Hugging Face's logo

HydraLM
/
Nous-Hermes-llama-2-7b_7b_cluster029_partitioned_v3_standardized_029

PEFT
Model card Files Community
1
Nous-Hermes-llama-2-7b_7b_cluster029_partitioned_v3_standardized_029
File size: 6,541 Bytes 
c293b8b
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
 
{
  "best_metric": 0.6020743250846863,
  "best_model_checkpoint": "./output_v2/7b_cluster029_Nous-Hermes-llama-2-7b_partitioned_v3_standardized_029/checkpoint-200",
  "epoch": 0.40526849037487334,
  "global_step": 200,
  "is_hyper_param_search": false,
  "is_local_process_zero": true,
  "is_world_process_zero": true,
  "log_history": [
    {
      "epoch": 0.02,
      "learning_rate": 0.0002,
      "loss": 0.6742,
      "step": 10
    },
    {
      "epoch": 0.04,
      "learning_rate": 0.0002,
      "loss": 0.6589,
      "step": 20
    },
    {
      "epoch": 0.06,
      "learning_rate": 0.0002,
      "loss": 0.6439,
      "step": 30
    },
    {
      "epoch": 0.08,
      "learning_rate": 0.0002,
      "loss": 0.611,
      "step": 40
    },
    {
      "epoch": 0.1,
      "learning_rate": 0.0002,
      "loss": 0.6127,
      "step": 50
    },
    {
      "epoch": 0.12,
      "learning_rate": 0.0002,
      "loss": 0.6089,
      "step": 60
    },
    {
      "epoch": 0.14,
      "learning_rate": 0.0002,
      "loss": 0.6102,
      "step": 70
    },
    {
      "epoch": 0.16,
      "learning_rate": 0.0002,
      "loss": 0.5998,
      "step": 80
    },
    {
      "epoch": 0.18,
      "learning_rate": 0.0002,
      "loss": 0.6031,
      "step": 90
    },
    {
      "epoch": 0.2,
      "learning_rate": 0.0002,
      "loss": 0.5942,
      "step": 100
    },
    {
      "epoch": 0.22,
      "learning_rate": 0.0002,
      "loss": 0.6057,
      "step": 110
    },
    {
      "epoch": 0.24,
      "learning_rate": 0.0002,
      "loss": 0.5994,
      "step": 120
    },
    {
      "epoch": 0.26,
      "learning_rate": 0.0002,
      "loss": 0.619,
      "step": 130
    },
    {
      "epoch": 0.28,
      "learning_rate": 0.0002,
      "loss": 0.6001,
      "step": 140
    },
    {
      "epoch": 0.3,
      "learning_rate": 0.0002,
      "loss": 0.6004,
      "step": 150
    },
    {
      "epoch": 0.32,
      "learning_rate": 0.0002,
      "loss": 0.6108,
      "step": 160
    },
    {
      "epoch": 0.34,
      "learning_rate": 0.0002,
      "loss": 0.5893,
      "step": 170
    },
    {
      "epoch": 0.36,
      "learning_rate": 0.0002,
      "loss": 0.5896,
      "step": 180
    },
    {
      "epoch": 0.39,
      "learning_rate": 0.0002,
      "loss": 0.5795,
      "step": 190
    },
    {
      "epoch": 0.41,
      "learning_rate": 0.0002,
      "loss": 0.587,
      "step": 200
    },
    {
      "epoch": 0.41,
      "eval_loss": 0.6020743250846863,
      "eval_runtime": 220.3104,
      "eval_samples_per_second": 4.539,
      "eval_steps_per_second": 2.27,
      "step": 200
    },
    {
      "epoch": 0.41,
      "mmlu_eval_accuracy": 0.4675041957905457,
      "mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
      "mmlu_eval_accuracy_anatomy": 0.5,
      "mmlu_eval_accuracy_astronomy": 0.4375,
      "mmlu_eval_accuracy_business_ethics": 0.6363636363636364,
      "mmlu_eval_accuracy_clinical_knowledge": 0.4482758620689655,
      "mmlu_eval_accuracy_college_biology": 0.4375,
      "mmlu_eval_accuracy_college_chemistry": 0.125,
      "mmlu_eval_accuracy_college_computer_science": 0.36363636363636365,
