sheepy928 commited on
Commit
84ebab7
1 Parent(s): 4aec5e5

Upload 12 files

Browse files
added_tokens.json ADDED
@@ -0,0 +1,6 @@
 
 
 
 
 
 
 
1
+ {
2
+ "[CLS]": 2900,
3
+ "[MASK]": 2901,
4
+ "[PAD]": 2899,
5
+ "[SEP]": 2898
6
+ }
config.json ADDED
@@ -0,0 +1,130 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "../../save/jtrans/models/jTrans-pretrain/",
3
+ "architectures": [
4
+ "JTransForMultipleSequenceClassification"
5
+ ],
6
+ "attention_probs_dropout_prob": 0.1,
7
+ "classifier_dropout": null,
8
+ "hidden_act": "gelu",
9
+ "hidden_dropout_prob": 0.1,
10
+ "hidden_size": 768,
11
+ "id2label": {
12
+ "0": "liewar",
13
+ "1": "tspy",
14
+ "2": "doina",
15
+ "3": "zxproxy",
16
+ "4": "lazy",
17
+ "5": "mint",
18
+ "6": "fugrafa",
19
+ "7": "midie",
20
+ "8": "flawedammyy",
21
+ "9": "plugx",
22
+ "10": "poison",
23
+ "11": "barys",
24
+ "12": "nettool",
25
+ "13": "cometer",
26
+ "14": "strongpity",
27
+ "15": "symmi",
28
+ "16": "bkdr",
29
+ "17": "msil",
30
+ "18": "rootkit",
31
+ "19": "ulise",
32
+ "20": "jaik",
33
+ "21": "fareit",
34
+ "22": "brambul",
35
+ "23": "graftor",
36
+ "24": "korplug",
37
+ "25": "agentb",
38
+ "26": "zusy",
39
+ "27": "startpage",
40
+ "28": "scar",
41
+ "29": "mikey",
42
+ "30": "casdet",
43
+ "31": "genome",
44
+ "32": "salgorea",
45
+ "33": "fraudload",
46
+ "34": "oceanlotus",
47
+ "35": "winnti",
48
+ "36": "pepex",
49
+ "37": "mokead",
50
+ "38": "razy",
51
+ "39": "ursu",
52
+ "40": "apost",
53
+ "41": "sednit",
54
+ "42": "rafdy",
55
+ "43": "filerepmalware",
56
+ "44": "meciv",
57
+ "45": "travnet",
58
+ "46": "turla",
59
+ "47": "miniduke",
60
+ "48": "zoxpng",
61
+ "49": "bulz"
62
+ },
63
+ "initializer_range": 0.02,
64
+ "intermediate_size": 3072,
65
+ "label2id": {
66
+ "agentb": 25,
67
+ "apost": 40,
68
+ "barys": 11,
69
+ "bkdr": 16,
70
+ "brambul": 22,
71
+ "bulz": 49,
72
+ "casdet": 30,
73
+ "cometer": 13,
74
+ "doina": 2,
75
+ "fareit": 21,
76
+ "filerepmalware": 43,
77
+ "flawedammyy": 8,
78
+ "fraudload": 33,
79
+ "fugrafa": 6,
80
+ "genome": 31,
81
+ "graftor": 23,
82
+ "jaik": 20,
83
+ "korplug": 24,
84
+ "lazy": 4,
85
+ "liewar": 0,
86
+ "meciv": 44,
87
+ "midie": 7,
88
+ "mikey": 29,
89
+ "miniduke": 47,
90
+ "mint": 5,
91
+ "mokead": 37,
92
+ "msil": 17,
93
+ "nettool": 12,
94
+ "oceanlotus": 34,
95
+ "pepex": 36,
96
+ "plugx": 9,
97
+ "poison": 10,
98
+ "rafdy": 42,
99
+ "razy": 38,
100
+ "rootkit": 18,
101
+ "salgorea": 32,
102
+ "scar": 28,
103
+ "sednit": 41,
104
+ "startpage": 27,
105
+ "strongpity": 14,
106
+ "symmi": 15,
107
+ "travnet": 45,
108
+ "tspy": 1,
109
+ "turla": 46,
110
+ "ulise": 19,
111
+ "ursu": 39,
112
+ "winnti": 35,
113
+ "zoxpng": 48,
114
+ "zusy": 26,
115
+ "zxproxy": 3
116
+ },
117
+ "layer_norm_eps": 1e-12,
118
+ "max_position_embeddings": 512,
119
+ "model_type": "bert",
120
+ "num_attention_heads": 12,
121
+ "num_hidden_layers": 12,
122
+ "pad_token_id": 0,
123
+ "position_embedding_type": "absolute",
124
+ "problem_type": "multi_label_classification",
125
+ "torch_dtype": "float32",
126
+ "transformers_version": "4.30.1",
127
+ "type_vocab_size": 2,
128
+ "use_cache": true,
129
+ "vocab_size": 2902
130
+ }
optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:714fe67a3cf013692aadf718df7e63ce9fb6ecb899b78b26677938d14bc5ade6
3
+ size 703446533
pytorch_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:2df7037e5c2b9ce46d9cac38b4c1e7d01c1faa963984424928a442e23491ea28
3
+ size 354100285
rng_state_0.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:cbf29dea18da364b662a05a0959a9b02d231b9943f7dba02c062251f781ad152
3
+ size 15607
rng_state_1.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:055ac9ef1ed05e7138ff0e56dc6407e2c233c9104c43a8f631b6ac99cffa3b4c
3
+ size 15607
scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e092d13c4c772dae461cc1973e98d9bd64c0e2d9324a26389ecab981b9043e53
3
+ size 627
special_tokens_map.json ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ {
2
+ "cls_token": "[CLS]",
3
+ "mask_token": "[MASK]",
4
+ "pad_token": "[PAD]",
5
+ "sep_token": "[SEP]",
6
+ "unk_token": "[UNK]"
7
+ }
tokenizer_config.json ADDED
@@ -0,0 +1,16 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "clean_up_tokenization_spaces": true,
3
+ "cls_token": "[CLS]",
4
+ "do_basic_tokenize": false,
5
+ "do_lower_case": false,
6
+ "mask_token": "[MASK]",
7
+ "model_max_length": 1000000000000000019884624838656,
8
+ "never_split": null,
9
+ "pad_token": "[PAD]",
10
+ "sep_token": "[SEP]",
11
+ "strip_accents": null,
12
+ "tokenize_chinese_chars": true,
13
+ "tokenizer_class": "BertTokenizer",
14
+ "tokenizer_file": null,
15
+ "unk_token": "[UNK]"
16
+ }
trainer_state.json ADDED
@@ -0,0 +1,2536 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 0.4437299035369775,
3
+ "best_model_checkpoint": "../save/jtrans-malware/checkpoint-3000",
4
+ "epoch": 9.043927648578812,
5
+ "global_step": 3500,
6
+ "is_hyper_param_search": false,
7
+ "is_local_process_zero": true,
8
+ "is_world_process_zero": true,
9
+ "log_history": [
10
+ {
11
+ "epoch": 0.03,
12
+ "learning_rate": 9.974160206718347e-05,
13
+ "loss": 0.434,
14
+ "step": 10
15
+ },
16
+ {
17
+ "epoch": 0.05,
18
+ "learning_rate": 9.948320413436693e-05,
19
+ "loss": 0.222,
20
+ "step": 20
21
+ },
22
+ {
23
+ "epoch": 0.08,
24
+ "learning_rate": 9.92248062015504e-05,
25
+ "loss": 0.1538,
26
+ "step": 30
27
+ },
28
+ {
29
+ "epoch": 0.1,
30
+ "learning_rate": 9.896640826873386e-05,
31
+ "loss": 0.1393,
32
+ "step": 40
33
+ },
34
+ {
35
+ "epoch": 0.13,
36
+ "learning_rate": 9.870801033591732e-05,
37
+ "loss": 0.1326,
38
+ "step": 50
39
+ },
40
+ {
41
+ "epoch": 0.16,
42
+ "learning_rate": 9.844961240310078e-05,
43
+ "loss": 0.1337,
44
+ "step": 60
45
+ },
46
+ {
47
+ "epoch": 0.18,
48
+ "learning_rate": 9.819121447028425e-05,
49
+ "loss": 0.1312,
50
+ "step": 70
51
+ },
52
+ {
53
+ "epoch": 0.21,
54
+ "learning_rate": 9.793281653746771e-05,
55
+ "loss": 0.1239,
56
+ "step": 80
57
+ },
58
+ {
59
+ "epoch": 0.23,
60
+ "learning_rate": 9.767441860465116e-05,
61
+ "loss": 0.1261,
62
+ "step": 90
63
+ },
64
+ {
65
+ "epoch": 0.26,
66
+ "learning_rate": 9.741602067183462e-05,
67
+ "loss": 0.1246,
68
+ "step": 100
69
+ },
70
+ {
71
+ "epoch": 0.26,
72
+ "eval_accuracy": 0.9733742331288343,
73
+ "eval_f1": 0.09958506224066391,
74
+ "eval_loss": 0.13609381020069122,
75
+ "eval_precision": 0.9230769230769231,
76
+ "eval_recall": 0.05263157894736842,
77
+ "eval_runtime": 11.6719,
78
+ "eval_samples_per_second": 13.965,
79
+ "eval_steps_per_second": 0.942,
80
+ "step": 100
81
+ },
82
+ {
83
+ "epoch": 0.28,
84
+ "learning_rate": 9.71576227390181e-05,
85
+ "loss": 0.1192,
86
+ "step": 110
87
+ },
88
+ {
89
+ "epoch": 0.31,
90
+ "learning_rate": 9.689922480620155e-05,
91
+ "loss": 0.1341,
92
+ "step": 120
93
+ },
94
+ {
95
+ "epoch": 0.34,
96
+ "learning_rate": 9.664082687338501e-05,
97
+ "loss": 0.1231,
98
+ "step": 130
99
+ },
100
+ {
101
+ "epoch": 0.36,
102
+ "learning_rate": 9.638242894056848e-05,
103
+ "loss": 0.1399,
104
+ "step": 140
105
+ },
106
+ {
107
+ "epoch": 0.39,
108
+ "learning_rate": 9.612403100775195e-05,
109
+ "loss": 0.1262,
110
+ "step": 150
111
+ },
112
+ {
113
+ "epoch": 0.41,
114
+ "learning_rate": 9.58656330749354e-05,
115
+ "loss": 0.133,
116
+ "step": 160
117
+ },
118
+ {
119
+ "epoch": 0.44,
120
+ "learning_rate": 9.560723514211886e-05,
121
+ "loss": 0.1247,
122
+ "step": 170
123
+ },
124
+ {
125
+ "epoch": 0.47,
126
+ "learning_rate": 9.534883720930233e-05,
127
+ "loss": 0.129,
128
+ "step": 180
129
+ },
130
+ {
131
+ "epoch": 0.49,
132
+ "learning_rate": 9.509043927648579e-05,
133
+ "loss": 0.1275,
134
+ "step": 190
135
+ },
136
+ {
137
+ "epoch": 0.52,
138
+ "learning_rate": 9.483204134366925e-05,
139
+ "loss": 0.1267,
140
+ "step": 200
141
+ },
142
+ {
143
+ "epoch": 0.52,
144
+ "eval_accuracy": 0.9720245398773006,
145
+ "eval_f1": 0.0,
146
+ "eval_loss": 0.12009111791849136,
147
+ "eval_precision": 0.0,
148
+ "eval_recall": 0.0,
149
+ "eval_runtime": 11.6034,
150
+ "eval_samples_per_second": 14.048,
151
+ "eval_steps_per_second": 0.948,
152
+ "step": 200
153
+ },
154
+ {
155
+ "epoch": 0.54,
156
+ "learning_rate": 9.457364341085272e-05,
157
+ "loss": 0.1257,
158
+ "step": 210
159
+ },
160
+ {
161
+ "epoch": 0.57,
162
+ "learning_rate": 9.431524547803618e-05,
163
+ "loss": 0.121,
164
+ "step": 220
165
+ },
166
+ {
167
+ "epoch": 0.59,
168
+ "learning_rate": 9.405684754521964e-05,
169
+ "loss": 0.1238,
170
+ "step": 230
171
+ },
172
+ {
173
+ "epoch": 0.62,
174
+ "learning_rate": 9.379844961240311e-05,
175
+ "loss": 0.1284,
176
+ "step": 240
177
+ },
178
+ {
179
+ "epoch": 0.65,
180
+ "learning_rate": 9.354005167958657e-05,
181
+ "loss": 0.1206,
182
+ "step": 250
183
+ },
184
+ {
185
+ "epoch": 0.67,
186
+ "learning_rate": 9.328165374677002e-05,
187
+ "loss": 0.1288,
188
+ "step": 260
189
+ },
190
+ {
191
+ "epoch": 0.7,
192
+ "learning_rate": 9.30232558139535e-05,
193
+ "loss": 0.1151,
194
+ "step": 270
195
+ },
196
+ {
197
+ "epoch": 0.72,
198
+ "learning_rate": 9.276485788113696e-05,
199
+ "loss": 0.1144,
200
+ "step": 280
201
+ },
202
+ {
203
+ "epoch": 0.75,
204
+ "learning_rate": 9.250645994832042e-05,
205
+ "loss": 0.13,
206
+ "step": 290
207
+ },
208
+ {
209
+ "epoch": 0.78,
210
+ "learning_rate": 9.224806201550387e-05,
211
+ "loss": 0.1202,
212
+ "step": 300
213
+ },
214
+ {
215
+ "epoch": 0.78,
216
+ "eval_accuracy": 0.9734969325153374,
217
+ "eval_f1": 0.10743801652892561,
218
+ "eval_loss": 0.11869814246892929,
219
+ "eval_precision": 0.9285714285714286,
220
+ "eval_recall": 0.05701754385964912,
221
+ "eval_runtime": 11.8735,
222
+ "eval_samples_per_second": 13.728,
223
+ "eval_steps_per_second": 0.926,
224
+ "step": 300
225
+ },
226
+ {
227
+ "epoch": 0.8,
228
+ "learning_rate": 9.198966408268735e-05,
229
+ "loss": 0.1218,
230
+ "step": 310
231
+ },
232
+ {
233
+ "epoch": 0.83,
234
+ "learning_rate": 9.173126614987081e-05,
235
+ "loss": 0.1218,
236
+ "step": 320
237
+ },
238
+ {
239
+ "epoch": 0.85,
240
+ "learning_rate": 9.147286821705426e-05,
241
+ "loss": 0.1197,
242
+ "step": 330
243
+ },
244
+ {
245
+ "epoch": 0.88,
246
+ "learning_rate": 9.121447028423772e-05,
247
+ "loss": 0.1221,
248
+ "step": 340
249
+ },
250
+ {
251
+ "epoch": 0.9,
252
+ "learning_rate": 9.09560723514212e-05,
253
+ "loss": 0.1223,
254
+ "step": 350
255
+ },
256
+ {
257
+ "epoch": 0.93,
258
+ "learning_rate": 9.069767441860465e-05,
259
+ "loss": 0.12,
260
+ "step": 360
261
+ },
262
+ {
263
+ "epoch": 0.96,
264
+ "learning_rate": 9.043927648578811e-05,
265
+ "loss": 0.1113,
266
+ "step": 370
267
+ },
268
+ {
269
+ "epoch": 0.98,
270
+ "learning_rate": 9.018087855297158e-05,
271
+ "loss": 0.121,
272
+ "step": 380
273
+ },
274
+ {
275
+ "epoch": 1.01,
276
+ "learning_rate": 8.992248062015505e-05,
277
+ "loss": 0.1195,
278
+ "step": 390
279
+ },
280
+ {
281
+ "epoch": 1.03,
282
+ "learning_rate": 8.96640826873385e-05,
283
+ "loss": 0.1227,
284
+ "step": 400
285
+ },
286
+ {
287
+ "epoch": 1.03,
288
+ "eval_accuracy": 0.9734969325153374,
289
+ "eval_f1": 0.10743801652892561,
290
+ "eval_loss": 0.11648325622081757,
291
+ "eval_precision": 0.9285714285714286,
292
+ "eval_recall": 0.05701754385964912,
293
+ "eval_runtime": 11.6629,
294
+ "eval_samples_per_second": 13.976,
295
+ "eval_steps_per_second": 0.943,
296
+ "step": 400
297
+ },
298
+ {
299
+ "epoch": 1.06,
300
+ "learning_rate": 8.940568475452197e-05,
301
+ "loss": 0.118,
302
+ "step": 410
303
+ },
304
+ {
305
+ "epoch": 1.09,
306
+ "learning_rate": 8.914728682170543e-05,
307
+ "loss": 0.12,
308
+ "step": 420
309
+ },
310
+ {
311
+ "epoch": 1.11,
312
+ "learning_rate": 8.888888888888889e-05,
313
+ "loss": 0.1223,
314
+ "step": 430
315
+ },
316
+ {
317
+ "epoch": 1.14,
318
+ "learning_rate": 8.863049095607236e-05,
319
+ "loss": 0.1154,
320
+ "step": 440
321
+ },
322
+ {
323
+ "epoch": 1.16,
324
+ "learning_rate": 8.837209302325582e-05,
325
+ "loss": 0.1124,
326
+ "step": 450
327
+ },
328
+ {
329
+ "epoch": 1.19,
330
+ "learning_rate": 8.811369509043928e-05,
331
+ "loss": 0.1095,
332
+ "step": 460
333
+ },
334
+ {
335
+ "epoch": 1.21,
336
+ "learning_rate": 8.785529715762275e-05,
337
+ "loss": 0.1159,
338
+ "step": 470
339
+ },
340
+ {
341
+ "epoch": 1.24,
342
+ "learning_rate": 8.759689922480621e-05,
343
+ "loss": 0.1229,
344
+ "step": 480
345
+ },
346
+ {
347
+ "epoch": 1.27,
348
+ "learning_rate": 8.733850129198967e-05,
349
+ "loss": 0.1185,
350
+ "step": 490
351
+ },
352
+ {
353
+ "epoch": 1.29,
354
+ "learning_rate": 8.708010335917312e-05,
355
+ "loss": 0.1139,
356
+ "step": 500
357
+ },
358
+ {
359
+ "epoch": 1.29,
360
+ "eval_accuracy": 0.9734969325153374,
361
+ "eval_f1": 0.10743801652892561,
362
+ "eval_loss": 0.11325845867395401,
363
+ "eval_precision": 0.9285714285714286,
364
