Hugging Face's logo

HydraLM
/
Nous-Hermes-llama-2-7b_7b_cluster011_partitioned_v3_standardized_011

PEFT
Model card Files Community
1
Nous-Hermes-llama-2-7b_7b_cluster011_partitioned_v3_standardized_011
File size: 6,583 Bytes 
3fcfc71
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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": 0.7327473163604736,
  "best_model_checkpoint": "./output_v2/7b_cluster011_Nous-Hermes-llama-2-7b_partitioned_v3_standardized_011/checkpoint-200",
  "epoch": 0.4626951995373048,
  "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": 0.7957,
      "step": 10
    },
    {
      "epoch": 0.05,
      "learning_rate": 0.0002,
      "loss": 0.718,
      "step": 20
    },
    {
      "epoch": 0.07,
      "learning_rate": 0.0002,
      "loss": 0.73,
      "step": 30
    },
    {
      "epoch": 0.09,
      "learning_rate": 0.0002,
      "loss": 0.7826,
      "step": 40
    },
    {
      "epoch": 0.12,
      "learning_rate": 0.0002,
      "loss": 0.7013,
      "step": 50
    },
    {
      "epoch": 0.14,
      "learning_rate": 0.0002,
      "loss": 0.7353,
      "step": 60
    },
    {
      "epoch": 0.16,
      "learning_rate": 0.0002,
      "loss": 0.6666,
      "step": 70
    },
    {
      "epoch": 0.19,
      "learning_rate": 0.0002,
      "loss": 0.7649,
      "step": 80
    },
    {
      "epoch": 0.21,
      "learning_rate": 0.0002,
      "loss": 0.7018,
      "step": 90
    },
    {
      "epoch": 0.23,
      "learning_rate": 0.0002,
      "loss": 0.7173,
      "step": 100
    },
    {
      "epoch": 0.25,
      "learning_rate": 0.0002,
      "loss": 0.7857,
      "step": 110
    },
    {
      "epoch": 0.28,
      "learning_rate": 0.0002,
      "loss": 0.7154,
      "step": 120
    },
    {
      "epoch": 0.3,
      "learning_rate": 0.0002,
      "loss": 0.7485,
      "step": 130
    },
    {
      "epoch": 0.32,
      "learning_rate": 0.0002,
      "loss": 0.7114,
      "step": 140
    },
    {
      "epoch": 0.35,
      "learning_rate": 0.0002,
      "loss": 0.7333,
      "step": 150
    },
    {
      "epoch": 0.37,
      "learning_rate": 0.0002,
      "loss": 0.6549,
      "step": 160
    },
    {
      "epoch": 0.39,
      "learning_rate": 0.0002,
      "loss": 0.6765,
      "step": 170
    },
    {
      "epoch": 0.42,
      "learning_rate": 0.0002,
      "loss": 0.677,
      "step": 180
    },
    {
      "epoch": 0.44,
      "learning_rate": 0.0002,
      "loss": 0.6763,
      "step": 190
    },
    {
      "epoch": 0.46,
      "learning_rate": 0.0002,
      "loss": 0.6638,
      "step": 200
    },
    {
      "epoch": 0.46,
      "eval_loss": 0.7327473163604736,
      "eval_runtime": 246.3779,
      "eval_samples_per_second": 4.059,
      "eval_steps_per_second": 2.029,
      "step": 200
    },
    {
      "epoch": 0.46,
      "mmlu_eval_accuracy": 0.4592376175825003,
      "mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
      "mmlu_eval_accuracy_anatomy": 0.5714285714285714,
      "mmlu_eval_accuracy_astronomy": 0.375,
      "mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
      "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": 0.45454545454545453,
      "mmlu_eval_accuracy_college_mathematics": 0.18181818181818182,
      "mmlu_eval_accuracy_college_medicine": 0.2727272727272727,
      "mmlu_eval_accuracy_college_physics": 0.45454545454545453,
      "mmlu_eval_accuracy_computer_security": 0.36363636363636365,
      "mmlu_eval_accuracy_conceptual_physics": 0.4230769230769231,
      "mmlu_eval_accuracy_econometrics": 0.16666666666666666,
      "mmlu_eval_accuracy_electrical_engineering": 0.4375,
      "mmlu_eval_accuracy_elementary_mathematics": 0.2926829268292683,
      "mmlu_eval_accuracy_formal_logic": 0.2857142857142857,
      "mmlu_eval_accuracy_global_facts": 0.4,
      "mmlu_eval_accuracy_high_school_biology": 0.34375,
      "mmlu_eval_accuracy_high_school_chemistry": 0.4090909090909091,
      "mmlu_eval_accuracy_high_school_computer_science": 0.6666666666666666,
      "mmlu_eval_accuracy_high_school_european_history": 0.5555555555555556,
      "mmlu_eval_accuracy_high_school_geography": 0.7272727272727273,
      "mmlu_eval_accuracy_high_school_government_and_politics": 0.6666666666666666,
      "mmlu_eval_accuracy_high_school_macroeconomics": 0.32558139534883723,
      "mmlu_eval_accuracy_high_school_mathematics": 0.20689655172413793,
      "mmlu_eval_accuracy_high_school_microeconomics": 0.38461538461538464,
      "mmlu_eval_accuracy_high_school_physics": 0.35294117647058826,
      "mmlu_eval_accuracy_high_school_psychology": 0.7333333333333333,
      "mmlu_eval_accuracy_high_school_statistics": 0.391304347826087,
      "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": 0.3333333333333333,
      "mmlu_eval_accuracy_international_law": 0.6923076923076923,
      "mmlu_eval_accuracy_jurisprudence": 0.5454545454545454,
      "mmlu_eval_accuracy_logical_fallacies": 0.5555555555555556,
      "mmlu_eval_accuracy_machine_learning": 0.2727272727272727,
      "mmlu_eval_accuracy_management": 0.6363636363636364,
      "mmlu_eval_accuracy_marketing": 0.72,
      "mmlu_eval_accuracy_medical_genetics": 0.7272727272727273,
      "mmlu_eval_accuracy_miscellaneous": 0.7093023255813954,
      "mmlu_eval_accuracy_moral_disputes": 0.39473684210526316,
      "mmlu_eval_accuracy_moral_scenarios": 0.24,
      "mmlu_eval_accuracy_nutrition": 0.5757575757575758,
      "mmlu_eval_accuracy_philosophy": 0.38235294117647056,
      "mmlu_eval_accuracy_prehistory": 0.45714285714285713,
      "mmlu_eval_accuracy_professional_accounting": 0.2903225806451613,
      "mmlu_eval_accuracy_professional_law": 0.34705882352941175,
      "mmlu_eval_accuracy_professional_medicine": 0.41935483870967744,
      "mmlu_eval_accuracy_professional_psychology": 0.391304347826087,
      "mmlu_eval_accuracy_public_relations": 0.4166666666666667,
      "mmlu_eval_accuracy_security_studies": 0.5185185185185185,
      "mmlu_eval_accuracy_sociology": 0.7272727272727273,
      "mmlu_eval_accuracy_us_foreign_policy": 0.45454545454545453,
      "mmlu_eval_accuracy_virology": 0.4444444444444444,
      "mmlu_eval_accuracy_world_religions": 0.7368421052631579,
      "mmlu_loss": 1.173365458184683,
      "step": 200
    }
  ],
  "max_steps": 5000,
  "num_train_epochs": 12,
  "total_flos": 5.784949765973606e+16,
  "trial_name": null,
  "trial_params": null
}