222224e-06,
915
+ "loss": 1.5588,
916
+ "step": 610
917
+ },
918
+ {
919
+ "epoch": 8.133333333333333,
920
+ "eval_loss": 2.9865269660949707,
921
+ "eval_runtime": 43.8606,
922
+ "eval_samples_per_second": 22.8,
923
+ "eval_steps_per_second": 2.85,
924
+ "step": 610
925
+ },
926
+ {
927
+ "epoch": 8.266666666666667,
928
+ "grad_norm": 4.463871479034424,
929
+ "learning_rate": 6.637037037037037e-06,
930
+ "loss": 1.5338,
931
+ "step": 620
932
+ },
933
+ {
934
+ "epoch": 8.266666666666667,
935
+ "eval_loss": 3.0131285190582275,
936
+ "eval_runtime": 43.8679,
937
+ "eval_samples_per_second": 22.796,
938
+ "eval_steps_per_second": 2.849,
939
+ "step": 620
940
+ },
941
+ {
942
+ "epoch": 8.4,
943
+ "grad_norm": 4.507328033447266,
944
+ "learning_rate": 5.451851851851853e-06,
945
+ "loss": 1.5481,
946
+ "step": 630
947
+ },
948
+ {
949
+ "epoch": 8.4,
950
+ "eval_loss": 3.003377914428711,
951
+ "eval_runtime": 43.8617,
952
+ "eval_samples_per_second": 22.799,
953
+ "eval_steps_per_second": 2.85,
954
+ "step": 630
955
+ },
956
+ {
957
+ "epoch": 8.533333333333333,
958
+ "grad_norm": 4.37155818939209,
959
+ "learning_rate": 4.266666666666668e-06,
960
+ "loss": 1.5694,
961
+ "step": 640
962
+ },
963
+ {
964
+ "epoch": 8.533333333333333,
965
+ "eval_loss": 2.9983274936676025,
966
+ "eval_runtime": 43.8567,
967
+ "eval_samples_per_second": 22.802,
968
+ "eval_steps_per_second": 2.85,
969
+ "step": 640
970
+ }
971
+ ],
972
+ "logging_steps": 10,
973
+ "max_steps": 675,
974
+ "num_input_tokens_seen": 0,
975
+ "num_train_epochs": 9,
976
+ "save_steps": 10,
977
+ "stateful_callbacks": {
978
+ "TrainerControl": {
979
+ "args": {
980
+ "should_epoch_stop": false,
981
+ "should_evaluate": false,
982
+ "should_log": false,
983
+ "should_save": true,
984
+ "should_training_stop": false
985
+ },
986
+ "attributes": {}
987
+ }
988
+ },
989
+ "total_flos": 1.048708607115264e+17,
990
+ "train_batch_size": 8,
991
+ "trial_name": null,
992
+ "trial_params": null
993
+ }
output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-nonmember-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-650/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/pythia-6_9b
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2