+ "eval_recall": 0.05701754385964912,
365
+ "eval_runtime": 11.9509,
366
+ "eval_samples_per_second": 13.639,
367
+ "eval_steps_per_second": 0.92,
368
+ "step": 500
369
+ },
370
+ {
371
+ "epoch": 1.32,
372
+ "learning_rate": 8.68217054263566e-05,
373
+ "loss": 0.1167,
374
+ "step": 510
375
+ },
376
+ {
377
+ "epoch": 1.34,
378
+ "learning_rate": 8.656330749354006e-05,
379
+ "loss": 0.119,
380
+ "step": 520
381
+ },
382
+ {
383
+ "epoch": 1.37,
384
+ "learning_rate": 8.630490956072352e-05,
385
+ "loss": 0.1115,
386
+ "step": 530
387
+ },
388
+ {
389
+ "epoch": 1.4,
390
+ "learning_rate": 8.604651162790697e-05,
391
+ "loss": 0.1108,
392
+ "step": 540
393
+ },
394
+ {
395
+ "epoch": 1.42,
396
+ "learning_rate": 8.578811369509044e-05,
397
+ "loss": 0.1194,
398
+ "step": 550
399
+ },
400
+ {
401
+ "epoch": 1.45,
402
+ "learning_rate": 8.552971576227391e-05,
403
+ "loss": 0.1147,
404
+ "step": 560
405
+ },
406
+ {
407
+ "epoch": 1.47,
408
+ "learning_rate": 8.527131782945736e-05,
409
+ "loss": 0.1171,
410
+ "step": 570
411
+ },
412
+ {
413
+ "epoch": 1.5,
414
+ "learning_rate": 8.501291989664083e-05,
415
+ "loss": 0.1218,
416
+ "step": 580
417
+ },
418
+ {
419
+ "epoch": 1.52,
420
+ "learning_rate": 8.475452196382429e-05,
421
+ "loss": 0.1211,
422
+ "step": 590
423
+ },
424
+ {
425
+ "epoch": 1.55,
426
+ "learning_rate": 8.449612403100775e-05,
427
+ "loss": 0.1102,
428
+ "step": 600
429
+ },
430
+ {
431
+ "epoch": 1.55,
432
+ "eval_accuracy": 0.9734969325153374,
433
+ "eval_f1": 0.10743801652892561,
434
+ "eval_loss": 0.10692530870437622,
435
+ "eval_precision": 0.9285714285714286,
436
+ "eval_recall": 0.05701754385964912,
437
+ "eval_runtime": 11.9673,
438
+ "eval_samples_per_second": 13.62,
439
+ "eval_steps_per_second": 0.919,
440
+ "step": 600
441
+ },
442
+ {
443
+ "epoch": 1.58,
444
+ "learning_rate": 8.423772609819122e-05,
445
+ "loss": 0.1061,
446
+ "step": 610
447
+ },
448
+ {
449
+ "epoch": 1.6,
450
+ "learning_rate": 8.397932816537468e-05,
451
+ "loss": 0.1062,
452
+ "step": 620
453
+ },
454
+ {
455
+ "epoch": 1.63,
456
+ "learning_rate": 8.372093023255814e-05,
457
+ "loss": 0.1148,
458
+ "step": 630
459
+ },
460
+ {
461
+ "epoch": 1.65,
462
+ "learning_rate": 8.34625322997416e-05,
463
+ "loss": 0.1114,
464
+ "step": 640
465
+ },
466
+ {
467
+ "epoch": 1.68,
468
+ "learning_rate": 8.320413436692507e-05,
469
+ "loss": 0.1117,
470
+ "step": 650
471
+ },
472
+ {
473
+ "epoch": 1.71,
474
+ "learning_rate": 8.294573643410853e-05,
475
+ "loss": 0.109,
476
+ "step": 660
477
+ },
478
+ {
479
+ "epoch": 1.73,
480
+ "learning_rate": 8.2687338501292e-05,
481
+ "loss": 0.1042,
482
+ "step": 670
483
+ },
484
+ {
485
+ "epoch": 1.76,
486
+ "learning_rate": 8.242894056847546e-05,
487
+ "loss": 0.1153,
488
+ "step": 680
489
+ },
490
+ {
491
+ "epoch": 1.78,
492
+ "learning_rate": 8.217054263565892e-05,
493
+ "loss": 0.1026,
494
+ "step": 690
495
+ },
496
+ {
497
+ "epoch": 1.81,
498
+ "learning_rate": 8.191214470284238e-05,
499
+ "loss": 0.1102,
500
+ "step": 700
501
+ },
502
+ {
503
+ "epoch": 1.81,
504
+ "eval_accuracy": 0.9734969325153374,
505
+ "eval_f1": 0.10743801652892561,
506
+ "eval_loss": 0.10341155529022217,
507
+ "eval_precision": 0.9285714285714286,
508
+ "eval_recall": 0.05701754385964912,
509
+ "eval_runtime": 11.7838,
510
+ "eval_samples_per_second": 13.833,
511
+ "eval_steps_per_second": 0.933,
512
+ "step": 700
513
+ },
514
+ {
515
+ "epoch": 1.83,
516
+ "learning_rate": 8.165374677002583e-05,
517
+ "loss": 0.1002,
518
+ "step": 710
519
+ },
520
+ {
521
+ "epoch": 1.86,
522
+ "learning_rate": 8.139534883720931e-05,
523
+ "loss": 0.1159,
524
+ "step": 720
525
+ },
526
+ {
527
+ "epoch": 1.89,
528
+ "learning_rate": 8.113695090439277e-05,
529
+ "loss": 0.1098,
530
+ "step": 730
531
+ },
532
+ {
533
+ "epoch": 1.91,
534
+ "learning_rate": 8.087855297157622e-05,
535
+ "loss": 0.1057,
536
+ "step": 740
537
+ },
538
+ {
539
+ "epoch": 1.94,
540
+ "learning_rate": 8.062015503875969e-05,
541
+ "loss": 0.1024,
542
+ "step": 750
543
+ },
544
+ {
545
+ "epoch": 1.96,
546
+ "learning_rate": 8.036175710594316e-05,
547
+ "loss": 0.1013,
548
+ "step": 760
549
+ },
550
+ {
551
+ "epoch": 1.99,
552
+ "learning_rate": 8.010335917312663e-05,
553
+ "loss": 0.0976,
554
+ "step": 770
555
+ },
556
+ {
557
+ "epoch": 2.02,
558
+ "learning_rate": 7.984496124031008e-05,
559
+ "loss": 0.1043,
560
+ "step": 780
561
+ },
562
+ {
563
+ "epoch": 2.04,
564
+ "learning_rate": 7.958656330749354e-05,
565
+ "loss": 0.1005,
566
+ "step": 790
567
+ },
568
+ {
569
+ "epoch": 2.07,
570
+ "learning_rate": 7.932816537467702e-05,
571
+ "loss": 0.0986,
572
+ "step": 800
573
+ },
574
+ {
575
+ "epoch": 2.07,
576
+ "eval_accuracy": 0.9738650306748466,
577
+ "eval_f1": 0.13061224489795917,
578
+ "eval_loss": 0.10085967928171158,
579
+ "eval_precision": 0.9411764705882353,
580
+ "eval_recall": 0.07017543859649122,
581
+ "eval_runtime": 11.946,
582
+ "eval_samples_per_second": 13.645,
583
+ "eval_steps_per_second": 0.921,
584
+ "step": 800
585
+ },
586
+ {
587
+ "epoch": 2.09,
588
+ "learning_rate": 7.906976744186047e-05,
589
+ "loss": 0.0978,
590
+ "step": 810
591
+ },
592
+ {
593
+ "epoch": 2.12,
594
+ "learning_rate": 7.881136950904393e-05,
595
+ "loss": 0.0943,
596
+ "step": 820
597
+ },
598
+ {
599
+ "epoch": 2.14,
600
+ "learning_rate": 7.855297157622739e-05,
601
+ "loss": 0.0916,
602
+ "step": 830
603
+ },
604
+ {
605
+ "epoch": 2.17,
606
+ "learning_rate": 7.829457364341086e-05,
607
+ "loss": 0.1007,
608
+ "step": 840
609
+ },
610
+ {
611
+ "epoch": 2.2,
612
+ "learning_rate": 7.803617571059432e-05,
613
+ "loss": 0.1053,
614
+ "step": 850
615
+ },
616
+ {
617
+ "epoch": 2.22,
618
+ "learning_rate": 7.777777777777778e-05,
619
+ "loss": 0.0992,
620
+ "step": 860
621
+ },
622
+ {
623
+ "epoch": 2.25,
624
+ "learning_rate": 7.751937984496124e-05,
625
+ "loss": 0.1038,
626
+ "step": 870
627
+ },
628
+ {
629
+ "epoch": 2.27,
630
+ "learning_rate": 7.726098191214471e-05,
631
+ "loss": 0.0982,
632
+ "step": 880
633
+ },
634
+ {
635
+ "epoch": 2.3,
636
+ "learning_rate": 7.700258397932817e-05,
637
+ "loss": 0.1031,
638
+ "step": 890
639
+ },
640
+ {
641
+ "epoch": 2.33,
642
+ "learning_rate": 7.674418604651163e-05,
643
+ "loss": 0.0964,
644
+ "step": 900
645
+ },
646
+ {
647
+ "epoch": 2.33,
648
+ "eval_accuracy": 0.9749693251533742,
649
+ "eval_f1": 0.20930232558139536,
650
+ "eval_loss": 0.09663821756839752,
651
+ "eval_precision": 0.9,
652
+ "eval_recall": 0.11842105263157894,
653
+ "eval_runtime": 11.6402,
654
+ "eval_samples_per_second": 14.003,
655
+ "eval_steps_per_second": 0.945,
656
+ "step": 900
657
+ },
658
+ {
659
+ "epoch": 2.35,
660
+ "learning_rate": 7.648578811369508e-05,
661
+ "loss": 0.0991,
662
+ "step": 910
663
+ },
664
+ {
665
+ "epoch": 2.38,
666
+ "learning_rate": 7.622739018087856e-05,
667
+ "loss": 0.0971,
668
+ "step": 920
669
+ },
670
+ {
671
+ "epoch": 2.4,
672
+ "learning_rate": 7.596899224806202e-05,
673
+ "loss": 0.093,
674
+ "step": 930
675
+ },
676
+ {
677
+ "epoch": 2.43,
678
+ "learning_rate": 7.571059431524549e-05,
679
+ "loss": 0.0965,
680
+ "step": 940
681
+ },
682
+ {
683
+ "epoch": 2.45,
684
+ "learning_rate": 7.545219638242894e-05,
685
+ "loss": 0.0949,
686
+ "step": 950
687
+ },
688
+ {
689
+ "epoch": 2.48,
690
+ "learning_rate": 7.519379844961241e-05,
691
+ "loss": 0.0941,
692
+ "step": 960
693
+ },
694
+ {
695
+ "epoch": 2.51,
696
+ "learning_rate": 7.493540051679588e-05,
697
+ "loss": 0.0985,
698
+ "step": 970
699
+ },
700
+ {
701
+ "epoch": 2.53,
702
+ "learning_rate": 7.467700258397933e-05,
703
+ "loss": 0.0999,
704
+ "step": 980
705
+ },
706
+ {
707
+ "epoch": 2.56,
708
+ "learning_rate": 7.441860465116279e-05,
709
+ "loss": 0.1096,
710
+ "step": 990
711
+ },
712
+ {
713
+ "epoch": 2.58,
714
+ "learning_rate": 7.416020671834627e-05,
715
+ "loss": 0.0994,
716
+ "step": 1000
717
+ },
718
+ {
719
+ "epoch": 2.58,
720
+ "eval_accuracy": 0.9750920245398773,
721
+ "eval_f1": 0.20392156862745098,
722
+ "eval_loss": 0.094399094581604,
723
+ "eval_precision": 0.9629629629629629,
724
+ "eval_recall": 0.11403508771929824,
725
+ "eval_runtime": 11.5607,
726
+ "eval_samples_per_second": 14.1,
727
+ "eval_steps_per_second": 0.952,
728
+ "step": 1000
729
+ },
730
+ {
731
+ "epoch": 2.61,
732
+ "learning_rate": 7.390180878552973e-05,
733
+ "loss": 0.1052,
734
+ "step": 1010
735
+ },
736
+ {
737
+ "epoch": 2.64,
738
+ "learning_rate": 7.364341085271318e-05,
739
+ "loss": 0.0974,
740
+ "step": 1020
741
+ },
742
+ {
743
+ "epoch": 2.66,
744
+ "learning_rate": 7.338501291989664e-05,
745
+ "loss": 0.099,
746
+ "step": 1030
747
+ },
748
+ {
749
+ "epoch": 2.69,
750
+ "learning_rate": 7.31266149870801e-05,
751
+ "loss": 0.0999,
752
+ "step": 1040
753
+ },
754
+ {
755
+ "epoch": 2.71,
756
+ "learning_rate": 7.286821705426357e-05,
757
+ "loss": 0.1039,
758
+ "step": 1050
759
+ },
760
+ {
761
+ "epoch": 2.74,
762
+ "learning_rate": 7.260981912144703e-05,
763
+ "loss": 0.0935,
764
+ "step": 1060
765
+ },
766
+ {
767
+ "epoch": 2.76,
768
+ "learning_rate": 7.23514211886305e-05,
769
+ "loss": 0.1,
770
+ "step": 1070
771
+ },
772
+ {
773
+ "epoch": 2.79,
774
+ "learning_rate": 7.209302325581396e-05,
775
+ "loss": 0.0921,
776
+ "step": 1080
777
+ },
778
+ {
779
+ "epoch": 2.82,
780
+ "learning_rate": 7.183462532299742e-05,
781
+ "loss": 0.0941,
782
+ "step": 1090
783
+ },
784
+ {
785
+ "epoch": 2.84,
786
+ "learning_rate": 7.157622739018088e-05,
787
+ "loss": 0.0913,
788
+ "step": 1100
789
+ },
790
+ {
791
+ "epoch": 2.84,
792
+ "eval_accuracy": 0.9757055214723926,
793
+ "eval_f1": 0.23846153846153845,
794
+ "eval_loss": 0.09476516395807266,
795
+ "eval_precision": 0.96875,
796
+ "eval_recall": 0.13596491228070176,
797
+ "eval_runtime": 11.7524,
798
+ "eval_samples_per_second": 13.87,
799
+ "eval_steps_per_second": 0.936,
800
+ "step": 1100
801
+ },
802
+ {
803
+ "epoch": 2.87,
804
+ "learning_rate": 7.131782945736435e-05,
805
+ "loss": 0.0944,
806
+ "step": 1110
807
+ },
808
+ {
809
+ "epoch": 2.89,
810
+ "learning_rate": 7.105943152454781e-05,
811
+ "loss": 0.0946,
812
+ "step": 1120
813
+ },
814
+ {
815
+ "epoch": 2.92,
816
+ "learning_rate": 7.080103359173127e-05,
817
+ "loss": 0.0842,
818
+ "step": 1130
819
+ },
820
+ {
821
+ "epoch": 2.95,
822
+ "learning_rate": 7.054263565891474e-05,
823
+ "loss": 0.0896,
824
+ "step": 1140
825
+ },
826
+ {
827
+ "epoch": 2.97,
828
+ "learning_rate": 7.028423772609819e-05,
829
+ "loss": 0.0977,
830
+ "step": 1150
831
+ },
832
+ {
833
+ "epoch": 3.0,
834
+ "learning_rate": 7.002583979328165e-05,
835
+ "loss": 0.1078,
836
+ "step": 1160
837
+ },
838
+ {
839
+ "epoch": 3.02,
840
+ "learning_rate": 6.976744186046513e-05,
841
+ "loss": 0.0854,
842
+ "step": 1170
843
+ },
844
+ {
845
+ "epoch": 3.05,
846
+ "learning_rate": 6.950904392764859e-05,
847
+ "loss": 0.0872,
848
+ "step": 1180
849
+ },
850
+ {
851
+ "epoch": 3.07,
852
+ "learning_rate": 6.925064599483204e-05,
853
+ "loss": 0.1017,
854
+ "step": 1190
855
+ },
856
+ {
857
+ "epoch": 3.1,
858
+ "learning_rate": 6.89922480620155e-05,
859
+ "loss": 0.0964,
860
+ "step": 1200
861
+ },
862
+ {
863
+ "epoch": 3.1,
864
+ "eval_accuracy": 0.9737423312883435,
865
+ "eval_f1": 0.2014925373134328,
866
+ "eval_loss": 0.09359467029571533,
867
+ "eval_precision": 0.675,
868
+ "eval_recall": 0.11842105263157894,
869
+ "eval_runtime": 11.5484,
870
+ "eval_samples_per_second": 14.115,
871
+ "eval_steps_per_second": 0.953,
872
+ "step": 1200
873
+ },
874
+ {
875
+ "epoch": 3.13,
876
+ "learning_rate": 6.873385012919898e-05,
877
+ "loss": 0.092,
878
+ "step": 1210
879
+ },
880
+ {
881
+ "epoch": 3.15,
882
+ "learning_rate": 6.847545219638243e-05,
883
+ "loss": 0.0919,
884
+ "step": 1220
885
+ },
886
+ {
887
+ "epoch": 3.18,
888
+ "learning_rate": 6.821705426356589e-05,
889
+ "loss": 0.0872,
890
+ "step": 1230
891
+ },
892
+ {
893
+ "epoch": 3.2,
894
+ "learning_rate": 6.795865633074935e-05,
895
+ "loss": 0.0822,
896
+ "step": 1240
897
+ },
898
+ {
899
+ "epoch": 3.23,
900
+ "learning_rate": 6.770025839793283e-05,
901
+ "loss": 0.0931,
902
+ "step": 1250
903
+ },
904
+ {
905
+ "epoch": 3.26,
906
+ "learning_rate": 6.744186046511628e-05,
907
+ "loss": 0.0878,
908
+ "step": 1260
909
+ },
910
+ {
911
+ "epoch": 3.28,
912
+ "learning_rate": 6.718346253229974e-05,
913
+ "loss": 0.0896,
914
+ "step": 1270
915
+ },
916
+ {
917
+ "epoch": 3.31,
918
+ "learning_rate": 6.69250645994832e-05,
919
+ "loss": 0.0917,
920
+ "step": 1280
921
+ },
922
+ {
923
+ "epoch": 3.33,
924
+ "learning_rate": 6.666666666666667e-05,
925
+ "loss": 0.0949,
926
+ "step": 1290
927
+ },
928
+ {
929
+ "epoch": 3.36,
930
+ "learning_rate": 6.640826873385013e-05,
931
+ "loss": 0.1,
932
+ "step": 1300
933
+ },
934
+ {
935
+ "epoch": 3.36,
936
+ "eval_accuracy": 0.9759509202453988,
937