      "mmlu_eval_accuracy_college_mathematics": 0.18181818181818182,
      "mmlu_eval_accuracy_college_medicine": 0.36363636363636365,
      "mmlu_eval_accuracy_college_physics": 0.45454545454545453,
      "mmlu_eval_accuracy_computer_security": 0.36363636363636365,
      "mmlu_eval_accuracy_conceptual_physics": 0.38461538461538464,
      "mmlu_eval_accuracy_econometrics": 0.16666666666666666,
      "mmlu_eval_accuracy_electrical_engineering": 0.4375,
      "mmlu_eval_accuracy_elementary_mathematics": 0.34146341463414637,
      "mmlu_eval_accuracy_formal_logic": 0.2857142857142857,
      "mmlu_eval_accuracy_global_facts": 0.6,
      "mmlu_eval_accuracy_high_school_biology": 0.34375,
      "mmlu_eval_accuracy_high_school_chemistry": 0.4090909090909091,
      "mmlu_eval_accuracy_high_school_computer_science": 0.7777777777777778,
      "mmlu_eval_accuracy_high_school_european_history": 0.6111111111111112,
      "mmlu_eval_accuracy_high_school_geography": 0.6818181818181818,
      "mmlu_eval_accuracy_high_school_government_and_politics": 0.6666666666666666,
      "mmlu_eval_accuracy_high_school_macroeconomics": 0.3023255813953488,
      "mmlu_eval_accuracy_high_school_mathematics": 0.20689655172413793,
      "mmlu_eval_accuracy_high_school_microeconomics": 0.4230769230769231,
      "mmlu_eval_accuracy_high_school_physics": 0.29411764705882354,
      "mmlu_eval_accuracy_high_school_psychology": 0.7333333333333333,
      "mmlu_eval_accuracy_high_school_statistics": 0.2608695652173913,
      "mmlu_eval_accuracy_high_school_us_history": 0.6818181818181818,
      "mmlu_eval_accuracy_high_school_world_history": 0.5384615384615384,
      "mmlu_eval_accuracy_human_aging": 0.6956521739130435,
      "mmlu_eval_accuracy_human_sexuality": 0.4166666666666667,
      "mmlu_eval_accuracy_international_law": 0.6923076923076923,
      "mmlu_eval_accuracy_jurisprudence": 0.36363636363636365,
      "mmlu_eval_accuracy_logical_fallacies": 0.6111111111111112,
      "mmlu_eval_accuracy_machine_learning": 0.2727272727272727,
      "mmlu_eval_accuracy_management": 0.5454545454545454,
      "mmlu_eval_accuracy_marketing": 0.72,
      "mmlu_eval_accuracy_medical_genetics": 0.7272727272727273,
      "mmlu_eval_accuracy_miscellaneous": 0.6511627906976745,
      "mmlu_eval_accuracy_moral_disputes": 0.47368421052631576,
      "mmlu_eval_accuracy_moral_scenarios": 0.24,
      "mmlu_eval_accuracy_nutrition": 0.6060606060606061,
      "mmlu_eval_accuracy_philosophy": 0.5,
      "mmlu_eval_accuracy_prehistory": 0.45714285714285713,
      "mmlu_eval_accuracy_professional_accounting": 0.2903225806451613,
      "mmlu_eval_accuracy_professional_law": 0.32941176470588235,
      "mmlu_eval_accuracy_professional_medicine": 0.41935483870967744,
      "mmlu_eval_accuracy_professional_psychology": 0.37681159420289856,
      "mmlu_eval_accuracy_public_relations": 0.4166666666666667,
      "mmlu_eval_accuracy_security_studies": 0.5555555555555556,
      "mmlu_eval_accuracy_sociology": 0.6818181818181818,
      "mmlu_eval_accuracy_us_foreign_policy": 0.6363636363636364,
      "mmlu_eval_accuracy_virology": 0.5,
      "mmlu_eval_accuracy_world_religions": 0.7368421052631579,
      "mmlu_loss": 1.169526866031689,
      "step": 200
    }
  ],
  "max_steps": 5000,
  "num_train_epochs": 11,
  "total_flos": 4.887015707226931e+16,
  "trial_name": null,
  "trial_params": null
}