+ "eval_f1": 0.2740740740740741,
938
+ "eval_loss": 0.08845529705286026,
939
+ "eval_precision": 0.8809523809523809,
940
+ "eval_recall": 0.16228070175438597,
941
+ "eval_runtime": 11.5355,
942
+ "eval_samples_per_second": 14.13,
943
+ "eval_steps_per_second": 0.954,
944
+ "step": 1300
945
+ },
946
+ {
947
+ "epoch": 3.39,
948
+ "learning_rate": 6.61498708010336e-05,
949
+ "loss": 0.092,
950
+ "step": 1310
951
+ },
952
+ {
953
+ "epoch": 3.41,
954
+ "learning_rate": 6.589147286821705e-05,
955
+ "loss": 0.09,
956
+ "step": 1320
957
+ },
958
+ {
959
+ "epoch": 3.44,
960
+ "learning_rate": 6.563307493540052e-05,
961
+ "loss": 0.0844,
962
+ "step": 1330
963
+ },
964
+ {
965
+ "epoch": 3.46,
966
+ "learning_rate": 6.537467700258399e-05,
967
+ "loss": 0.087,
968
+ "step": 1340
969
+ },
970
+ {
971
+ "epoch": 3.49,
972
+ "learning_rate": 6.511627906976745e-05,
973
+ "loss": 0.0792,
974
+ "step": 1350
975
+ },
976
+ {
977
+ "epoch": 3.51,
978
+ "learning_rate": 6.48578811369509e-05,
979
+ "loss": 0.0868,
980
+ "step": 1360
981
+ },
982
+ {
983
+ "epoch": 3.54,
984
+ "learning_rate": 6.459948320413438e-05,
985
+ "loss": 0.0892,
986
+ "step": 1370
987
+ },
988
+ {
989
+ "epoch": 3.57,
990
+ "learning_rate": 6.434108527131784e-05,
991
+ "loss": 0.0792,
992
+ "step": 1380
993
+ },
994
+ {
995
+ "epoch": 3.59,
996
+ "learning_rate": 6.408268733850129e-05,
997
+ "loss": 0.0876,
998
+ "step": 1390
999
+ },
1000
+ {
1001
+ "epoch": 3.62,
1002
+ "learning_rate": 6.382428940568475e-05,
1003
+ "loss": 0.0982,
1004
+ "step": 1400
1005
+ },
1006
+ {
1007
+ "epoch": 3.62,
1008
+ "eval_accuracy": 0.9753374233128834,
1009
+ "eval_f1": 0.22988505747126434,
1010
+ "eval_loss": 0.09349281340837479,
1011
+ "eval_precision": 0.9090909090909091,
1012
+ "eval_recall": 0.13157894736842105,
1013
+ "eval_runtime": 11.6178,
1014
+ "eval_samples_per_second": 14.03,
1015
+ "eval_steps_per_second": 0.947,
1016
+ "step": 1400
1017
+ },
1018
+ {
1019
+ "epoch": 3.64,
1020
+ "learning_rate": 6.356589147286823e-05,
1021
+ "loss": 0.0905,
1022
+ "step": 1410
1023
+ },
1024
+ {
1025
+ "epoch": 3.67,
1026
+ "learning_rate": 6.330749354005169e-05,
1027
+ "loss": 0.0881,
1028
+ "step": 1420
1029
+ },
1030
+ {
1031
+ "epoch": 3.7,
1032
+ "learning_rate": 6.304909560723514e-05,
1033
+ "loss": 0.0849,
1034
+ "step": 1430
1035
+ },
1036
+ {
1037
+ "epoch": 3.72,
1038
+ "learning_rate": 6.27906976744186e-05,
1039
+ "loss": 0.0829,
1040
+ "step": 1440
1041
+ },
1042
+ {
1043
+ "epoch": 3.75,
1044
+ "learning_rate": 6.253229974160208e-05,
1045
+ "loss": 0.0992,
1046
+ "step": 1450
1047
+ },
1048
+ {
1049
+ "epoch": 3.77,
1050
+ "learning_rate": 6.227390180878553e-05,
1051
+ "loss": 0.0998,
1052
+ "step": 1460
1053
+ },
1054
+ {
1055
+ "epoch": 3.8,
1056
+ "learning_rate": 6.201550387596899e-05,
1057
+ "loss": 0.0966,
1058
+ "step": 1470
1059
+ },
1060
+ {
1061
+ "epoch": 3.82,
1062
+ "learning_rate": 6.175710594315246e-05,
1063
+ "loss": 0.0833,
1064
+ "step": 1480
1065
+ },
1066
+ {
1067
+ "epoch": 3.85,
1068
+ "learning_rate": 6.149870801033592e-05,
1069
+ "loss": 0.0914,
1070
+ "step": 1490
1071
+ },
1072
+ {
1073
+ "epoch": 3.88,
1074
+ "learning_rate": 6.124031007751938e-05,
1075
+ "loss": 0.0785,
1076
+ "step": 1500
1077
+ },
1078
+ {
1079
+ "epoch": 3.88,
1080
+ "eval_accuracy": 0.9759509202453988,
1081
+ "eval_f1": 0.2949640287769784,
1082
+ "eval_loss": 0.08881861716508865,
1083
+ "eval_precision": 0.82,
1084
+ "eval_recall": 0.17982456140350878,
1085
+ "eval_runtime": 11.8266,
1086
+ "eval_samples_per_second": 13.783,
1087
+ "eval_steps_per_second": 0.93,
1088
+ "step": 1500
1089
+ },
1090
+ {
1091
+ "epoch": 3.9,
1092
+ "learning_rate": 6.0981912144702846e-05,
1093
+ "loss": 0.0993,
1094
+ "step": 1510
1095
+ },
1096
+ {
1097
+ "epoch": 3.93,
1098
+ "learning_rate": 6.072351421188631e-05,
1099
+ "loss": 0.0951,
1100
+ "step": 1520
1101
+ },
1102
+ {
1103
+ "epoch": 3.95,
1104
+ "learning_rate": 6.0465116279069765e-05,
1105
+ "loss": 0.0937,
1106
+ "step": 1530
1107
+ },
1108
+ {
1109
+ "epoch": 3.98,
1110
+ "learning_rate": 6.0206718346253235e-05,
1111
+ "loss": 0.089,
1112
+ "step": 1540
1113
+ },
1114
+ {
1115
+ "epoch": 4.01,
1116
+ "learning_rate": 5.99483204134367e-05,
1117
+ "loss": 0.0891,
1118
+ "step": 1550
1119
+ },
1120
+ {
1121
+ "epoch": 4.03,
1122
+ "learning_rate": 5.9689922480620155e-05,
1123
+ "loss": 0.0856,
1124
+ "step": 1560
1125
+ },
1126
+ {
1127
+ "epoch": 4.06,
1128
+ "learning_rate": 5.943152454780362e-05,
1129
+ "loss": 0.0832,
1130
+ "step": 1570
1131
+ },
1132
+ {
1133
+ "epoch": 4.08,
1134
+ "learning_rate": 5.917312661498709e-05,
1135
+ "loss": 0.088,
1136
+ "step": 1580
1137
+ },
1138
+ {
1139
+ "epoch": 4.11,
1140
+ "learning_rate": 5.891472868217055e-05,
1141
+ "loss": 0.0829,
1142
+ "step": 1590
1143
+ },
1144
+ {
1145
+ "epoch": 4.13,
1146
+ "learning_rate": 5.865633074935401e-05,
1147
+ "loss": 0.0859,
1148
+ "step": 1600
1149
+ },
1150
+ {
1151
+ "epoch": 4.13,
1152
+ "eval_accuracy": 0.9759509202453988,
1153
+ "eval_f1": 0.3,
1154
+ "eval_loss": 0.08691960573196411,
1155
+ "eval_precision": 0.8076923076923077,
1156
+ "eval_recall": 0.18421052631578946,
1157
+ "eval_runtime": 11.8328,
1158
+ "eval_samples_per_second": 13.775,
1159
+ "eval_steps_per_second": 0.93,
1160
+ "step": 1600
1161
+ },
1162
+ {
1163
+ "epoch": 4.16,
1164
+ "learning_rate": 5.839793281653747e-05,
1165
+ "loss": 0.0927,
1166
+ "step": 1610
1167
+ },
1168
+ {
1169
+ "epoch": 4.19,
1170
+ "learning_rate": 5.8139534883720933e-05,
1171
+ "loss": 0.0904,
1172
+ "step": 1620
1173
+ },
1174
+ {
1175
+ "epoch": 4.21,
1176
+ "learning_rate": 5.788113695090439e-05,
1177
+ "loss": 0.0891,
1178
+ "step": 1630
1179
+ },
1180
+ {
1181
+ "epoch": 4.24,
1182
+ "learning_rate": 5.762273901808786e-05,
1183
+ "loss": 0.0819,
1184
+ "step": 1640
1185
+ },
1186
+ {
1187
+ "epoch": 4.26,
1188
+ "learning_rate": 5.736434108527132e-05,
1189
+ "loss": 0.0868,
1190
+ "step": 1650
1191
+ },
1192
+ {
1193
+ "epoch": 4.29,
1194
+ "learning_rate": 5.7105943152454786e-05,
1195
+ "loss": 0.0909,
1196
+ "step": 1660
1197
+ },
1198
+ {
1199
+ "epoch": 4.32,
1200
+ "learning_rate": 5.684754521963824e-05,
1201
+ "loss": 0.0797,
1202
+ "step": 1670
1203
+ },
1204
+ {
1205
+ "epoch": 4.34,
1206
+ "learning_rate": 5.6589147286821706e-05,
1207
+ "loss": 0.0863,
1208
+ "step": 1680
1209
+ },
1210
+ {
1211
+ "epoch": 4.37,
1212
+ "learning_rate": 5.6330749354005176e-05,
1213
+ "loss": 0.0849,
1214
+ "step": 1690
1215
+ },
1216
+ {
1217
+ "epoch": 4.39,
1218
+ "learning_rate": 5.607235142118863e-05,
1219
+ "loss": 0.0794,
1220
+ "step": 1700
1221
+ },
1222
+ {
1223
+ "epoch": 4.39,
1224
+ "eval_accuracy": 0.976319018404908,
1225
+ "eval_f1": 0.3228070175438596,
1226
+ "eval_loss": 0.08520764857530594,
1227
+ "eval_precision": 0.8070175438596491,
1228
+ "eval_recall": 0.20175438596491227,
1229
+ "eval_runtime": 11.7131,
1230
+ "eval_samples_per_second": 13.916,
1231
+ "eval_steps_per_second": 0.939,
1232
+ "step": 1700
1233
+ },
1234
+ {
1235
+ "epoch": 4.42,
1236
+ "learning_rate": 5.5813953488372095e-05,
1237
+ "loss": 0.0857,
1238
+ "step": 1710
1239
+ },
1240
+ {
1241
+ "epoch": 4.44,
1242
+ "learning_rate": 5.555555555555556e-05,
1243
+ "loss": 0.0876,
1244
+ "step": 1720
1245
+ },
1246
+ {
1247
+ "epoch": 4.47,
1248
+ "learning_rate": 5.5297157622739015e-05,
1249
+ "loss": 0.0807,
1250
+ "step": 1730
1251
+ },
1252
+ {
1253
+ "epoch": 4.5,
1254
+ "learning_rate": 5.503875968992248e-05,
1255
+ "loss": 0.0903,
1256
+ "step": 1740
1257
+ },
1258
+ {
1259
+ "epoch": 4.52,
1260
+ "learning_rate": 5.478036175710595e-05,
1261
+ "loss": 0.0804,
1262
+ "step": 1750
1263
+ },
1264
+ {
1265
+ "epoch": 4.55,
1266
+ "learning_rate": 5.452196382428941e-05,
1267
+ "loss": 0.0921,
1268
+ "step": 1760
1269
+ },
1270
+ {
1271
+ "epoch": 4.57,
1272
+ "learning_rate": 5.426356589147287e-05,
1273
+ "loss": 0.0734,
1274
+ "step": 1770
1275
+ },
1276
+ {
1277
+ "epoch": 4.6,
1278
+ "learning_rate": 5.400516795865633e-05,
1279
+ "loss": 0.0778,
1280
+ "step": 1780
1281
+ },
1282
+ {
1283
+ "epoch": 4.63,
1284
+ "learning_rate": 5.37467700258398e-05,
1285
+ "loss": 0.0833,
1286
+ "step": 1790
1287
+ },
1288
+ {
1289
+ "epoch": 4.65,
1290
+ "learning_rate": 5.348837209302326e-05,
1291
+ "loss": 0.0835,
1292
+ "step": 1800
1293
+ },
1294
+ {
1295
+ "epoch": 4.65,
1296
+ "eval_accuracy": 0.9773006134969325,
1297
+ "eval_f1": 0.37288135593220334,
1298
+ "eval_loss": 0.08421062678098679,
1299
+ "eval_precision": 0.8208955223880597,
1300
+ "eval_recall": 0.2412280701754386,
1301
+ "eval_runtime": 11.9185,
1302
+ "eval_samples_per_second": 13.676,
1303
+ "eval_steps_per_second": 0.923,
1304
+ "step": 1800
1305
+ },
1306
+ {
1307
+ "epoch": 4.68,
1308
+ "learning_rate": 5.322997416020672e-05,
1309
+ "loss": 0.0774,
1310
+ "step": 1810
1311
+ },
1312
+ {
1313
+ "epoch": 4.7,
1314
+ "learning_rate": 5.297157622739018e-05,
1315
+ "loss": 0.0829,
1316
+ "step": 1820
1317
+ },
1318
+ {
1319
+ "epoch": 4.73,
1320
+ "learning_rate": 5.271317829457365e-05,
1321
+ "loss": 0.0821,
1322
+ "step": 1830
1323
+ },
1324
+ {
1325
+ "epoch": 4.75,
1326
+ "learning_rate": 5.24547803617571e-05,
1327
+ "loss": 0.0827,
1328
+ "step": 1840
1329
+ },
1330
+ {
1331
+ "epoch": 4.78,
1332
+ "learning_rate": 5.219638242894057e-05,
1333
+ "loss": 0.0836,
1334
+ "step": 1850
1335
+ },
1336
+ {
1337
+ "epoch": 4.81,
1338
+ "learning_rate": 5.1937984496124036e-05,
1339
+ "loss": 0.0767,
1340
+ "step": 1860
1341
+ },
1342
+ {
1343
+ "epoch": 4.83,
1344
+ "learning_rate": 5.167958656330749e-05,
1345
+ "loss": 0.0769,
1346
+ "step": 1870
1347
+ },
1348
+ {
1349
+ "epoch": 4.86,
1350
+ "learning_rate": 5.1421188630490955e-05,
1351
+ "loss": 0.0823,
1352
+ "step": 1880
1353
+ },
1354
+ {
1355
+ "epoch": 4.88,
1356
+ "learning_rate": 5.1162790697674425e-05,
1357
+ "loss": 0.0833,
1358
+ "step": 1890
1359
+ },
1360
+ {
1361
+ "epoch": 4.91,
1362
+ "learning_rate": 5.090439276485789e-05,
1363
+ "loss": 0.0831,
1364
+ "step": 1900
1365
+ },
1366
+ {
1367
+ "epoch": 4.91,
1368
+ "eval_accuracy": 0.9775460122699386,
1369
+ "eval_f1": 0.37542662116040953,
1370
+ "eval_loss": 0.0831713080406189,
1371
+ "eval_precision": 0.8461538461538461,
1372
+ "eval_recall": 0.2412280701754386,
1373
+ "eval_runtime": 11.6419,
1374
+ "eval_samples_per_second": 14.001,
1375
+ "eval_steps_per_second": 0.945,
1376
+ "step": 1900
1377
+ },
1378
+ {
1379
+ "epoch": 4.94,
1380
+ "learning_rate": 5.0645994832041345e-05,
1381
+ "loss": 0.0885,
1382
+ "step": 1910
1383
+ },
1384
+ {
1385
+ "epoch": 4.96,
1386
+ "learning_rate": 5.038759689922481e-05,
1387
+ "loss": 0.0838,
1388
+ "step": 1920
1389
+ },
1390
+ {
1391
+ "epoch": 4.99,
1392
+ "learning_rate": 5.012919896640828e-05,
1393
+ "loss": 0.0797,
1394
+ "step": 1930
1395
+ },
1396
+ {
1397
+ "epoch": 5.01,
1398
+ "learning_rate": 4.9870801033591734e-05,
1399
+ "loss": 0.0734,
1400
+ "step": 1940
1401
+ },
1402
+ {
1403
+ "epoch": 5.04,
1404
+ "learning_rate": 4.96124031007752e-05,
1405
+ "loss": 0.075,
1406
+ "step": 1950
1407
+ },
1408
+ {
1409
+ "epoch": 5.06,
1410
+ "learning_rate": 4.935400516795866e-05,
1411
+ "loss": 0.0721,
1412
+ "step": 1960
1413
+ },
1414
+ {
1415
+ "epoch": 5.09,
1416
+ "learning_rate": 4.9095607235142123e-05,
1417
+ "loss": 0.0746,
1418
+ "step": 1970
1419
+ },
1420
+ {
1421
+ "epoch": 5.12,
1422
+ "learning_rate": 4.883720930232558e-05,
1423
+ "loss": 0.0678,
1424
+ "step": 1980
1425
+ },
1426
+ {
1427
+ "epoch": 5.14,
1428
+ "learning_rate": 4.857881136950905e-05,
1429
+ "loss": 0.077,
1430
+ "step": 1990
1431
+ },
1432
+ {
1433
+ "epoch": 5.17,
1434
+ "learning_rate": 4.8320413436692506e-05,
1435
+ "loss": 0.0763,
1436
+ "step": 2000
1437
+ },
1438
+ {
1439
+ "epoch": 5.17,
1440
+ "eval_accuracy": 0.9771779141104294,
1441
+ "eval_f1": 0.3673469387755102,
1442
+ "eval_loss": 0.08154629170894623,
1443
+ "eval_precision": 0.8181818181818182,
1444
+ "eval_recall": 0.23684210526315788,
1445
+ "eval_runtime": 11.9474,
1446
+ "eval_samples_per_second": 13.643,
1447
+ "eval_steps_per_second": 0.921,
1448
+ "step": 2000
1449
+ },
1450
+ {
1451
+ "epoch": 5.19,
1452
+ "learning_rate": 4.8062015503875976e-05,
1453
+ "loss": 0.0803,
1454
+ "step": 2010
1455
+ },
1456
+ {
1457
+ "epoch": 5.22,
1458
+ "learning_rate": 4.780361757105943e-05,
1459
+ "loss": 0.086,
1460
+ "step": 2020
1461
+ },
1462
+ {
1463
+ "epoch": 5.25,
1464
+ "learning_rate": 4.7545219638242896e-05,
1465
+ "loss": 0.0766,
1466
+ "step": 2030
1467
+ },
1468
+ {
1469
+ "epoch": 5.27,
1470
+ "learning_rate": 4.728682170542636e-05,
1471
+ "loss": 0.0832,
1472
+ "step": 2040
1473
+ },
1474
+ {
1475
+ "epoch": 5.3,
1476
+ "learning_rate": 4.702842377260982e-05,
1477
+ "loss": 0.0817,
1478
+ "step": 2050
1479
+ },
1480
+ {
1481
+ "epoch": 5.32,
1482
+ "learning_rate": 4.6770025839793285e-05,
1483
+ "loss": 0.0825,
1484
+ "step": 2060
1485
+ },
1486
+ {
1487
+ "epoch": 5.35,
1488
+ "learning_rate": 4.651162790697675e-05,
1489
+ "loss": 0.0751,
1490
+ "step": 2070
1491
+ },
1492
+ {
1493
+ "epoch": 5.37,
1494
+ "learning_rate": 4.625322997416021e-05,
1495
+ "loss": 0.0719,
1496
+ "step": 2080
1497
+ },
1498
+ {
1499
+ "epoch": 5.4,
1500
+ "learning_rate": 4.5994832041343674e-05,
1501
+ "loss": 0.0826,
1502
+ "step": 2090
1503
+ },
1504
+ {
1505
+ "epoch": 5.43,
1506
+ "learning_rate": 4.573643410852713e-05,
1507
+ "loss": 0.0784,
1508
+ "step": 2100
1509
+ },
1510
+ {
1511
+ "epoch": 5.43,
1512
+ "eval_accuracy": 0.9773006134969325,
1513
+ "eval_f1": 0.3642611683848797,
1514
+ "eval_loss": 0.08145377784967422,
1515
+ "eval_precision": 0.8412698412698413,
1516
+ "eval_recall": 0.2324561403508772,
1517
+ "eval_runtime": 11.7404,
1518
+ "eval_samples_per_second": 13.884,
1519
+ "eval_steps_per_second": 0.937,
1520
+ "step": 2100
1521
+ },
1522
+ {
1523
+ "epoch": 5.45,
1524
+ "learning_rate": 4.54780361757106e-05,
1525
+ "loss": 0.0888,
1526
+ "step": 2110
1527
+ },
1528
+ {
1529
+ "epoch": 5.48,
1530
+ "learning_rate": 4.521963824289406e-05,
1531
+ "loss": 0.0743,
1532
+ "step": 2120
1533
+ },
1534
+ {
1535
+ "epoch": 5.5,
1536
+ "learning_rate": 4.496124031007753e-05,
1537
+ "loss": 0.0678,
1538
+ "step": 2130
1539
+ },
1540
+ {
1541
+ "epoch": 5.53,
1542
+ "learning_rate": 4.4702842377260983e-05,
1543
+ "loss": 0.0737,
1544
+ "step": 2140
1545
+ },
1546
+ {
1547
+ "epoch": 5.56,
1548
+ "learning_rate": 4.4444444444444447e-05,
1549
+ "loss": 0.0747,
1550
+ "step": 2150
1551
+ },
1552
+ {
1553
+ "epoch": 5.58,
1554
+ "learning_rate": 4.418604651162791e-05,
1555
+ "loss": 0.0735,
1556
+ "step": 2160
1557
+ },
1558
+ {
1559
+ "epoch": 5.61,
1560
+ "learning_rate": 4.392764857881137e-05,
1561
+ "loss": 0.075,
1562
+ "step": 2170
1563
+ },
1564
+ {
1565
+ "epoch": 5.63,
1566
+ "learning_rate": 4.3669250645994836e-05,
1567
+ "loss": 0.0726,
1568
+ "step": 2180
1569
+ },
1570
+ {
1571
+ "epoch": 5.66,
1572
+ "learning_rate": 4.34108527131783e-05,
1573
+ "loss": 0.0701,
1574
+ "step": 2190
1575
+ },
1576
+ {
1577
+ "epoch": 5.68,
1578
+ "learning_rate": 4.315245478036176e-05,
1579
+ "loss": 0.073,
1580
+ "step": 2200
1581
+ },
1582
+ {
1583
+ "epoch": 5.68,
1584
+ "eval_accuracy": 0.9769325153374233,
1585
+ "eval_f1": 0.38562091503267976,
1586
+ "eval_loss": 0.08116535097360611,
1587
+ "eval_precision": 0.7564102564102564,
1588
+ "eval_recall": 0.25877192982456143,
1589
+ "eval_runtime": 11.6668,
1590
+ "eval_samples_per_second": 13.971,
1591
+ "eval_steps_per_second": 0.943,
1592
+ "step": 2200
1593
+ },
1594
+ {
1595
+ "epoch": 5.71,
1596
+ "learning_rate": 4.289405684754522e-05,
1597
+ "loss": 0.0725,
1598
+ "step": 2210
1599
+ },
1600
+ {
1601
+ "epoch": 5.74,
1602
+ "learning_rate": 4.263565891472868e-05,
1603
+ "loss": 0.087,
1604
+ "step": 2220
1605
+ },
1606
+ {
1607
+ "epoch": 5.76,
1608
+ "learning_rate": 4.2377260981912145e-05,
1609
+ "loss": 0.0849,
1610
+ "step": 2230
1611
+ },
1612
+ {
1613
+ "epoch": 5.79,
1614
+ "learning_rate": 4.211886304909561e-05,
1615
+ "loss": 0.0696,
1616
+ "step": 2240
1617
+ },
1618
+ {
1619
+ "epoch": 5.81,
1620
+ "learning_rate": 4.186046511627907e-05,
1621
+ "loss": 0.0848,
1622
+ "step": 2250
1623
+ },
1624
+ {
1625
+ "epoch": 5.84,
1626
+ "learning_rate": 4.1602067183462534e-05,
1627
+ "loss": 0.0798,
1628
+ "step": 2260
1629
+ },
1630
+ {
1631
+ "epoch": 5.87,
1632
+ "learning_rate": 4.1343669250646e-05,
1633
+ "loss": 0.0751,
1634
+ "step": 2270
1635
+ },
1636
+ {
1637
+ "epoch": 5.89,
1638
+ "learning_rate": 4.108527131782946e-05,
1639
+ "loss": 0.0773,
1640
+ "step": 2280
1641
+ },
1642
+ {
1643
+ "epoch": 5.92,
1644
+ "learning_rate": 4.082687338501292e-05,
1645
+ "loss": 0.0848,
1646
+ "step": 2290
1647
+ },
1648
+ {
1649
+ "epoch": 5.94,
1650
+ "learning_rate": 4.056847545219639e-05,
1651
+ "loss": 0.0801,
1652
+ "step": 2300
1653
+ },
1654
+ {
1655
+ "epoch": 5.94,
1656
+ "eval_accuracy": 0.9776687116564418,
1657
+ "eval_f1": 0.3591549295774648,
1658
+ "eval_loss": 0.07930972427129745,
1659
+ "eval_precision": 0.9107142857142857,
1660
+ "eval_recall": 0.2236842105263158,
1661
+ "eval_runtime": 11.5705,
1662
+ "eval_samples_per_second": 14.088,
1663
+ "eval_steps_per_second": 0.951,
1664
+ "step": 2300
1665
+ },
1666
+ {
1667
+ "epoch": 5.97,
1668
+ "learning_rate": 4.0310077519379843e-05,
1669
+ "loss": 0.0853,
1670
+ "step": 2310
1671
+ },
1672
+ {
1673
+ "epoch": 5.99,
1674
+ "learning_rate": 4.005167958656331e-05,
1675
+ "loss": 0.0789,
1676
+ "step": 2320
1677
+ },
1678
+ {
1679
+ "epoch": 6.02,
1680
+ "learning_rate": 3.979328165374677e-05,
1681
+ "loss": 0.0724,
1682
+ "step": 2330
1683
+ },
1684
+ {
1685
+ "epoch": 6.05,
1686
+ "learning_rate": 3.953488372093023e-05,
1687
+ "loss": 0.0754,
1688
+ "step": 2340
1689
+ },
1690
+ {
1691
+ "epoch": 6.07,
1692
+ "learning_rate": 3.9276485788113696e-05,
1693
+ "loss": 0.0769,
1694
+ "step": 2350
1695
+ },
1696
+ {
1697
+ "epoch": 6.1,
1698
+ "learning_rate": 3.901808785529716e-05,
1699
+ "loss": 0.0665,
1700
+ "step": 2360
1701
+ },
1702
+ {
1703
+ "epoch": 6.12,
1704
+ "learning_rate": 3.875968992248062e-05,
1705
+ "loss": 0.067,
1706
+ "step": 2370
1707
+ },
1708
+ {
1709
+ "epoch": 6.15,
1710
+ "learning_rate": 3.8501291989664085e-05,
1711
+ "loss": 0.0682,
1712
+ "step": 2380
1713
+ },
1714
+ {
1715
+ "epoch": 6.18,
1716
+ "learning_rate": 3.824289405684754e-05,
1717
+ "loss": 0.0741,
1718
+ "step": 2390
1719
+ },
1720
+ {
1721
+ "epoch": 6.2,
1722
+ "learning_rate": 3.798449612403101e-05,
1723
+ "loss": 0.077,
1724
+ "step": 2400
1725
+ },
1726
+ {
1727
+ "epoch": 6.2,
1728
+ "eval_accuracy": 0.9774233128834355,
1729
+ "eval_f1": 0.3825503355704698,
1730
+ "eval_loss": 0.07888315618038177,
1731
+ "eval_precision": 0.8142857142857143,
1732
+ "eval_recall": 0.25,
1733
+ "eval_runtime": 11.8196,
1734
+ "eval_samples_per_second": 13.791,
1735
+ "eval_steps_per_second": 0.931,
1736
+ "step": 2400
1737
+ },
1738
+ {
1739
+ "epoch": 6.23,
1740
+ "learning_rate": 3.772609819121447e-05,
1741
+ "loss": 0.0685,
1742
+ "step": 2410
1743
+ },
1744
+ {
1745
+ "epoch": 6.25,
1746
+ "learning_rate": 3.746770025839794e-05,
1747
+ "loss": 0.0752,
1748
+ "step": 2420
1749
+ },
1750
+ {
1751
+ "epoch": 6.28,
1752
+ "learning_rate": 3.7209302325581394e-05,
1753
+ "loss": 0.0704,
1754
+ "step": 2430
1755
+ },
1756
+ {
1757
+ "epoch": 6.3,
1758
+ "learning_rate": 3.6950904392764864e-05,
1759
+ "loss": 0.0755,
1760
+ "step": 2440
1761
+ },
1762
+ {
1763
+ "epoch": 6.33,
1764
+ "learning_rate": 3.669250645994832e-05,
1765
+ "loss": 0.0726,
1766
+ "step": 2450
1767
+ },
1768
+ {
1769
+ "epoch": 6.36,
1770
+ "learning_rate": 3.6434108527131784e-05,
1771
+ "loss": 0.0622,
1772
+ "step": 2460
1773
+ },
1774
+ {
1775
+ "epoch": 6.38,
1776
+ "learning_rate": 3.617571059431525e-05,
1777
+ "loss": 0.0742,
1778
+ "step": 2470
1779
+ },
1780
+ {
1781
+ "epoch": 6.41,
1782
+ "learning_rate": 3.591731266149871e-05,
1783
+ "loss": 0.0813,
1784
+ "step": 2480
1785
+ },
1786
+ {
1787
+ "epoch": 6.43,
1788
+ "learning_rate": 3.565891472868217e-05,
1789
+ "loss": 0.0724,
1790
+ "step": 2490
1791
+ },
1792
+ {
1793
+ "epoch": 6.46,
1794
+ "learning_rate": 3.5400516795865637e-05,
1795
+ "loss": 0.0749,
1796
+ "step": 2500
1797
+ },
1798
+ {
1799
+ "epoch": 6.46,
1800
+ "eval_accuracy": 0.9779141104294479,
1801
+ "eval_f1": 0.41558441558441556,
1802
+ "eval_loss": 0.077651746571064,
1803
+ "eval_precision": 0.8,
1804
+ "eval_recall": 0.2807017543859649,
1805
+ "eval_runtime": 12.0214,
1806
+ "eval_samples_per_second": 13.559,
1807
+ "eval_steps_per_second": 0.915,
1808
+ "step": 2500
1809
+ },
1810
+ {
1811
+ "epoch": 6.49,
1812
+ "learning_rate": 3.514211886304909e-05,
1813
+ "loss": 0.0667,
1814
+ "step": 2510
1815
+ },
1816
+ {
1817
+ "epoch": 6.51,
1818
+ "learning_rate": 3.488372093023256e-05,
1819
+ "loss": 0.0646,
1820
+ "step": 2520
1821
+ },
1822
+ {
1823
+ "epoch": 6.54,
1824
+ "learning_rate": 3.462532299741602e-05,
1825
+ "loss": 0.0744,
1826
+ "step": 2530
1827
+ },
1828
+ {
1829
+ "epoch": 6.56,
1830
+ "learning_rate": 3.436692506459949e-05,
1831
+ "loss": 0.0815,
1832
+ "step": 2540
1833
+ },
1834
+ {
1835
+ "epoch": 6.59,
1836
+ "learning_rate": 3.4108527131782945e-05,
1837
+ "loss": 0.0629,
1838
+ "step": 2550
1839
+ },
1840
+ {
1841
+ "epoch": 6.61,
1842
+ "learning_rate": 3.3850129198966415e-05,
1843
+ "loss": 0.0729,
1844
+ "step": 2560
1845
+ },
1846
+ {
1847
+ "epoch": 6.64,
1848
+ "learning_rate": 3.359173126614987e-05,
1849
+ "loss": 0.0874,
1850
+ "step": 2570
1851
+ },
1852
+ {
1853
+ "epoch": 6.67,
1854
+ "learning_rate": 3.3333333333333335e-05,
1855
+ "loss": 0.0725,
1856
+ "step": 2580
1857
+ },
1858
+ {
1859
+ "epoch": 6.69,
1860
+ "learning_rate": 3.30749354005168e-05,
1861
+ "loss": 0.0693,
1862
+ "step": 2590
1863
+ },
1864
+ {
1865
+ "epoch": 6.72,
1866
+ "learning_rate": 3.281653746770026e-05,
1867
+ "loss": 0.0704,
1868
+ "step": 2600
1869
+ },
1870
+ {
1871
+ "epoch": 6.72,
1872
+ "eval_accuracy": 0.9786503067484662,
1873
+ "eval_f1": 0.423841059602649,
1874
+ "eval_loss": 0.07763181626796722,
1875
+ "eval_precision": 0.8648648648648649,
1876
+ "eval_recall": 0.2807017543859649,
1877
+ "eval_runtime": 11.5898,
1878
+ "eval_samples_per_second": 14.064,
1879
+ "eval_steps_per_second": 0.949,
1880
+ "step": 2600
1881
+ },
1882
+ {
1883
+ "epoch": 6.74,
1884
+ "learning_rate": 3.2558139534883724e-05,
1885
+ "loss": 0.0812,
1886
+ "step": 2610
1887
+ },
1888
+ {
1889
+ "epoch": 6.77,
1890
+ "learning_rate": 3.229974160206719e-05,
1891
+ "loss": 0.0693,
1892
+ "step": 2620
1893
+ },
1894
+ {
1895
+ "epoch": 6.8,
1896
+ "learning_rate": 3.2041343669250644e-05,
1897
+ "loss": 0.0687,
1898
+ "step": 2630
1899
+ },
1900
+ {
1901
+ "epoch": 6.82,
1902
+ "learning_rate": 3.1782945736434114e-05,
1903
+ "loss": 0.0698,
1904
+ "step": 2640
1905
+ },
1906
+ {
1907
+ "epoch": 6.85,
1908
+ "learning_rate": 3.152454780361757e-05,
1909
+ "loss": 0.0688,
1910
+ "step": 2650
1911
+ },
1912
+ {
1913
+ "epoch": 6.87,
1914
+ "learning_rate": 3.126614987080104e-05,
1915
+ "loss": 0.0742,
1916
+ "step": 2660
1917
+ },
1918
+ {
1919
+ "epoch": 6.9,
1920
+ "learning_rate": 3.1007751937984497e-05,
1921
+ "loss": 0.0773,
1922
+ "step": 2670
1923
+ },
1924
+ {
1925
+ "epoch": 6.93,
1926
+ "learning_rate": 3.074935400516796e-05,
1927
+ "loss": 0.0714,
1928
+ "step": 2680
1929
+ },
1930
+ {
1931
+ "epoch": 6.95,
1932
+ "learning_rate": 3.0490956072351423e-05,
1933
+ "loss": 0.0678,
1934
+ "step": 2690
1935
+ },
1936
+ {
1937
+ "epoch": 6.98,
1938
+ "learning_rate": 3.0232558139534883e-05,
1939
+ "loss": 0.0718,
1940
+ "step": 2700
1941
+ },
1942
+ {
1943
+ "epoch": 6.98,
1944
+ "eval_accuracy": 0.9776687116564418,
1945
+ "eval_f1": 0.389261744966443,
1946
+ "eval_loss": 0.07732577621936798,
1947
+ "eval_precision": 0.8285714285714286,
1948
+ "eval_recall": 0.2543859649122807,
1949
+ "eval_runtime": 11.7112,
1950
+ "eval_samples_per_second": 13.918,
1951
+ "eval_steps_per_second": 0.939,
1952
+ "step": 2700
1953
+ },
1954
+ {
1955
+ "epoch": 7.0,
1956
+ "learning_rate": 2.997416020671835e-05,
1957
+ "loss": 0.0723,
1958
+ "step": 2710
1959
+ },
1960
+ {
1961
+ "epoch": 7.03,
1962
+ "learning_rate": 2.971576227390181e-05,
1963
+ "loss": 0.0669,
1964
+ "step": 2720
1965
+ },
1966
+ {
1967
+ "epoch": 7.05,
1968
+ "learning_rate": 2.9457364341085275e-05,
1969
+ "loss": 0.0705,
1970
+ "step": 2730
1971
+ },
1972
+ {
1973
+ "epoch": 7.08,
1974
+ "learning_rate": 2.9198966408268735e-05,
1975
+ "loss": 0.0697,
1976
+ "step": 2740
1977
+ },
1978
+ {
1979
+ "epoch": 7.11,
1980
+ "learning_rate": 2.8940568475452195e-05,
1981
+ "loss": 0.0723,
1982
+ "step": 2750
1983
+ },
1984
+ {
1985
+ "epoch": 7.13,
1986
+ "learning_rate": 2.868217054263566e-05,
1987
+ "loss": 0.0693,
1988
+ "step": 2760
1989
+ },
1990
+ {
1991
+ "epoch": 7.16,
1992
+ "learning_rate": 2.842377260981912e-05,
1993
+ "loss": 0.0653,
1994
+ "step": 2770
1995
+ },
1996
+ {
1997
+ "epoch": 7.18,
1998
+ "learning_rate": 2.8165374677002588e-05,
1999
+ "loss": 0.0651,
2000
+ "step": 2780
2001
+ },
2002
+ {
2003
+ "epoch": 7.21,
2004
+ "learning_rate": 2.7906976744186048e-05,
2005
+ "loss": 0.0714,
2006
+ "step": 2790
2007
+ },
2008
+ {
2009
+ "epoch": 7.24,
2010
+ "learning_rate": 2.7648578811369507e-05,
2011
+ "loss": 0.0624,
2012
+ "step": 2800
2013
+ },
2014
+ {
2015
+ "epoch": 7.24,
2016
+ "eval_accuracy": 0.978159509202454,
2017
+ "eval_f1": 0.3945578231292517,
2018
+ "eval_loss": 0.0775144025683403,
2019
+ "eval_precision": 0.8787878787878788,
2020
+ "eval_recall": 0.2543859649122807,
2021
+ "eval_runtime": 11.801,
2022
+ "eval_samples_per_second": 13.812,
2023
+ "eval_steps_per_second": 0.932,
2024
+ "step": 2800
2025
+ },
2026
+ {
2027
+ "epoch": 7.26,
2028
+ "learning_rate": 2.7390180878552974e-05,
2029
+ "loss": 0.0596,
2030
+ "step": 2810
2031
+ },
2032
+ {
2033
+ "epoch": 7.29,
2034
+ "learning_rate": 2.7131782945736434e-05,
2035
+ "loss": 0.0712,
2036
+ "step": 2820
2037
+ },
2038
+ {
2039
+ "epoch": 7.31,
2040
+ "learning_rate": 2.68733850129199e-05,
2041
+ "loss": 0.0605,
2042
+ "step": 2830
2043
+ },
2044
+ {
2045
+ "epoch": 7.34,
2046
+ "learning_rate": 2.661498708010336e-05,
2047
+ "loss": 0.0665,
2048
+ "step": 2840
2049
+ },
2050
+ {
2051
+ "epoch": 7.36,
2052
+ "learning_rate": 2.6356589147286826e-05,
2053
+ "loss": 0.0651,
2054
+ "step": 2850
2055
+ },
2056
+ {
2057
+ "epoch": 7.39,
2058
+ "learning_rate": 2.6098191214470286e-05,
2059
+ "loss": 0.0677,
2060
+ "step": 2860
2061
+ },
2062
+ {
2063
+ "epoch": 7.42,
2064
+ "learning_rate": 2.5839793281653746e-05,
2065
+ "loss": 0.0715,
2066
+ "step": 2870
2067
+ },
2068
+ {
2069
+ "epoch": 7.44,
2070
+ "learning_rate": 2.5581395348837212e-05,
2071
+ "loss": 0.0691,
2072
+ "step": 2880
2073
+ },
2074
+ {
2075
+ "epoch": 7.47,
2076
+ "learning_rate": 2.5322997416020672e-05,
2077
+ "loss": 0.0689,
2078
+ "step": 2890
2079
+ },
2080
+ {
2081
+ "epoch": 7.49,
2082
+ "learning_rate": 2.506459948320414e-05,
2083
+ "loss": 0.0718,
2084
+ "step": 2900
2085
+ },
2086
+ {
2087
+ "epoch": 7.49,
2088
+ "eval_accuracy": 0.9780368098159509,
2089
+ "eval_f1": 0.4013377926421405,
2090
+ "eval_loss": 0.07592039555311203,
2091
+ "eval_precision": 0.8450704225352113,
2092
+ "eval_recall": 0.2631578947368421,
2093
+ "eval_runtime": 11.7263,
2094
+ "eval_samples_per_second": 13.9,
2095
+ "eval_steps_per_second": 0.938,
2096
+ "step": 2900
2097
+ },
2098
+ {
2099
+ "epoch": 7.52,
2100
+ "learning_rate": 2.48062015503876e-05,
2101
+ "loss": 0.0668,
2102
+ "step": 2910
2103
+ },
2104
+ {
2105
+ "epoch": 7.55,
2106
+ "learning_rate": 2.4547803617571062e-05,
2107
+ "loss": 0.0664,
2108
+ "step": 2920
2109
+ },
2110
+ {
2111
+ "epoch": 7.57,
2112
+ "learning_rate": 2.4289405684754525e-05,
2113
+ "loss": 0.0645,
2114
+ "step": 2930
2115
+ },
2116
+ {
2117
+ "epoch": 7.6,
2118
+ "learning_rate": 2.4031007751937988e-05,
2119
+ "loss": 0.0763,
2120
+ "step": 2940
2121
+ },
2122
+ {
2123
+ "epoch": 7.62,
2124
+ "learning_rate": 2.3772609819121448e-05,
2125
+ "loss": 0.0677,
2126
+ "step": 2950
2127
+ },
2128
+ {
2129
+ "epoch": 7.65,
2130
+ "learning_rate": 2.351421188630491e-05,
2131
+ "loss": 0.0679,
2132
+ "step": 2960
2133
+ },
2134
+ {
2135
+ "epoch": 7.67,
2136
+ "learning_rate": 2.3255813953488374e-05,
2137
+ "loss": 0.0722,
2138
+ "step": 2970
2139
+ },
2140
+ {
2141
+ "epoch": 7.7,
2142
+ "learning_rate": 2.2997416020671837e-05,
2143
+ "loss": 0.0655,
2144
+ "step": 2980
2145
+ },
2146
+ {
2147
+ "epoch": 7.73,
2148
+ "learning_rate": 2.27390180878553e-05,
2149
+ "loss": 0.0702,
2150
+ "step": 2990
2151
+ },
2152
+ {
2153
+ "epoch": 7.75,
2154
+ "learning_rate": 2.2480620155038764e-05,
2155
+ "loss": 0.0671,
2156
+ "step": 3000
2157
+ },
2158
+ {
2159
+ "epoch": 7.75,
2160
+ "eval_accuracy": 0.9787730061349693,
2161
+ "eval_f1": 0.4437299035369775,
2162
+ "eval_loss": 0.07497038692235947,
2163
+ "eval_precision": 0.8313253012048193,
2164
+ "eval_recall": 0.3026315789473684,
2165
+ "eval_runtime": 11.8994,
2166
+ "eval_samples_per_second": 13.698,
2167
+ "eval_steps_per_second": 0.924,
2168
+ "step": 3000
2169
+ },
2170
+ {
2171
+ "epoch": 7.78,
2172
+ "learning_rate": 2.2222222222222223e-05,
2173
+ "loss": 0.0681,
2174
+ "step": 3010
2175
+ },
2176
+ {
2177
+ "epoch": 7.8,
2178
+ "learning_rate": 2.1963824289405686e-05,
2179
+ "loss": 0.0687,
2180
+ "step": 3020
2181
+ },
2182
+ {
2183
+ "epoch": 7.83,
2184
+ "learning_rate": 2.170542635658915e-05,
2185
+ "loss": 0.07,
2186
+ "step": 3030
2187
+ },
2188
+ {
2189
+ "epoch": 7.86,
2190
+ "learning_rate": 2.144702842377261e-05,
2191
+ "loss": 0.0702,
2192
+ "step": 3040
2193
+ },
2194
+ {
2195
+ "epoch": 7.88,
2196
+ "learning_rate": 2.1188630490956073e-05,
2197
+ "loss": 0.0717,
2198
+ "step": 3050
2199
+ },
2200
+ {
2201
+ "epoch": 7.91,
2202
+ "learning_rate": 2.0930232558139536e-05,
2203
+ "loss": 0.0646,
2204
+ "step": 3060
2205
+ },
2206
+ {
2207
+ "epoch": 7.93,
2208
+ "learning_rate": 2.0671834625323e-05,
2209
+ "loss": 0.0706,
2210
+ "step": 3070
2211
+ },
2212
+ {
2213
+ "epoch": 7.96,
2214
+ "learning_rate": 2.041343669250646e-05,
2215
+ "loss": 0.0649,
2216
+ "step": 3080
2217
+ },
2218
+ {
2219
+ "epoch": 7.98,
2220
+ "learning_rate": 2.0155038759689922e-05,
2221
+ "loss": 0.0663,
2222
+ "step": 3090
2223
+ },
2224
+ {
2225
+ "epoch": 8.01,
2226
+ "learning_rate": 1.9896640826873385e-05,
2227
+ "loss": 0.0554,
2228
+ "step": 3100
2229
+ },
2230
+ {
2231
+ "epoch": 8.01,
2232
+ "eval_accuracy": 0.9790184049079754,
2233
+ "eval_f1": 0.45714285714285713,
2234
+ "eval_loss": 0.07580507546663284,
2235
+ "eval_precision": 0.8275862068965517,
2236
+ "eval_recall": 0.3157894736842105,
2237
+ "eval_runtime": 11.6291,
2238
+ "eval_samples_per_second": 14.017,
2239
+ "eval_steps_per_second": 0.946,
2240
+ "step": 3100
2241
+ },
2242
+ {
2243
+ "epoch": 8.04,
2244
+ "learning_rate": 1.9638242894056848e-05,
2245
+ "loss": 0.0562,
2246
+ "step": 3110
2247
+ },
2248
+ {
2249
+ "epoch": 8.06,
2250
+ "learning_rate": 1.937984496124031e-05,
2251
+ "loss": 0.061,
2252
+ "step": 3120
2253
+ },
2254
+ {
2255
+ "epoch": 8.09,
2256
+ "learning_rate": 1.912144702842377e-05,
2257
+ "loss": 0.0642,
2258
+ "step": 3130
2259
+ },
2260
+ {
2261
+ "epoch": 8.11,
2262
+ "learning_rate": 1.8863049095607234e-05,
2263
+ "loss": 0.0581,
2264
+ "step": 3140
2265
+ },
2266
+ {
2267
+ "epoch": 8.14,
2268
+ "learning_rate": 1.8604651162790697e-05,
2269
+ "loss": 0.0611,
2270
+ "step": 3150
2271
+ },
2272
+ {
2273
+ "epoch": 8.17,
2274
+ "learning_rate": 1.834625322997416e-05,
2275
+ "loss": 0.0683,
2276
+ "step": 3160
2277
+ },
2278
+ {
2279
+ "epoch": 8.19,
2280
+ "learning_rate": 1.8087855297157624e-05,
2281
+ "loss": 0.0635,
2282
+ "step": 3170
2283
+ },
2284
+ {
2285
+ "epoch": 8.22,
2286
+ "learning_rate": 1.7829457364341087e-05,
2287
+ "loss": 0.0617,
2288
+ "step": 3180
2289
+ },
2290
+ {
2291
+ "epoch": 8.24,
2292
+ "learning_rate": 1.7571059431524546e-05,
2293
+ "loss": 0.0656,
2294
+ "step": 3190
2295
+ },
2296
+ {
2297
+ "epoch": 8.27,
2298
+ "learning_rate": 1.731266149870801e-05,
2299
+ "loss": 0.0533,
2300
+ "step": 3200
2301
+ },
2302
+ {
2303
+ "epoch": 8.27,
2304
+ "eval_accuracy": 0.9787730061349693,
2305
+ "eval_f1": 0.4507936507936508,
2306
+ "eval_loss": 0.07549890875816345,
2307
+ "eval_precision": 0.8160919540229885,
2308
+ "eval_recall": 0.31140350877192985,
2309
+ "eval_runtime": 11.6344,
2310
+ "eval_samples_per_second": 14.01,
2311
+ "eval_steps_per_second": 0.945,
2312
+ "step": 3200
2313
+ },
2314
+ {
2315
+ "epoch": 8.29,
2316
+ "learning_rate": 1.7054263565891473e-05,
2317
+ "loss": 0.061,
2318
+ "step": 3210
2319
+ },
2320
+ {
2321
+ "epoch": 8.32,
2322
+ "learning_rate": 1.6795865633074936e-05,
2323
+ "loss": 0.0727,
2324
+ "step": 3220
2325
+ },
2326
+ {
2327
+ "epoch": 8.35,
2328
+ "learning_rate": 1.65374677002584e-05,
2329
+ "loss": 0.057,
2330
+ "step": 3230
2331
+ },
2332
+ {
2333
+ "epoch": 8.37,
2334
+ "learning_rate": 1.6279069767441862e-05,
2335
+ "loss": 0.0692,
2336
+ "step": 3240
2337
+ },
2338
+ {
2339
+ "epoch": 8.4,
2340
+ "learning_rate": 1.6020671834625322e-05,
2341
+ "loss": 0.0709,
2342
+ "step": 3250
2343
+ },
2344
+ {
2345
+ "epoch": 8.42,
2346
+ "learning_rate": 1.5762273901808785e-05,
2347
+ "loss": 0.055,
2348
+ "step": 3260
2349
+ },
2350
+ {
2351
+ "epoch": 8.45,
2352
+ "learning_rate": 1.5503875968992248e-05,
2353
+ "loss": 0.0626,
2354
+ "step": 3270
2355
+ },
2356
+ {
2357
+ "epoch": 8.48,
2358
+ "learning_rate": 1.5245478036175711e-05,
2359
+ "loss": 0.0696,
2360
+ "step": 3280
2361
+ },
2362
+ {
2363
+ "epoch": 8.5,
2364
+ "learning_rate": 1.4987080103359175e-05,
2365
+ "loss": 0.063,
2366
+ "step": 3290
2367
+ },
2368
+ {
2369
+ "epoch": 8.53,
2370
+ "learning_rate": 1.4728682170542638e-05,
2371
+ "loss": 0.063,
2372
+ "step": 3300
2373
+ },
2374
+ {
2375
+ "epoch": 8.53,
2376
+ "eval_accuracy": 0.9790184049079754,
2377
+ "eval_f1": 0.4605678233438486,
2378
+ "eval_loss": 0.07512389868497849,
2379
+ "eval_precision": 0.8202247191011236,
2380
+ "eval_recall": 0.3201754385964912,
2381
+ "eval_runtime": 11.9167,
2382
+ "eval_samples_per_second": 13.678,
2383
+ "eval_steps_per_second": 0.923,
2384
+ "step": 3300
2385
+ },
2386
+ {
2387
+ "epoch": 8.55,
2388
+ "learning_rate": 1.4470284237726097e-05,
2389
+ "loss": 0.0664,
2390
+ "step": 3310
2391
+ },
2392
+ {
2393
+ "epoch": 8.58,
2394
+ "learning_rate": 1.421188630490956e-05,
2395
+ "loss": 0.0717,
2396
+ "step": 3320
2397
+ },
2398
+ {
2399
+ "epoch": 8.6,
2400
+ "learning_rate": 1.3953488372093024e-05,
2401
+ "loss": 0.0632,
2402
+ "step": 3330
2403
+ },
2404
+ {
2405
+ "epoch": 8.63,
2406
+ "learning_rate": 1.3695090439276487e-05,
2407
+ "loss": 0.0645,
2408
+ "step": 3340
2409
+ },
2410
+ {
2411
+ "epoch": 8.66,
2412
+ "learning_rate": 1.343669250645995e-05,
2413
+ "loss": 0.062,
2414
+ "step": 3350
2415
+ },
2416
+ {
2417
+ "epoch": 8.68,
2418
+ "learning_rate": 1.3178294573643413e-05,
2419
+ "loss": 0.0628,
2420
+ "step": 3360
2421
+ },
2422
+ {
2423
+ "epoch": 8.71,
2424
+ "learning_rate": 1.2919896640826873e-05,
2425
+ "loss": 0.0647,
2426
+ "step": 3370
2427
+ },
2428
+ {
2429
+ "epoch": 8.73,
2430
+ "learning_rate": 1.2661498708010336e-05,
2431
+ "loss": 0.0675,
2432
+ "step": 3380
2433
+ },
2434
+ {
2435
+ "epoch": 8.76,
2436
+ "learning_rate": 1.24031007751938e-05,
2437
+ "loss": 0.0563,
2438
+ "step": 3390
2439
+ },
2440
+ {
2441
+ "epoch": 8.79,
2442
+ "learning_rate": 1.2144702842377262e-05,
2443
+ "loss": 0.0605,
2444
+ "step": 3400
2445
+ },
2446
+ {
2447
+ "epoch": 8.79,
2448
+ "eval_accuracy": 0.9790184049079754,
2449
+ "eval_f1": 0.4605678233438486,
2450
+ "eval_loss": 0.07484734058380127,
2451
+ "eval_precision": 0.8202247191011236,
2452
+ "eval_recall": 0.3201754385964912,
2453
+ "eval_runtime": 12.0314,
2454
+ "eval_samples_per_second": 13.548,
2455
+ "eval_steps_per_second": 0.914,
2456
+ "step": 3400
2457
+ },
2458
+ {
2459
+ "epoch": 8.81,
2460
+ "learning_rate": 1.1886304909560724e-05,
2461
+ "loss": 0.0623,
2462
+ "step": 3410
2463
+ },
2464
+ {
2465
+ "epoch": 8.84,
2466
+ "learning_rate": 1.1627906976744187e-05,
2467
+ "loss": 0.0666,
2468
+ "step": 3420
2469
+ },
2470
+ {
2471
+ "epoch": 8.86,
2472
+ "learning_rate": 1.136950904392765e-05,
2473
+ "loss": 0.0601,
2474
+ "step": 3430
2475
+ },
2476
+ {
2477
+ "epoch": 8.89,
2478
+ "learning_rate": 1.1111111111111112e-05,
2479
+ "loss": 0.0758,
2480
+ "step": 3440
2481
+ },
2482
+ {
2483
+ "epoch": 8.91,
2484
+ "learning_rate": 1.0852713178294575e-05,
2485
+ "loss": 0.0687,
2486
+ "step": 3450
2487
+ },
2488
+ {
2489
+ "epoch": 8.94,
2490
+ "learning_rate": 1.0594315245478036e-05,
2491
+ "loss": 0.0569,
2492
+ "step": 3460
2493
+ },
2494
+ {
2495
+ "epoch": 8.97,
2496
+ "learning_rate": 1.03359173126615e-05,
2497
+ "loss": 0.0714,
2498
+ "step": 3470
2499
+ },
2500
+ {
2501
+ "epoch": 8.99,
2502
+ "learning_rate": 1.0077519379844961e-05,
2503
+ "loss": 0.0742,
2504
+ "step": 3480
2505
+ },
2506
+ {
2507
+ "epoch": 9.02,
2508
+ "learning_rate": 9.819121447028424e-06,
2509
+ "loss": 0.0665,
2510
+ "step": 3490
2511
+ },
2512
+ {
2513
+ "epoch": 9.04,
2514
+ "learning_rate": 9.560723514211885e-06,
2515
+ "loss": 0.0592,
2516
+ "step": 3500
2517
+ },
2518
+ {
2519
+ "epoch": 9.04,
2520
+ "eval_accuracy": 0.9787730061349693,
2521
+ "eval_f1": 0.4327868852459017,
2522
+ "eval_loss": 0.07429111003875732,
2523
+ "eval_precision": 0.8571428571428571,
2524
+ "eval_recall": 0.2894736842105263,
2525
+ "eval_runtime": 11.4554,
2526
+ "eval_samples_per_second": 14.229,
2527
+ "eval_steps_per_second": 0.96,
2528
+ "step": 3500
2529
+ }
2530
+ ],
2531
+ "max_steps": 3870,
2532
+ "num_train_epochs": 10,
2533
+ "total_flos": 1.1850942195223757e+17,
2534
+ "trial_name": null,
2535
+ "trial_params": null
2536
+ }
training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ea45e8e685a8033f43eb1389d16906f6812f2862c5d13c09e2013489c73e6f88
3
+ size 3899
vocab.txt ADDED
@@ -0,0 +1,2898 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ JUMP_ADDR_0
2
+ JUMP_ADDR_1
3
+ JUMP_ADDR_2
4
+ JUMP_ADDR_3
5
+ JUMP_ADDR_4
6
+ JUMP_ADDR_5
7
+ JUMP_ADDR_6
8
+ JUMP_ADDR_7
9
+ JUMP_ADDR_8
10
+ JUMP_ADDR_9
11
+ JUMP_ADDR_10
12
+ JUMP_ADDR_11
13
+ JUMP_ADDR_12
14
+ JUMP_ADDR_13
15
+ JUMP_ADDR_14
16
+ JUMP_ADDR_15
17
+ JUMP_ADDR_16
18
+ JUMP_ADDR_17
19
+ JUMP_ADDR_18
20
+ JUMP_ADDR_19
21
+ JUMP_ADDR_20
22
+ JUMP_ADDR_21
23
+ JUMP_ADDR_22
24
+ JUMP_ADDR_23
25
+ JUMP_ADDR_24
26
+ JUMP_ADDR_25
27
+ JUMP_ADDR_26
28
+ JUMP_ADDR_27
29
+ JUMP_ADDR_28
30
+ JUMP_ADDR_29
31
+ JUMP_ADDR_30
32
+ JUMP_ADDR_31
33
+ JUMP_ADDR_32
34
+ JUMP_ADDR_33
35
+ JUMP_ADDR_34
36
+ JUMP_ADDR_35
37
+ JUMP_ADDR_36
38
+ JUMP_ADDR_37
39
+ JUMP_ADDR_38
40
+ JUMP_ADDR_39
41
+ JUMP_ADDR_40
42
+ JUMP_ADDR_41
43
+ JUMP_ADDR_42
44
+ JUMP_ADDR_43
45
+ JUMP_ADDR_44
46
+ JUMP_ADDR_45
47
+ JUMP_ADDR_46
48
+ JUMP_ADDR_47
49
+ JUMP_ADDR_48
50
+ JUMP_ADDR_49
51
+ JUMP_ADDR_50
52
+ JUMP_ADDR_51
53
+ JUMP_ADDR_52
54
+ JUMP_ADDR_53
55
+ JUMP_ADDR_54
56
+ JUMP_ADDR_55
57
+ JUMP_ADDR_56
58
+ JUMP_ADDR_57
59
+ JUMP_ADDR_58
60
+ JUMP_ADDR_59
61
+ JUMP_ADDR_60
62
+ JUMP_ADDR_61
63
+ JUMP_ADDR_62
64
+ JUMP_ADDR_63
65
+ JUMP_ADDR_64
66
+ JUMP_ADDR_65
67
+ JUMP_ADDR_66
68
+ JUMP_ADDR_67
69
+ JUMP_ADDR_68
70
+ JUMP_ADDR_69
71
+ JUMP_ADDR_70
72
+ JUMP_ADDR_71
73
+ JUMP_ADDR_72
74
+ JUMP_ADDR_73
75
+ JUMP_ADDR_74
76
+ JUMP_ADDR_75
77
+ JUMP_ADDR_76
78
+ JUMP_ADDR_77
79
+ JUMP_ADDR_78
80
+ JUMP_ADDR_79
81
+ JUMP_ADDR_80
82
+ JUMP_ADDR_81
83
+ JUMP_ADDR_82
84
+ JUMP_ADDR_83
85
+ JUMP_ADDR_84
86
+ JUMP_ADDR_85
87
+ JUMP_ADDR_86
88
+ JUMP_ADDR_87
89
+ JUMP_ADDR_88
90
+ JUMP_ADDR_89
91
+ JUMP_ADDR_90
92
+ JUMP_ADDR_91
93
+ JUMP_ADDR_92
94
+ JUMP_ADDR_93
95
+ JUMP_ADDR_94
96
+ JUMP_ADDR_95
97
+ JUMP_ADDR_96
98
+ JUMP_ADDR_97
99
+ JUMP_ADDR_98
100
+ JUMP_ADDR_99
101
+ JUMP_ADDR_100
102
+ JUMP_ADDR_101
103
+ JUMP_ADDR_102
104
+ JUMP_ADDR_103
105
+ JUMP_ADDR_104
106
+ JUMP_ADDR_105
107
+ JUMP_ADDR_106
108
+ JUMP_ADDR_107
109
+ JUMP_ADDR_108
110
+ JUMP_ADDR_109
111
+ JUMP_ADDR_110
112
+ JUMP_ADDR_111
113
+ JUMP_ADDR_112
114
+ JUMP_ADDR_113
115
+ JUMP_ADDR_114
116
+ JUMP_ADDR_115
117
+ JUMP_ADDR_116
118
+ JUMP_ADDR_117
119
+ JUMP_ADDR_118
120
+ JUMP_ADDR_119
121
+ JUMP_ADDR_120
122
+ JUMP_ADDR_121
123
+ JUMP_ADDR_122
124
+ JUMP_ADDR_123
125
+ JUMP_ADDR_124
126
+ JUMP_ADDR_125
127
+ JUMP_ADDR_126
128
+ JUMP_ADDR_127
129
+ JUMP_ADDR_128
130
+ JUMP_ADDR_129
131
+ JUMP_ADDR_130
132
+ JUMP_ADDR_131
133
+ JUMP_ADDR_132
134
+ JUMP_ADDR_133
135
+ JUMP_ADDR_134
136
+ JUMP_ADDR_135
137
+ JUMP_ADDR_136
138
+ JUMP_ADDR_137
139
+ JUMP_ADDR_138
140
+ JUMP_ADDR_139
141
+ JUMP_ADDR_140
142
+ JUMP_ADDR_141
143
+ JUMP_ADDR_142
144
+ JUMP_ADDR_143
145
+ JUMP_ADDR_144
146
+ JUMP_ADDR_145
147
+ JUMP_ADDR_146
148
+ JUMP_ADDR_147
149
+ JUMP_ADDR_148
150
+ JUMP_ADDR_149
151
+ JUMP_ADDR_150
152
+ JUMP_ADDR_151
153
+ JUMP_ADDR_152
154
+ JUMP_ADDR_153
155
+ JUMP_ADDR_154
156
+ JUMP_ADDR_155
157
+ JUMP_ADDR_156
158
+ JUMP_ADDR_157
159
+ JUMP_ADDR_158
160
+ JUMP_ADDR_159
161
+ JUMP_ADDR_160
162
+ JUMP_ADDR_161
163
+ JUMP_ADDR_162
164
+ JUMP_ADDR_163
165
+ JUMP_ADDR_164
166
+ JUMP_ADDR_165
167
+ JUMP_ADDR_166
168
+ JUMP_ADDR_167
169
+ JUMP_ADDR_168
170
+ JUMP_ADDR_169
171
+ JUMP_ADDR_170
172
+ JUMP_ADDR_171
173
+ JUMP_ADDR_172
174
+ JUMP_ADDR_173
175
+ JUMP_ADDR_174
176
+ JUMP_ADDR_175
177
+ JUMP_ADDR_176
178
+ JUMP_ADDR_177
179
+ JUMP_ADDR_178
180
+ JUMP_ADDR_179
181
+ JUMP_ADDR_180
182
+ JUMP_ADDR_181
183
+ JUMP_ADDR_182
184
+ JUMP_ADDR_183
185
+ JUMP_ADDR_184
186
+ JUMP_ADDR_185
187
+ JUMP_ADDR_186
188
+ JUMP_ADDR_187
189
+ JUMP_ADDR_188
190
+ JUMP_ADDR_189
191
+ JUMP_ADDR_190
192
+ JUMP_ADDR_191
193
+ JUMP_ADDR_192
194
+ JUMP_ADDR_193
195
+ JUMP_ADDR_194
196
+ JUMP_ADDR_195
197
+ JUMP_ADDR_196
198
+ JUMP_ADDR_197
199
+ JUMP_ADDR_198
200
+ JUMP_ADDR_199
201
+ JUMP_ADDR_200
202
+ JUMP_ADDR_201
203
+ JUMP_ADDR_202
204
+ JUMP_ADDR_203
205
+ JUMP_ADDR_204
206
+ JUMP_ADDR_205
207
+ JUMP_ADDR_206
208
+ JUMP_ADDR_207
209
+ JUMP_ADDR_208
210
+ JUMP_ADDR_209
211
+ JUMP_ADDR_210
212
+ JUMP_ADDR_211
213
+ JUMP_ADDR_212
214
+ JUMP_ADDR_213
215
+ JUMP_ADDR_214
216
+ JUMP_ADDR_215
217
+ JUMP_ADDR_216
218
+ JUMP_ADDR_217
219
+ JUMP_ADDR_218
220
+ JUMP_ADDR_219
221
+ JUMP_ADDR_220
222
+ JUMP_ADDR_221
223
+ JUMP_ADDR_222
224
+ JUMP_ADDR_223
225
+ JUMP_ADDR_224
226
+ JUMP_ADDR_225
227
+ JUMP_ADDR_226
228
+ JUMP_ADDR_227
229
+ JUMP_ADDR_228
230
+ JUMP_ADDR_229
231
+ JUMP_ADDR_230
232
+ JUMP_ADDR_231
233
+ JUMP_ADDR_232
234
+ JUMP_ADDR_233
235
+ JUMP_ADDR_234
236
+ JUMP_ADDR_235
237
+ JUMP_ADDR_236
238
+ JUMP_ADDR_237
239
+ JUMP_ADDR_238
240
+ JUMP_ADDR_239
241
+ JUMP_ADDR_240
242
+ JUMP_ADDR_241
243
+ JUMP_ADDR_242
244
+ JUMP_ADDR_243
245
+ JUMP_ADDR_244
246
+ JUMP_ADDR_245
247
+ JUMP_ADDR_246
248
+ JUMP_ADDR_247
249
+ JUMP_ADDR_248
250
+ JUMP_ADDR_249
251
+ JUMP_ADDR_250
252
+ JUMP_ADDR_251
253
+ JUMP_ADDR_252
254
+ JUMP_ADDR_253
255
+ JUMP_ADDR_254
256
+ JUMP_ADDR_255
257
+ JUMP_ADDR_256
258
+ JUMP_ADDR_257
259
+ JUMP_ADDR_258
260
+ JUMP_ADDR_259
261
+ JUMP_ADDR_260
262
+ JUMP_ADDR_261
263
+ JUMP_ADDR_262
264
+ JUMP_ADDR_263
265
+ JUMP_ADDR_264
266
+ JUMP_ADDR_265
267
+ JUMP_ADDR_266
268
+ JUMP_ADDR_267
269
+ JUMP_ADDR_268
270
+ JUMP_ADDR_269
271
+ JUMP_ADDR_270
272
+ JUMP_ADDR_271
273
+ JUMP_ADDR_272
274
+ JUMP_ADDR_273
275
+ JUMP_ADDR_274
276
+ JUMP_ADDR_275
277
+ JUMP_ADDR_276
278
+ JUMP_ADDR_277
279
+ JUMP_ADDR_278
280
+ JUMP_ADDR_279
281
+ JUMP_ADDR_280
282
+ JUMP_ADDR_281
283
+ JUMP_ADDR_282
284
+ JUMP_ADDR_283
285
+ JUMP_ADDR_284
286
+ JUMP_ADDR_285
287
+ JUMP_ADDR_286
288
+ JUMP_ADDR_287
289
+ JUMP_ADDR_288
290
+ JUMP_ADDR_289
291
+ JUMP_ADDR_290
292
+ JUMP_ADDR_291
293
+ JUMP_ADDR_292
294
+ JUMP_ADDR_293
295
+ JUMP_ADDR_294
296
+ JUMP_ADDR_295
297
+ JUMP_ADDR_296
298
+ JUMP_ADDR_297
299
+ JUMP_ADDR_298
300
+ JUMP_ADDR_299
301
+ JUMP_ADDR_300
302
+ JUMP_ADDR_301
303
+ JUMP_ADDR_302
304
+ JUMP_ADDR_303
305
+ JUMP_ADDR_304
306
+ JUMP_ADDR_305
307
+ JUMP_ADDR_306
308
+ JUMP_ADDR_307
309
+ JUMP_ADDR_308
310
+ JUMP_ADDR_309
311
+ JUMP_ADDR_310
312
+ JUMP_ADDR_311
313
+ JUMP_ADDR_312
314
+ JUMP_ADDR_313
315
+ JUMP_ADDR_314
316
+ JUMP_ADDR_315
317
+ JUMP_ADDR_316
318
+ JUMP_ADDR_317
319
+ JUMP_ADDR_318
320
+ JUMP_ADDR_319
321
+ JUMP_ADDR_320
322
+ JUMP_ADDR_321
323
+ JUMP_ADDR_322
324
+ JUMP_ADDR_323
325
+ JUMP_ADDR_324
326
+ JUMP_ADDR_325
327
+ JUMP_ADDR_326
328
+ JUMP_ADDR_327
329
+ JUMP_ADDR_328
330
+ JUMP_ADDR_329
331
+ JUMP_ADDR_330
332
+ JUMP_ADDR_331
333
+ JUMP_ADDR_332
334
+ JUMP_ADDR_333
335
+ JUMP_ADDR_334
336
+ JUMP_ADDR_335
337
+ JUMP_ADDR_336
338
+ JUMP_ADDR_337
339
+ JUMP_ADDR_338
340
+ JUMP_ADDR_339
341
+ JUMP_ADDR_340
342
+ JUMP_ADDR_341
343
+ JUMP_ADDR_342
344
+ JUMP_ADDR_343
345
+ JUMP_ADDR_344
346
+ JUMP_ADDR_345
347
+ JUMP_ADDR_346
348
+ JUMP_ADDR_347
349
+ JUMP_ADDR_348
350
+ JUMP_ADDR_349
351
+ JUMP_ADDR_350
352
+ JUMP_ADDR_351
353
+ JUMP_ADDR_352
354
+ JUMP_ADDR_353
355
+ JUMP_ADDR_354
356
+ JUMP_ADDR_355
357
+ JUMP_ADDR_356
358
+ JUMP_ADDR_357
359
+ JUMP_ADDR_358
360
+ JUMP_ADDR_359
361
+ JUMP_ADDR_360
362
+ JUMP_ADDR_361
363
+ JUMP_ADDR_362
364
+ JUMP_ADDR_363
365
+ JUMP_ADDR_364
366
+ JUMP_ADDR_365
367
+ JUMP_ADDR_366
368
+ JUMP_ADDR_367
369
+ JUMP_ADDR_368
370
+ JUMP_ADDR_369
371
+ JUMP_ADDR_370
372
+ JUMP_ADDR_371
373
+ JUMP_ADDR_372
374
+ JUMP_ADDR_373
375
+ JUMP_ADDR_374
376
+ JUMP_ADDR_375
377
+ JUMP_ADDR_376
378
+ JUMP_ADDR_377
379
+ JUMP_ADDR_378
380
+ JUMP_ADDR_379
381
+ JUMP_ADDR_380
382
+ JUMP_ADDR_381
383
+ JUMP_ADDR_382
384
+ JUMP_ADDR_383
385
+ JUMP_ADDR_384
386
+ JUMP_ADDR_385
387
+ JUMP_ADDR_386
388
+ JUMP_ADDR_387
389
+ JUMP_ADDR_388
390
+ JUMP_ADDR_389
391
+ JUMP_ADDR_390
392
+ JUMP_ADDR_391
393
+ JUMP_ADDR_392
394
+ JUMP_ADDR_393
395
+ JUMP_ADDR_394
396
+ JUMP_ADDR_395
397
+ JUMP_ADDR_396
398
+ JUMP_ADDR_397
399
+ JUMP_ADDR_398
400
+ JUMP_ADDR_399
401
+ JUMP_ADDR_400
402
+ JUMP_ADDR_401
403
+ JUMP_ADDR_402
404
+ JUMP_ADDR_403
405
+ JUMP_ADDR_404
406
+ JUMP_ADDR_405
407
+ JUMP_ADDR_406
408
+ JUMP_ADDR_407
409
+ JUMP_ADDR_408
410
+ JUMP_ADDR_409
411
+ JUMP_ADDR_410
412
+ JUMP_ADDR_411
413
+ JUMP_ADDR_412
414
+ JUMP_ADDR_413
415
+ JUMP_ADDR_414
416
+ JUMP_ADDR_415
417
+ JUMP_ADDR_416
418
+ JUMP_ADDR_417
419
+ JUMP_ADDR_418
420
+ JUMP_ADDR_419
421
+ JUMP_ADDR_420
422
+ JUMP_ADDR_421
423
+ JUMP_ADDR_422
424
+ JUMP_ADDR_423
425
+ JUMP_ADDR_424
426
+ JUMP_ADDR_425
427
+ JUMP_ADDR_426
428
+ JUMP_ADDR_427
429
+ JUMP_ADDR_428
430
+ JUMP_ADDR_429
431
+ JUMP_ADDR_430
432
+ JUMP_ADDR_431
433
+ JUMP_ADDR_432
434
+ JUMP_ADDR_433
435
+ JUMP_ADDR_434
436
+ JUMP_ADDR_435
437
+ JUMP_ADDR_436
438
+ JUMP_ADDR_437
439
+ JUMP_ADDR_438
440
+ JUMP_ADDR_439
441
+ JUMP_ADDR_440
442
+ JUMP_ADDR_441
443
+ JUMP_ADDR_442
444
+ JUMP_ADDR_443
445
+ JUMP_ADDR_444
446
+ JUMP_ADDR_445
447
+ JUMP_ADDR_446
448
+ JUMP_ADDR_447
449
+ JUMP_ADDR_448
450
+ JUMP_ADDR_449
451
+ JUMP_ADDR_450
452
+ JUMP_ADDR_451
453
+ JUMP_ADDR_452
454
+ JUMP_ADDR_453
455
+ JUMP_ADDR_454
456
+ JUMP_ADDR_455
457
+ JUMP_ADDR_456
458
+ JUMP_ADDR_457
459
+ JUMP_ADDR_458
460
+ JUMP_ADDR_459
461
+ JUMP_ADDR_460
462
+ JUMP_ADDR_461
463
+ JUMP_ADDR_462
464
+ JUMP_ADDR_463
465
+ JUMP_ADDR_464
466
+ JUMP_ADDR_465
467
+ JUMP_ADDR_466
468
+ JUMP_ADDR_467
469
+ JUMP_ADDR_468
470
+ JUMP_ADDR_469
471
+ JUMP_ADDR_470
472
+ JUMP_ADDR_471
473
+ JUMP_ADDR_472
474
+ JUMP_ADDR_473
475
+ JUMP_ADDR_474
476
+ JUMP_ADDR_475
477
+ JUMP_ADDR_476
478
+ JUMP_ADDR_477
479
+ JUMP_ADDR_478
480
+ JUMP_ADDR_479
481
+ JUMP_ADDR_480
482
+ JUMP_ADDR_481
483
+ JUMP_ADDR_482
484
+ JUMP_ADDR_483
485
+ JUMP_ADDR_484
486
+ JUMP_ADDR_485
487
+ JUMP_ADDR_486
488
+ JUMP_ADDR_487
489
+ JUMP_ADDR_488
490
+ JUMP_ADDR_489
491
+ JUMP_ADDR_490
492
+ JUMP_ADDR_491
493
+ JUMP_ADDR_492
494
+ JUMP_ADDR_493
495
+ JUMP_ADDR_494
496
+ JUMP_ADDR_495
497
+ JUMP_ADDR_496
498
+ JUMP_ADDR_497
499
+ JUMP_ADDR_498
500
+ JUMP_ADDR_499
501
+ JUMP_ADDR_500
502
+ JUMP_ADDR_501
503
+ JUMP_ADDR_502
504
+ JUMP_ADDR_503
505
+ JUMP_ADDR_504
506
+ JUMP_ADDR_505
507
+ JUMP_ADDR_506
508
+ JUMP_ADDR_507
509
+ JUMP_ADDR_508
510
+ JUMP_ADDR_509
511
+ JUMP_ADDR_510
512
+ JUMP_ADDR_511
513
+ [UNK]
514
+ endbr64
515
+ sub
516
+ rsp
517
+ CONST
518
+ mov
519
+ rax
520
+ cs:xxx
521
+ test
522
+ jz
523
+ call
524
+ add
525
+ retn
526
+ push
527
+ jmp
528
+ rdi
529
+ [rbx+CONST]
530
+ callfunc_xxx
531
+ rbp
532
+ jnz
533
+ movapd
534
+ xmm0
535
+ movups
536
+ [r12]
537
+ [r12+CONST]
538
+ [rsp+arg_xxx]
539
+ cmp
540
+ r15
541
+ r12
542
+ rbx
543
+ fs:xxx
544
+ [rsp+CONST+var_xxx]
545
+ xor
546
+ eax
547
+ lea
548
+ [CONST_VAR+CONST]
549
+ [CONST_VAR]
550
+ rsi
551
+ jbe
552
+ edx
553
+ [rbx]
554
+ dl
555
+ [rax]
556
+ rcx
557
+ rep
558
+ rdx
559
+ [rdx+rax]
560
+ GLOBAL_VAR
561
+ pop
562
+ [rbp+CONST]
563
+ edi
564
+ r13
565
+ [rax+CONST]
566
+ sub_xxx
567
+ r14
568
+ [rsp+CONST]
569
+ [rsp+CONST_VAR]
570
+ r8
571
+ [rsp+rax+arg_xxx]
572
+ movzx
573
+ [r14]
574
+ al
575
+ [r13+CONST]
576
+ ebp
577
+ dil
578
+ movsx
579
+ bpl
580
+ off_xxx
581
+ ebx
582
+ imul
583
+ [r14+CONST]
584
+ dec
585
+ ja
586
+ UNK_ADDR
587
+ movsxd
588
+ ds:xxx
589
+ sil
590
+ [rax+rbp+CONST]
591
+ esi
592
+ or
593
+ lock
594
+ nop
595
+ loc_xxx
596
+ unk_xxx
597
+ shr
598
+ sar
599
+ pxor
600
+ movdqu
601
+ [rdx]
602
+ setz
603
+ setnz
604
+ xmm1
605
+ [rax+rax+CONST]
606
+ jle
607
+ [rax+rcx*8]
608
+ jge
609
+ jg
610
+ jb
611
+ [rdx+CONST]
612
+ movdqa
613
+ xmm2
614
+ shl
615
+ paddd
616
+ and
617
+ [rcx+rax*4]
618
+ [rcx+CONST]
619
+ [rcx]
620
+ [rdx+rbx*8]
621
+ [rdx+r13*8]
622
+ movd
623
+ xmm3
624
+ ecx
625
+ pshufd
626
+ [rdx+rax*4]
627
+ [rcx+rsi*4]
628
+ [rdx+rsi*4]
629
+ [rax+r13*8]
630
+ jnb
631
+ [rdx+rsi*8]
632
+ [r8+CONST]
633
+ movq
634
+ [rax+rbx]
635
+ punpcklqdq
636
+ [rdx+rbx*4]
637
+ [r14+rbx*4]
638
+ r14d
639
+ r15d
640
+ cmovnz
641
+ setb
642
+ cl
643
+ [r15]
644
+ [CONST_VAR+rdx+CONST]
645
+ [CONST_VAR+rdx]
646
+ [r15+r12]
647
+ movaps
648
+ cmova
649
+ cmovnb
650
+ r9
651
+ [r15+rbx*4]
652
+ [rcx+rbx*4]
653
+ [r15+rbx*8]
654
+ [rcx+rbx*8]
655
+ movsd
656
+ xmm5
657
+ xmm4
658
+ comisd
659
+ maxsd
660
+ xmm6
661
+ minsd
662
+ xmm7
663
+ movhpd
664
+ [rsp+var_xxx]
665
+ [rsp+var_xxx+CONST]
666
+ [rbp+var_xxx+CONST]
667
+ [rbp+var_xxx]
668
+ movupd
669
+ [rax+r12]
670
+ [r12+rax+CONST]
671
+ [rbp+rax+CONST]
672
+ [CONST_VAR+r12]
673
+ [rsp+CONST+arg_xxx]
674
+ [rsp+CONST+var_xxx+CONST]
675
+ psubq
676
+ [r15+CONST]
677
+ cmovg
678
+ r8d
679
+ [rax+r14]
680
+ [CONST_VAR+r14]
681
+ xchg
682
+ ax
683
+ jns
684
+ js
685
+ [rsp+CONST+CONST_VAR]
686
+ [r9]
687
+ cdqe
688
+ r12d
689
+ bl
690
+ r13d
691
+ [r13+r14+CONST]
692
+ [rax+rax*2]
693
+ movss
694
+ unpcklps
695
+ movlps
696
+ [r14+r13]
697
+ [r14+r13+CONST]
698
+ [r8]
699
+ jl
700
+ [CONST_VAR+r14+CONST]
701
+ r10
702
+ cmovb
703
+ r11
704
+ [r14+r10]
705
+ [r11+r12]
706
+ [rax+r13]
707
+ [rax+rcx]
708
+ [CONST_VAR+rax]
709
+ [CONST_VAR+r13]
710
+ cmovbe
711
+ [rcx+rcx*2]
712
+ [rax+rcx*4]
713
+ [rbx+rbx*2]
714
+ [r15+rax*4]
715
+ [CONST_VAR+rax*4]
716
+ [CONST_VAR+rax*4+CONST]
717
+ [r13+rbp+CONST]
718
+ [r15+rbp]
719
+ comiss
720
+ [rsp+rdx*8+CONST+var_xxx]
721
+ movhlps
722
+ movlhps
723
+ [rax+r15]
724
+ [CONST_VAR+r15]
725
+ sbb
726
+ [rdx+r12]
727
+ [rdx+rbp]
728
+ [r8+rdx]
729
+ [r13+rax+CONST]
730
+ [r12+rax]
731
+ [rbp+rdx+CONST]
732
+ [r9+rdx]
733
+ unpcklpd
734
+ unpckhpd
735
+ not
736
+ ucomisd
737
+ setbe
738
+ pandn
739
+ andpd
740
+ andnpd
741
+ orpd
742
+ cmplepd
743
+ movhps
744
+ [rdx+rcx]
745
+ [r14+rbp]
746
+ [r9+CONST]
747
+ [rdx+rax*8]
748
+ [rdx+r13]
749
+ [r10+CONST]
750
+ cmovns
751
+ [r11+rax*8]
752
+ r10d
753
+ [r11]
754
+ [rbp+rdx*8+CONST]
755
+ cqo
756
+ [rax+rdx]
757
+ [rcx+rdx*8]
758
+ [r15+r14]
759
+ r11d
760
+ [r10]
761
+ [CONST_VAR+rcx*8]
762
+ r9d
763
+ cmovz
764
+ cmovl
765
+ setl
766
+ setnle
767
+ [rsp+CONST+CONST_VAR+CONST]
768
+ [rcx+rax]
769
+ [rcx+rax+CONST]
770
+ [rax+rax]
771
+ cdq
772
+ idiv
773
+ [r8+rbp]
774
+ [r8+rax*4]
775
+ [CONST_VAR+rcx*4]
776
+ [CONST_VAR+rcx*8+CONST]
777
+ [rax+CONST_VAR]
778
+ [CONST_VAR+rbp]
779
+ [rbp+rax*4+CONST]
780
+ [r10+r11+CONST]
781
+ [rdx+rdx]
782
+ [rax+r12*4]
783
+ [r9+r11+CONST]
784
+ [rax+rbx*4]
785
+ [rbp+rax*8+CONST]
786
+ [rcx+CONST_VAR]
787
+ div
788
+ [r11+CONST_VAR+CONST]
789
+ [r9+CONST_VAR+CONST]
790
+ [rax+rdx*8]
791
+ [r15+r13]
792
+ [rcx+r12]
793
+ [rbp+rbp*2+CONST]
794
+ [r14+rdx*8]
795
+ [r14+r12]
796
+ [rcx+rsi*8]
797
+ [r14+rax*8]
798
+ [r9+rdx*4]
799
+ punpckldq
800
+ [r12+rdx*4]
801
+ [r12+rax*4]
802
+ [CONST_VAR+rdi*4]
803
+ [r8+rax]
804
+ setnbe
805
+ [CONST_VAR+rcx*4+CONST]
806
+ [r8+rcx*4]
807
+ [r9+rcx*4]
808
+ [CONST_VAR+CONST_VAR]
809
+ [r9+r10+CONST]
810
+ [CONST_VAR+rcx+CONST]
811
+ [CONST_VAR+rdx*4]
812
+ [r9+r9]
813
+ [CONST_VAR+r9*4]
814
+ [CONST_VAR+rsi*2]
815
+ [CONST_VAR+r10*8]
816
+ [CONST_VAR+rdx*8]
817
+ [CONST_VAR+r8*8]
818
+ [CONST_VAR+rsi*8]
819
+ [rdx+rdx+CONST]
820
+ [r13+r12+CONST]
821
+ r8b
822
+ [r13+r13*2+CONST]
823
+ [r12+rax*4+CONST]
824
+ [r12+rax*8]
825
+ [r12+r13*8]
826
+ [CONST_VAR+r9+CONST]
827
+ [CONST_VAR+r9]
828
+ [rbp+r12+CONST]
829
+ cvtsi2sd
830
+ mulsd
831
+ cvttsd2si
832
+ [r12+r13]
833
+ addsd
834
+ subsd
835
+ btc
836
+ [r8+CONST_VAR]
837
+ neg
838
+ [r13+r15+CONST]
839
+ [rdx+rdx*4]
840
+ [rcx+rsi*2+CONST]
841
+ [rax+r13*4]
842
+ [rax+rdx*4]
843
+ cmovge
844
+ cmovle
845
+ [r8+r13]
846
+ [r8+r15]
847
+ [rcx+rdx]
848
+ [rcx+r15]
849
+ [rdx+rcx*4]
850
+ [rax+rbx*8]
851
+ [r13+rbx+CONST]
852
+ adc
853
+ [rcx+rdx*4]
854
+ [rdx+rbp*8]
855
+ [r8+rcx]
856
+ [rcx+rdx+CONST]
857
+ [rax+rdx+CONST]
858
+ [r12+r15]
859
+ bsr
860
+ [rdx+rcx*8]
861
+ [rax+rdi*4]
862
+ [rax+rdi*8]
863
+ [r15+CONST_VAR]
864
+ [r15+CONST_VAR+CONST]
865
+ [CONST_VAR+r8]
866
+ [r8+rcx+CONST]
867
+ [r9+r11*8]
868
+ [r8+r12]
869
+ [r8+rbx*8]
870
+ [CONST_VAR+rbx*8]
871
+ [CONST_VAR+CONST_VAR+CONST]
872
+ [rax+rax*4]
873
+ [CONST_VAR+r15+CONST]
874
+ r15b
875
+ [rbx+r14*8]
876
+ [rbx+rax+CONST]
877
+ [r14+CONST_VAR]
878
+ [r14+CONST_VAR+CONST]
879
+ [r14+rcx+CONST]
880
+ r13b
881
+ [r12+rbp]
882
+ [r8+rdx*4+CONST]
883
+ [rax+rbp*4]
884
+ [r13+rbp*4+CONST]
885
+ [r13+rax*4+CONST]
886
+ [rbp+r15*4+CONST]
887
+ [rsp+rax+CONST+var_xxx]
888
+ [r11+rax*4]
889
+ [r9+rax*4]
890
+ [r12+rdx*8]
891
+ [rsp+rax*4+CONST+var_xxx]
892
+ r10b
893
+ [rbx+r12*8]
894
+ ud2
895
+ [rax+rax*2+CONST]
896
+ bt
897
+ [rbp+rbx+CONST]
898
+ [r10+r15]
899
+ [r15+r10]
900
+ [r15+rcx+CONST]
901
+ r9b
902
+ [r15+rcx]
903
+ [rbp+r15+CONST]
904
+ [rax+r10]
905
+ r14b
906
+ [r10+rdx]
907
+ [rdx+r10]
908
+ [rbp+r10+CONST]
909
+ [r14+rdx]
910
+ [r12+r14+CONST]
911
+ [r12+rcx]
912
+ mul
913
+ [r12+CONST_VAR]
914
+ [r12+rdx]
915
+ [r12+rbx]
916
+ [rsp+r8+CONST+var_xxx]
917
+ [rsp+CONST_VAR+CONST+var_xxx]
918
+ [r14+r9]
919
+ [r14+rax]
920
+ [r8+r8*2]
921
+ [rdx+rcx*2+CONST]
922
+ [rcx+rax*8]
923
+ [rax+rbp*8]
924
+ [rax+r12*8]
925
+ [rcx+r12*4]
926
+ [r12+r10]
927
+ [r11+CONST]
928
+ setnb
929
+ r12b
930
+ movmskpd
931
+ xorpd
932
+ jp
933
+ dx
934
+ fld
935
+ fstp
936
+ fst
937
+ fchs
938
+ fucomip
939
+ st
940
+ fabs
941
+ fxch
942
+ r10w
943
+ [r14+rax*4]
944
+ [CONST_VAR+r12*8]
945
+ [CONST_VAR+rax*8]
946
+ [r8+rdx*2+CONST]
947
+ [r8+rdx*2]
948
+ [CONST_VAR+r10]
949
+ r11b
950
+ [r8+rcx*2+CONST]
951
+ [r8+rcx*2]
952
+ [rax+rax*8]
953
+ [r14+r14*8]
954
+ [CONST_VAR+rdi*8]
955
+ [rcx+rcx*8]
956
+ [r13+rax*8+CONST]
957
+ [r8+r8*8]
958
+ [CONST_VAR+rsi*8+CONST]
959
+ [rdx+rdx*8]
960
+ [CONST_VAR+rbx]
961
+ cx
962
+ si
963
+ jo
964
+ mulss
965
+ addss
966
+ cvtsi2ss
967
+ addps
968
+ cvtps2pd
969
+ cvtss2sd
970
+ pcmpgtb
971
+ pand
972
+ por
973
+ psrldq
974
+ pcmpeqd
975
+ pmaxub
976
+ pminub
977
+ pshuflw
978
+ bh
979
+ ah
980
+ pmaxsw
981
+ pminsw
982
+ [CONST_VAR+rax*2]
983
+ pextrw
984
+ bp
985
+ r13w
986
+ psubusw
987
+ paddw
988
+ pcmpeqw
989
+ pcmpgtd
990
+ [rcx+r9*4]
991
+ cvtdq2pd
992
+ psubd
993
+ minss
994
+ maxss
995
+ shufps
996
+ [CONST_VAR+r11*8]
997
+ [rdx+rdx*2]
998
+ xmm8
999
+ xmm9
1000
+ packuswb
1001
+ psrlw
1002
+ [rbp+rcx*4+CONST]
1003
+ [rax+rcx*8+CONST]
1004
+ [rax+r10*8]
1005
+ [rdx+r9]
1006
+ [rax+r11*8]
1007
+ [rdx+rdi*8]
1008
+ [rbx+rax]
1009
+ [r13+r15*4+CONST]
1010
+ [r13+r15*8+CONST]
1011
+ [r12+r15*8]
1012
+ [r12+r14*8]
1013
+ [rbx+r14]
1014
+ [r14+r15]
1015
+ [rbx+r12]
1016
+ [rax+r14*8]
1017
+ [rax+rcx+CONST]
1018
+ [r13+rdx+CONST]
1019
+ cvtpd2ps
1020
+ cmovs
1021
+ subpd
1022
+ divpd
1023
+ mulpd
1024
+ addpd
1025
+ divsd
1026
+ andps
1027
+ ucomiss
1028
+ [rax+rsi*4]
1029
+ [r8+rcx*8]
1030
+ [rcx+r12*8]
1031
+ [r12+r12*2]
1032
+ [r8+rdi*8]
1033
+ [r8+rax*8]
1034
+ [rax+r13+CONST]
1035
+ subss
1036
+ mulps
1037
+ [r15+rcx*8]
1038
+ [r8+r10*8]
1039
+ [r8+rdx*8]
1040
+ cvtsd2ss
1041
+ [r10+r10*2]
1042
+ [CONST_VAR+r9*8]
1043
+ [rbx+rcx*8]
1044
+ [r11+rcx*4]
1045
+ [r8+r11]
1046
+ [rax+r10*4]
1047
+ [CONST_VAR+r12+CONST]
1048
+ divss
1049
+ cvttss2si
1050
+ [CONST_VAR+r8*8+CONST]
1051
+ [r9+r9*2]
1052
+ [rax+r8]
1053
+ [rax+r8+CONST]
1054
+ [rax+rdx*4+CONST]
1055
+ [r8+rsi*8+CONST]
1056
+ [rcx+rsi*4+CONST]
1057
+ [r8+r9*8]
1058
+ [r9+r8*4+CONST]
1059
+ setp
1060
+ sqrtss
1061
+ xorps
1062
+ [r14+rcx]
1063
+ [rax+rdx*8+CONST]
1064
+ [rsp+CONST+arg_xxx+CONST]
1065
+ [rax+rsi*8]
1066
+ extrn
1067
+ extrn_xxx
1068
+ inc
1069
+ [rbx+rax*8]
1070
+ dh
1071
+ [r8+rsi*8]
1072
+ [rdx+rax*8+CONST]
1073
+ [rcx+rax*8+CONST]
1074
+ [CONST_VAR+rax+CONST]
1075
+ [CONST_VAR+rax*8+CONST]
1076
+ [CONST_VAR+r10*8+CONST]
1077
+ [CONST_VAR+r9*8+CONST]
1078
+ [r12+rbx*8]
1079
+ [rbp+r14*8+CONST]
1080
+ [r10+rax*8]
1081
+ [rcx+r13]
1082
+ r12w
1083
+ r14w
1084
+ [CONST_VAR+rcx]
1085
+ ch
1086
+ [rbx+r9*8]
1087
+ [r12+rbp*8+CONST]
1088
+ [rsp+rdx+CONST+var_xxx]
1089
+ [r8+rax*8+CONST]
1090
+ [r8+rbx*8+CONST]
1091
+ [r15+rbp*8+CONST]
1092
+ [rdx+r13*4]
1093
+ [r8+r8*2+CONST]
1094
+ [rcx+rbp*4]
1095
+ [r14+r13*8+CONST]
1096
+ [CONST_VAR+rdx*8+CONST]
1097
+ [r9+rcx*8+CONST]
1098
+ [r9+rax*8]
1099
+ [rcx+rbx]
1100
+ [rdx+rbx]
1101
+ [r9+rsi*8]
1102
+ [rcx+r14]
1103
+ [r9+rax*8+CONST]
1104
+ [r9+r13*8+CONST]
1105
+ [rax+r15*8]
1106
+ [rbp+rbx*8+CONST]
1107
+ [rsp+rbp+CONST+var_xxx]
1108
+ movddup
1109
+ [r15+rbx*8+CONST]
1110
+ [rsp+rcx+CONST+var_xxx]
1111
+ [rdx+r12*4]
1112
+ [r12+rax*8+CONST]
1113
+ [r12+rbx*8+CONST]
1114
+ [rbx+r15]
1115
+ [rbx+r15+CONST]
1116
+ [rcx+rcx]
1117
+ [rbx+r14+CONST]
1118
+ [r11+rax]
1119
+ [r12+rbx+CONST]
1120
+ [r10+r10*4]
1121
+ [r9+r10*4]
1122
+ [rbx+r12+CONST]
1123
+ [rbp+r14+CONST]
1124
+ [rbp+rdi*4+CONST]
1125
+ [rbx+CONST_VAR]
1126
+ paddq
1127
+ [rdx+rsi*8+CONST]
1128
+ [CONST_VAR+r14*8]
1129
+ [rcx+rbp*8]
1130
+ btr
1131
+ [r15+r14+CONST]
1132
+ [r15+rax*8]
1133
+ [rbx+rdx]
1134
+ [r12+r14*8+CONST]
1135
+ [r10+rax*8+CONST]
1136
+ [r10+rdx*8+CONST]
1137
+ [r8+rcx*8+CONST]
1138
+ [r14+rbp*8]
1139
+ [CONST_VAR+rbp*8]
1140
+ [r14+rbx*8]
1141
+ [r13+r12*8+CONST]
1142
+ [r14+rbx*8+CONST]
1143
+ [CONST_VAR+r11*8+CONST]
1144
+ [rcx+rdx*8+CONST]
1145
+ [rbp+r15*8+CONST]
1146
+ [r14+r15*8]
1147
+ setnl
1148
+ cmpnltsd
1149
+ [r14+r15*4]
1150
+ cmpnlesd
1151
+ [rcx+rcx*2+CONST]
1152
+ [rax+r9*8]
1153
+ [r15+rdx*4]
1154
+ [r12+rdx+CONST]
1155
+ sqrtsd
1156
+ [rsp+rax*8+CONST+var_xxx]
1157
+ [r15+rbx*4+CONST]
1158
+ [r12+rbx*4]
1159
+ [rbp+rbx*4+CONST]
1160
+ [r13+r14*4+CONST]
1161
+ [r13+rbx*4+CONST]
1162
+ [r12+r15*4+CONST]
1163
+ [r12+r14*4+CONST]
1164
+ [rbx+rax*4]
1165
+ [rbx+rdx*4]
1166
+ [r15+rax*4+CONST]
1167
+ [r15+rsi*4+CONST]
1168
+ [r13+CONST_VAR+CONST]
1169
+ [r15+rcx*4+CONST]
1170
+ [r13+rsi*4+CONST]
1171
+ [r13+r8*4+CONST]
1172
+ [r13+rcx*4+CONST]
1173
+ cvttps2dq
1174
+ cmpltps
1175
+ punpckhdq
1176
+ [r14+rdx*4]
1177
+ [rbp+rsi*4+CONST]
1178
+ [rbp+rdx*4+CONST]
1179
+ [r11+r11*2]
1180
+ [r15+r11+CONST]
1181
+ [r11+r15+CONST]
1182
+ [rbp+r11*4+CONST]
1183
+ [r15+rdx+CONST]
1184
+ [rdx+r15+CONST]
1185
+ [r15+r15*2]
1186
+ [rdx+rax*4+CONST]
1187
+ [rcx+r15+CONST]
1188
+ [r15+rax+CONST]
1189
+ [rax+r15+CONST]
1190
+ [rbp+r9*4+CONST]
1191
+ [rbp+r8*4+CONST]
1192
+ [CONST_VAR+rsi*4+CONST]
1193
+ [rcx+rdi*8]
1194
+ [r10+rdi*4]
1195
+ [rcx+r8+CONST]
1196
+ [r10+r9+CONST]
1197
+ [rdx+r8+CONST]
1198
+ [rax+r9+CONST]
1199
+ [rdx+r12*8]
1200
+ [rax+rbp]
1201
+ [r10+rsi*4]
1202
+ [r9+rsi*4]
1203
+ [r8+rsi*4]
1204
+ [r12+rsi*4]
1205
+ [r14+rsi*4]
1206
+ [r11+rsi*4]
1207
+ [rbx+rsi*4]
1208
+ [r15+rsi*4]
1209
+ [r11+rbp*8]
1210
+ [CONST_VAR+rsi*4]
1211
+ [r15+rax]
1212
+ [r15+r8]
1213
+ [r8+r14]
1214
+ [rbx+r12*8+CONST]
1215
+ [r15+rax*8+CONST]
1216
+ [r14+rax*8+CONST]
1217
+ [r12+r9]
1218
+ [rbp+rsi*8+CONST]
1219
+ [r8+rdx*4]
1220
+ [r14+r12*4]
1221
+ [rbx+r12*4]
1222
+ [r14+r13*4]
1223
+ [r13+r12*4+CONST]
1224
+ [rbx+r13*4]
1225
+ [r15+r14*4]
1226
+ [rbp+CONST_VAR]
1227
+ [r14+r12*8]
1228
+ [r15+r12*4]
1229
+ [rcx+r8]
1230
+ [rbp+rcx+CONST]
1231
+ setle
1232
+ [rbp+rdi*8+CONST]
1233
+ [r11+rcx]
1234
+ [r9+rcx]
1235
+ [rbp+rcx*8+CONST]
1236
+ subps
1237
+ unpckhps
1238
+ [rbp+rax*2+CONST]
1239
+ [r13+rcx+CONST]
1240
+ [rbx+rcx+CONST]
1241
+ [rbp+CONST_VAR+CONST]
1242
+ [r13+rbx*8+CONST]
1243
+ [rax+rbx*8+CONST]
1244
+ psrad
1245
+ punpcklwd
1246
+ punpckhwd
1247
+ psubb
1248
+ [rbx+r10+CONST]
1249
+ [rbx+r10]
1250
+ [r9+CONST_VAR]
1251
+ [rbx+r11+CONST]
1252
+ [rbx+r11]
1253
+ [r13+r9+CONST]
1254
+ [rax+r13*8+CONST]
1255
+ cmpltsd
1256
+ [rbx+CONST_VAR+CONST]
1257
+ [rax+rax*4+CONST]
1258
+ [CONST_VAR+rsi*2+CONST]
1259
+ [CONST_VAR+rdi*2]
1260
+ [r12+rsi*8]
1261
+ [rsp+rax+CONST+CONST_VAR]
1262
+ [rax+rbx+CONST]
1263
+ shufpd
1264
+ [rbp+rax+var_xxx]
1265
+ [rbp+rdx+var_xxx]
1266
+ [rbx+rax*8+CONST]
1267
+ [rax+CONST_VAR+CONST]
1268
+ jnp
1269
+ [rdx+CONST_VAR]
1270
+ setnp
1271
+ [rdx+r14*8]
1272
+ [rax+r14*4]
1273
+ [rdx+r15]
1274
+ [rdx+rax+CONST]
1275
+ [rbp+r13+CONST]
1276
+ [rdx+rcx*8+CONST]
1277
+ [r13+r8*8+CONST]
1278
+ [r13+rsi*8+CONST]
1279
+ [rbx+rbx]
1280
+ [rcx+rbx*2]
1281
+ [rdx+rdi*4]
1282
+ [rax+rdx*2]
1283
+ [rax+rbx*2]
1284
+ [r14+r14]
1285
+ [rbp+rbp+CONST]
1286
+ [rcx+rbp*2]
1287
+ [rdx+rax*2]
1288
+ [r8+r9]
1289
+ [r8+r9+CONST]
1290
+ [rcx+r9]
1291
+ [rax+r9]
1292
+ [r11+CONST_VAR]
1293
+ [r9+r11]
1294
+ [rcx+r11]
1295
+ [rax+r11]
1296
+ [rcx+r9+CONST]
1297
+ [r10+CONST_VAR]
1298
+ [rcx+r10]
1299
+ [rcx+r10+CONST]
1300
+ [rdx+r8]
1301
+ [r9+r10]
1302
+ [rcx+rax*2]
1303
+ r11w
1304
+ [r15+rdx]
1305
+ r15w
1306
+ [CONST_VAR+rbx+CONST]
1307
+ [r8+rbx]
1308
+ [r10+rax+CONST]
1309
+ [rbx+rcx]
1310
+ [rdx+rcx*2]
1311
+ [r9+r12]
1312
+ [rdx+r9+CONST]
1313
+ [r11+rdx+CONST]
1314
+ [rcx+CONST_VAR+CONST]
1315
+ bx
1316
+ [r15+rbx]
1317
+ [r15+rbp*8]
1318
+ [r15+r14*8]
1319
+ [r15+rsi*8]
1320
+ [r14+r14+CONST]
1321
+ [rbx+rbp*8]
1322
+ [rax+r14*2]
1323
+ [r9+rax*2]
1324
+ r8w
1325
+ [CONST_VAR+rdx*2]
1326
+ [r9+rdx*2]
1327
+ [rcx+r8*8]
1328
+ [r10+rcx]
1329
+ [r8+r10]
1330
+ [r8+r10+CONST]
1331
+ [r9+rax]
1332
+ [r11+r9]
1333
+ [rdx+r10+CONST]
1334
+ [r8+rax*4+CONST]
1335
+ [r10+rbp+CONST]
1336
+ [rbx+rbp+CONST]
1337
+ [rdx+r9*4]
1338
+ [rcx+r14*4]
1339
+ [rcx+r13*4]
1340
+ [rcx+r15*4]
1341
+ [r10+rax*4]
1342
+ [r10+rax]
1343
+ [r9+rbp+CONST]
1344
+ [r9+rbx+CONST]
1345
+ [r10+r12+CONST]
1346
+ [r8+r13*4]
1347
+ [r9+r12*4]
1348
+ [r8+r15*4]
1349
+ [r9+r15*4]
1350
+ [rbx+rax*4+CONST]
1351
+ [r11+rax+CONST]
1352
+ [CONST_VAR+r10*4]
1353
+ [rdx+r14+CONST]
1354
+ [r11+r13+CONST]
1355
+ [r10+rax*4+CONST]
1356
+ [r9+rax*4+CONST]
1357
+ [r11+rbp+CONST]
1358
+ [rcx+r11*4]
1359
+ [CONST_VAR+r11*4]
1360
+ [r13+r11*4+CONST]
1361
+ [r12+r11*4+CONST]
1362
+ [CONST_VAR+rbx*4]
1363
+ [r10+rcx+CONST]
1364
+ [r12+rsi*4+CONST]
1365
+ [r8+r14*4]
1366
+ [r8+rbp*4]
1367
+ [r9+rbp*4]
1368
+ [r9+r13*4]
1369
+ [r12+rcx*4+CONST]
1370
+ [r14+rax+CONST]
1371
+ [r15+rcx*4]
1372
+ [rbx+rcx*4]
1373
+ [r11+rax*4+CONST]
1374
+ [r15+r10*4]
1375
+ [rbx+r11*4]
1376
+ [r8+rax+CONST]
1377
+ [r10+rdx*4]
1378
+ [r14+r8*4]
1379
+ [rbx+r8*4]
1380
+ [r15+r8*4]
1381
+ [r15+rdi*4]
1382
+ [rdx+r10*4]
1383
+ [rcx+rax*4+CONST]
1384
+ [r13+r10*4+CONST]
1385
+ [rdx+r8*4]
1386
+ [rax+r11*4]
1387
+ [rdx+r11*4]
1388
+ [rcx+r10*4]
1389
+ [r15+r13*4+CONST]
1390
+ [rax+r9*4]
1391
+ [r12+r13*4+CONST]
1392
+ [r10+rbx+CONST]
1393
+ [r14+rbx]
1394
+ [r8+rbx*4]
1395
+ [r9+rbx*4]
1396
+ [r8+r10*4]
1397
+ [r9+rdi*4]
1398
+ [r12+rcx*4]
1399
+ [r12+r11*4]
1400
+ [rdx+r12+CONST]
1401
+ [rdx+CONST_VAR+CONST]
1402
+ [rdx+r13+CONST]
1403
+ [r12+r13*4]
1404
+ [r15+r13*4]
1405
+ [rdx+rbp*4]
1406
+ [r14+rbp*4]
1407
+ [r15+rbp*4]
1408
+ [rbx+rbp*4]
1409
+ [rsp+r8*4+CONST+var_xxx]
1410
+ r9w
1411
+ di
1412
+ [rdx+r14]
1413
+ [rax+r14+CONST]
1414
+ [rbx+rcx*4+CONST]
1415
+ [rbx+rsi*4+CONST]
1416
+ cmpnless
1417
+ andnps
1418
+ orps
1419
+ [rbx+r8*4+CONST]
1420
+ [rbx+r11*4+CONST]
1421
+ [rbx+rdi*4+CONST]
1422
+ [rbx+rdx*4+CONST]
1423
+ [rbx+r10*4+CONST]
1424
+ [r9+rbx]
1425
+ [r13+rbp*8+CONST]
1426
+ [r13+rcx*8+CONST]
1427
+ [CONST_VAR+r8+CONST]
1428
+ [r9+r14*8+CONST]
1429
+ [rsp+rbx+CONST+var_xxx]
1430
+ [rcx+rbp]
1431
+ [rbx+r14*8+CONST]
1432
+ [rbp+r12*4+CONST]
1433
+ [r8+rbp*8]
1434
+ [r12+rbp*8]
1435
+ [rax+rdx*2+CONST]
1436
+ [r14+rbx+CONST]
1437
+ [rcx+rdx*2+CONST]
1438
+ bswap
1439
+ hlt
1440
+ [rsp+CONST_VAR+CONST+CONST_VAR]
1441
+ [rsp+rdx+CONST+CONST_VAR]
1442
+ [r12+rcx*8]
1443
+ [r12+rcx*8+CONST]
1444
+ [r13+rdx*4+CONST]
1445
+ [r12+rbx*4+CONST]
1446
+ [CONST_VAR+rax*2+CONST]
1447
+ [CONST_VAR+rcx*2+CONST]
1448
+ [rbx+rdx+CONST]
1449
+ [rax+rbx*4+CONST]
1450
+ [rsp+r13*4+CONST+var_xxx]
1451
+ pslldq
1452
+ [rbx+rbx*4]
1453
+ [rcx+rdx*2]
1454
+ [r13+r8+CONST]
1455
+ [rax+r10+CONST]
1456
+ [rbx+r8]
1457
+ [r14+rax*2+CONST]
1458
+ [rbx+rbp]
1459
+ [r8+rdx+CONST]
1460
+ [r8+CONST_VAR+CONST]
1461
+ [r9+r13+CONST]
1462
+ [r8+r8*4]
1463
+ [rax+rbp*2+CONST]
1464
+ [r8+rax*2+CONST]
1465
+ [r8+r9*2+CONST]
1466
+ [r12+r12*4]
1467
+ [rbx+rax*2+CONST]
1468
+ [rbx+rdx*8+CONST]
1469
+ [rbx+r12*4+CONST]
1470
+ bts
1471
+ [rsp+r14*4+CONST+var_xxx]
1472
+ [rax+r12+CONST]
1473
+ [rsp+rbx+CONST+CONST_VAR]
1474
+ [CONST_VAR+rcx*2]
1475
+ [r8+rbp*8+CONST]
1476
+ [r13+rdx*8+CONST]
1477
+ [rcx+rax*2+CONST]
1478
+ [rdx+rax*2+CONST]
1479
+ [rbx+r13]
1480
+ [r12+r15+CONST]
1481
+ [rdx+rdi*2]
1482
+ [rdx+r11]
1483
+ [r12+r14]
1484
+ [r9+r9*4]
1485
+ [rcx+rcx*4]
1486
+ [r11+rdx*8]
1487
+ [r15+r13*8]
1488
+ [rbx+rcx*8+CONST]
1489
+ [rcx+rbx*8+CONST]
1490
+ [rbx+rbp*8+CONST]
1491
+ [r12+rsi*8+CONST]
1492
+ [r12+rdx*8+CONST]
1493
+ [rbx+rsi*8+CONST]
1494
+ [rax+r14*8+CONST]
1495
+ [r9+r8]
1496
+ [rdx+r9*8]
1497
+ [r8+rdi*8+CONST]
1498
+ [r12+r9*4]
1499
+ [rbx+r14*4]
1500
+ [rbx+r14*4+CONST]
1501
+ [rcx+rsi*8+CONST]
1502
+ [r13+r13+CONST]
1503
+ [rbx+rbx+CONST]
1504
+ [rbp+r13*8+CONST]
1505
+ [r15+rdx*8]
1506
+ [r12+CONST_VAR+CONST]
1507
+ [rsp+r14+CONST+var_xxx]
1508
+ [r8+r8+CONST]
1509
+ [CONST_VAR+rbx*8+CONST]
1510
+ [CONST_VAR+r14*8+CONST]
1511
+ [rcx+r13*8+CONST]
1512
+ [rcx+r14*8+CONST]
1513
+ [rdx+r14*4]
1514
+ [r15+rdx*8+CONST]
1515
+ [rax+rbp*8+CONST]
1516
+ [rdx+r14*8+CONST]
1517
+ [rcx+r12*8+CONST]
1518
+ [rcx+r15*8+CONST]
1519
+ [rax+r12*8+CONST]
1520
+ [r14+r15*8+CONST]
1521
+ movlpd
1522
+ [r12+r13*8+CONST]
1523
+ [rdx+rbx*8+CONST]
1524
+ [rbp+rbp*4+CONST]
1525
+ [CONST_VAR+r13*8]
1526
+ [rdx+rcx+CONST]
1527
+ [rbx+rdx*8]
1528
+ [rbx+rsi*8]
1529
+ [r12+rdi*8]
1530
+ [rdx+r8*8]
1531
+ [rdx+r15*8]
1532
+ [r15+r15*4]
1533
+ [rax+r8*8]
1534
+ [r10+rcx*8]
1535
+ [r10+rdx*8]
1536
+ [r11+r8*8]
1537
+ [r11+rcx*8]
1538
+ [r11+rsi*8]
1539
+ [r8+r8]
1540
+ [rcx+r8*4]
1541
+ [r11+r10*8+CONST]
1542
+ [r13+r9*4+CONST]
1543
+ [rbx+r8*8]
1544
+ [CONST_VAR+r8*4]
1545
+ [r8+r11*8]
1546
+ [rbp+r12*8+CONST]
1547
+ [rbx+r13*8]
1548
+ [rbp+r9*8+CONST]
1549
+ [rbx+r10*8]
1550
+ [r15+r9*8]
1551
+ [r15+r10*8]
1552
+ [rcx+r9*8]
1553
+ [r12+r9*8]
1554
+ [r10+rsi*8]
1555
+ [r10+rdi*8]
1556
+ [r10+r9*8]
1557
+ [r10+r14]
1558
+ [r9+rcx*8]
1559
+ [r11+r9*8]
1560
+ [r9+r10*8]
1561
+ [r12+r12]
1562
+ [r9+r12*8]
1563
+ [r14+r8*8]
1564
+ [r9+rdi*8]
1565
+ [r9+r8*8]
1566
+ [r9+r14]
1567
+ [r12+r11*8]
1568
+ [r13+rdi*8+CONST]
1569
+ [r14+rdi*8]
1570
+ [r14+rcx*8]
1571
+ [r10+r8*8+CONST]
1572
+ [r9+r15]
1573
+ [r11+r11*4]
1574
+ [r11+rdx*8+CONST]
1575
+ [rax+r10*8+CONST]
1576
+ [r11+r10*8]
1577
+ [r11+rdi*8]
1578
+ [r11+rbx*8]
1579
+ [r14+r11*8]
1580
+ [r11+r13*8]
1581
+ [CONST_VAR+rbp*4]
1582
+ [CONST_VAR+r15*4]
1583
+ [CONST_VAR+r15*8]
1584
+ [rcx+r15*8]
1585
+ [r9+rdx*8+CONST]
1586
+ [r9+r15*8+CONST]
1587
+ [r14+rbp*8+CONST]
1588
+ [r12+r12+CONST]
1589
+ [r10+rcx*8+CONST]
1590
+ [r13+r14*8+CONST]
1591
+ [r11+rax*8+CONST]
1592
+ [rsp+r15+CONST+var_xxx]
1593
+ [r9+r12*8+CONST]
1594
+ [r11+rbp*8+CONST]
1595
+ [r9+r8+CONST]
1596
+ [rcx+rdi*2]
1597
+ err
1598
+ rol
1599
+ [r12+rdx*4+CONST]
1600
+ [r12+rdi*4+CONST]
1601
+ [r15+rbx+CONST]
1602
+ [r15+rbp+CONST]
1603
+ [r14+r13*8]
1604
+ punpckhqdq
1605
+ [rax+rsi*8+CONST]
1606
+ [CONST_VAR+r12*8+CONST]
1607
+ [r12+r13+CONST]
1608
+ [rbp+r8*8+CONST]
1609
+ [r8+r10*2]
1610
+ [rax+rcx*2+CONST]
1611
+ [rax+rdi*2+CONST]
1612
+ [rdx+rsi*2+CONST]
1613
+ [CONST_VAR+rdi*2+CONST]
1614
+ [rsp+rax*8+CONST+CONST_VAR]
1615
+ [rsp+rcx*8+CONST+CONST_VAR]
1616
+ [rcx+r14*8]
1617
+ [rbx+r15*8]
1618
+ [rax+rbp*2]
1619
+ [CONST_VAR+r9*2]
1620
+ [r9+r10*2]
1621
+ [rax+r9*2]
1622
+ [rax+rdi*2]
1623
+ [CONST_VAR+r8*2]
1624
+ [rax+r8*4]
1625
+ [r12+r12*4+CONST]
1626
+ [r12+r12*2+CONST]
1627
+ [r14+r15+CONST]
1628
+ fldz
1629
+ fcomip
1630
+ fnstcw
1631
+ fmul
1632
+ fsub
1633
+ fldcw
1634
+ fistp
1635
+ fsubrp
1636
+ fld1
1637
+ fdivp
1638
+ fmulp
1639
+ fucomi
1640
+ fcomi
1641
+ fdiv
1642
+ [rsp+rax+CONST+var_xxx+CONST]
1643
+ fdivrp
1644
+ [r13+r13*4+CONST]
1645
+ [rdx+rsi*2]
1646
+ [r8+rsi*2+CONST]
1647
+ [r11+r8]
1648
+ [rsp+arg_xxx+CONST]
1649
+ [r8+r15*8+CONST]
1650
+ [r15+r14*8+CONST]
1651
+ [r12+r15*8+CONST]
1652
+ [r10+r14*8+CONST]
1653
+ [rbp+arg_xxx]
1654
+ [r11+rdx*4]
1655
+ [CONST_VAR+r10+CONST]
1656
+ [rcx+r12+CONST]
1657
+ [rdx+rsi*4+CONST]
1658
+ [rax+rcx*4+CONST]
1659
+ [r13+rdi*4+CONST]
1660
+ [CONST_VAR+r14*4]
1661
+ [r11+r13]
1662
+ [r10+rbx]
1663
+ [r12+r10*4]
1664
+ [r14+rcx*4]
1665
+ [r12+r8]
1666
+ [rbx+rdi*4]
1667
+ [rcx+rdx*4+CONST]
1668
+ [CONST_VAR+rdx*4+CONST]
1669
+ [rdx+rcx*4+CONST]
1670
+ [r11+r14*4]
1671
+ [rcx+r8*4+CONST]
1672
+ [r10+r13]
1673
+ [r10+r13*4]
1674
+ [r12+rbp*4]
1675
+ [rbx+r13*8+CONST]
1676
+ jno
1677
+ [r10+r13*8+CONST]
1678
+ [r15+r13*8+CONST]
1679
+ [CONST_VAR+r13*4]
1680
+ [r15+r12*8+CONST]
1681
+ [r14+rcx*8+CONST]
1682
+ [r10+r12*8+CONST]
1683
+ [r14+r10*8+CONST]
1684
+ [r15+rsi*8+CONST]
1685
+ [rsp+r12+CONST+var_xxx]
1686
+ [r10+rbp*8+CONST]
1687
+ [rsp+r13+CONST+var_xxx]
1688
+ locretxxx
1689
+ [rbx+r15*8+CONST]
1690
+ [r14+rsi*8+CONST]
1691
+ [r14+r12*8+CONST]
1692
+ [r11+r14*8+CONST]
1693
+ [rdx+rbp*8+CONST]
1694
+ [CONST_VAR+r13*8+CONST]
1695
+ [r9+rbx*8+CONST]
1696
+ [r15+rcx*8+CONST]
1697
+ [r11+rbx*8+CONST]
1698
+ [r8+r13*8+CONST]
1699
+ [r14+rdx+CONST]
1700
+ [rbx+rdx*2]
1701
+ [CONST_VAR+rdx*2+CONST]
1702
+ [rax+rbx*2+CONST]
1703
+ [r11+r11+CONST]
1704
+ [CONST_VAR+r11]
1705
+ [rax+rcx*2]
1706
+ [r15+r15]
1707
+ [rax+r15*2]
1708
+ [r14+r12+CONST]
1709
+ [r13+rdx*2+CONST]
1710
+ [rcx+rcx+CONST]
1711
+ [rbx+rcx*2]
1712
+ [r13+rax*2+CONST]
1713
+ [rbx+rax*2]
1714
+ [CONST_VAR+r13+CONST]
1715
+ [rcx+rbx+CONST]
1716
+ [rax+rsi*2+CONST]
1717
+ [rbp+r8+CONST]
1718
+ [CONST_VAR+r9*2+CONST]
1719
+ [rbx+r9+CONST]
1720
+ [r14+r14*4]
1721
+ [rax+r8*2+CONST]
1722
+ [CONST_VAR+r8*2+CONST]
1723
+ [rbx+r8+CONST]
1724
+ [rdx+rdx*2+CONST]
1725
+ [rcx+r10*8]
1726
+ [r10+r14*8]
1727
+ [rdx+r11*8]
1728
+ [r9+r9+CONST]
1729
+ [r9+rdx*8]
1730
+ [rax+rsi*2]
1731
+ [r8+rax*2]
1732
+ [r8+r11*4]
1733
+ [rcx+rdi*4]
1734
+ [rcx+rdi*4+CONST]
1735
+ [rbp+r9+CONST]
1736
+ punpcklbw
1737
+ pcmpeqb
1738
+ paddb
1739
+ punpckhbw
1740
+ psllw
1741
+ psrld
1742
+ pslld
1743
+ [rcx+r13+CONST]
1744
+ [rsp+rsi*8+CONST+var_xxx]
1745
+ [rsp+rdx+CONST+CONST_VAR+CONST]
1746
+ [rdx+r8*8+CONST]
1747
+ [rdx+rbx+CONST]
1748
+ [r12+rcx+CONST]
1749
+ [r8+r14+CONST]
1750
+ [r9+rdx+CONST]
1751
+ [r9+rax+CONST]
1752
+ [r12+r8*8]
1753
+ [r13+r10+CONST]
1754
+ [r14+r9*4]
1755
+ [r15+r9]
1756
+ [r13+r11+CONST]
1757
+ [rcx+rbp+CONST]
1758
+ [r8+r9*4]
1759
+ [rax+r13*2]
1760
+ [r14+rsi*8]
1761
+ [rbp+rbx*2+CONST]
1762
+ ss:xxx
1763
+ cwde
1764
+ [r14+rsi*2]
1765
+ pinsrw
1766
+ [r10+r8]
1767
+ [r9+rcx+CONST]
1768
+ [r14+r8]
1769
+ [r13+rbx*2+CONST]
1770
+ [rbp+rax*8+var_xxx]
1771
+ [rbp+rdx*8+var_xxx]
1772
+ [rbp+rsi*8+var_xxx]
1773
+ [rbp+rcx*8+var_xxx]
1774
+ [rax+r15*4]
1775
+ [r14+r14*2]
1776
+ [r10+r12]
1777
+ [rbx+r13+CONST]
1778
+ [r15+r12+CONST]
1779
+ [rcx+rcx*4+CONST]
1780
+ [CONST_VAR+rbp+CONST]
1781
+ [r12+r11]
1782
+ [r12+rax*2+CONST]
1783
+ [rdx+r13*2+CONST]
1784
+ [rdx+r11+CONST]
1785
+ [r10+r10]
1786
+ [r11+r11]
1787
+ [rax+r11+CONST]
1788
+ [rax+rsi*4+CONST]
1789
+ [r10+CONST_VAR+CONST]
1790
+ [r14+r11]
1791
+ [rsp+r12*8+CONST+var_xxx]
1792
+ [rbp+CONST_VAR+var_xxx]
1793
+ [rsp+rbx*8+CONST+var_xxx]
1794
+ [rsp+rcx*8+CONST+var_xxx]
1795
+ [r15+rdi*8]
1796
+ [rbp+rcx+var_xxx]
1797
+ [rbp+rax+var_xxx+CONST]
1798
+ leave
1799
+ rdsspq
1800
+ incsspq
1801
+ [rbx+r8*8+CONST]
1802
+ [r11+r10]
1803
+ pmuludq
1804
+ psllq
1805
+ [r8+r12*4]
1806
+ [CONST_VAR+r12*4]
1807
+ [rsp+rbp*8+CONST+var_xxx]
1808
+ [r10+r11*8]
1809
+ [r10+r8*8]
1810
+ [rsp+CONST_VAR+CONST+var_xxx+CONST]
1811
+ [rsp+r8+CONST+var_xxx+CONST]
1812
+ [rsp+r11+CONST+var_xxx]
1813
+ [rsp+r11+CONST+var_xxx+CONST]
1814
+ [rsp+r12+CONST+var_xxx+CONST]
1815
+ [rsp+rdx+CONST+var_xxx+CONST]
1816
+ [rsp+rdi*8+CONST+var_xxx+CONST]
1817
+ [rsp+r11*8+CONST+var_xxx+CONST]
1818
+ [rsp+CONST_VAR+var_xxx]
1819
+ [r15+rdx*4+CONST]
1820
+ [r8+r12*8]
1821
+ [r8+r11*8+CONST]
1822
+ [CONST_VAR+r8*4+CONST]
1823
+ [rsp+rsi*4+CONST+var_xxx]
1824
+ [rsp+rdi*8+CONST+var_xxx]
1825
+ [r9+rbx*8]
1826
+ [r12+rbp+CONST]
1827
+ [r9+r15+CONST]
1828
+ [rbp+r11+CONST]
1829
+ cmplesd
1830
+ [rcx+r13*8]
1831
+ [rax+r8*4+CONST]
1832
+ [rsp+rdi*4+CONST+var_xxx]
1833
+ [rsp+rdx*4+CONST+var_xxx]
1834
+ [r14+rax*4+CONST]
1835
+ movsb
1836
+ [r9+rcx*2]
1837
+ [r9+rsi*2]
1838
+ [rbx+rbx*2+CONST]
1839
+ [r15+rbp*4+CONST]
1840
+ cvttpd2dq
1841
+ [r14+r14*2+CONST]
1842
+ [r8+r10*8+CONST]
1843
+ [r14+rdi*8+CONST]
1844
+ [rbp+rcx*2+CONST]
1845
+ [r12+rcx*2]
1846
+ [r10+rsi*4+CONST]
1847
+ [r11+rdx]
1848
+ [r11+rcx+CONST]
1849
+ [rcx+r9*4+CONST]
1850
+ [r8+r13+CONST]
1851
+ [rsp+rsi*4+CONST+var_xxx+CONST]
1852
+ cvtdq2ps
1853
+ ror
1854
+ [r8+rdx*8+CONST]
1855
+ psrlq
1856
+ [rcx+r11*8]
1857
+ [rdx+r10*8]
1858
+ [rax+rdi*4+CONST]
1859
+ [rdx+r15*4]
1860
+ cmpnltss
1861
+ [r15+r13+CONST]
1862
+ [rax+r8*8+CONST]
1863
+ [r13+r12*2+CONST]
1864
+ [r10+rcx*4]
1865
+ pcmpgtw
1866
+ [rbx+r9*8+CONST]
1867
+ [rdx+r8*2+CONST]
1868
+ [rsp+r15+CONST+CONST_VAR]
1869
+ [rsp+r13+CONST+CONST_VAR]
1870
+ [r10+rsi*8+CONST]
1871
+ [r14+rax*2]
1872
+ [rax+r13*2+CONST]
1873
+ [rdx+rdi*2+CONST]
1874
+ [rbx+r9]
1875
+ [r11+r15]
1876
+ [rdx+r13*8+CONST]
1877
+ [rbp+r15*2+CONST]
1878
+ [r12+r10*8+CONST]
1879
+ [rbx+rdi*8]
1880
+ [CONST_VAR+rdi*8+CONST]
1881
+ [r14+rdx*8+CONST]
1882
+ [r8+r12*8+CONST]
1883
+ [r10+r12*4]
1884
+ [r10+rbp*4]
1885
+ [r9+r11*4]
1886
+ [r12+rdi*8+CONST]
1887
+ [r14+r10*4]
1888
+ [rbp+r13*4+CONST]
1889
+ [r12+r15*4]
1890
+ [r11+r9*4]
1891
+ [r11+r11*2+CONST]
1892
+ [rax+r12*2+CONST]
1893
+ [r15+rax*2]
1894
+ [r11+rbp*4]
1895
+ [r11+r12*4]
1896
+ [rsp+rcx*4+CONST+var_xxx]
1897
+ [rcx+r14+CONST]
1898
+ [rsp+rbx*4+CONST+var_xxx]
1899
+ [rbp+rbx*8+var_xxx]
1900
+ [rbp+r12*8+var_xxx]
1901
+ [rsp+r13*8+CONST+var_xxx]
1902
+ [r9+r11*8+CONST]
1903
+ [rsp+r14*8+CONST+var_xxx]
1904
+ [r10+rdi*8+CONST]
1905
+ [r10+rbx*8+CONST]
1906
+ [r9+rbp*8+CONST]
1907
+ [r8+r14*8+CONST]
1908
+ [r10+r15*8+CONST]
1909
+ [r10+rcx*4+CONST]
1910
+ [r10+rdx*4+CONST]
1911
+ [r11+rbx]
1912
+ [r12+rdi*4]
1913
+ [r12+r14*4]
1914
+ [r15+r12*8]
1915
+ [r11+rdx*2]
1916
+ [rbx+rdi*8+CONST]
1917
+ [r11+r15*8+CONST]
1918
+ [r9+r10*8+CONST]
1919
+ [r10+r10*8]
1920
+ [r9+r9*8]
1921
+ [r11+r11*8]
1922
+ [r9+r13*8]
1923
+ [r12+r10*8]
1924
+ [rbx+rbx*8]
1925
+ [r15+r11*4]
1926
+ divps
1927
+ [rbp+r14*4+CONST]
1928
+ [rbx+r15*4]
1929
+ [r14+r10+CONST]
1930
+ [rbx+r10*4]
1931
+ [r9+rdx*4+CONST]
1932
+ [r15+r11*8]
1933
+ [r10+r11*4]
1934
+ [r10+r8*4]
1935
+ [rsp+r15*8+CONST+arg_xxx]
1936
+ [r13+r9*8+CONST]
1937
+ [r11+r8*4]
1938
+ clc
1939
+ [r11+rdi*4]
1940
+ [r11+r12*8]
1941
+ [CONST_VAR+r12*4+CONST]
1942
+ [rdx+r12*4+CONST]
1943
+ [rax+r10*4+CONST]
1944
+ [rax+r15*4+CONST]
1945
+ [r10+rdx+CONST]
1946
+ [r12+r12*8]
1947
+ [rax+r13*4+CONST]
1948
+ [rcx+rbp*4+CONST]
1949
+ [CONST_VAR+r14*4+CONST]
1950
+ [rcx+rbp*8+CONST]
1951
+ [rbp+rbp*8+CONST]
1952
+ [r13+r10*8+CONST]
1953
+ [r11+r10+CONST]
1954
+ [r15+rax*2+CONST]
1955
+ [r10+rbp]
1956
+ pmullw
1957
+ [r10+r9]
1958
+ [r12+r8*4]
1959
+ [r12+rbx*2]
1960
+ [r12+r8*2]
1961
+ [r12+r14*2]
1962
+ [r12+rdx*2]
1963
+ [r13+r8*2+CONST]
1964
+ [r13+r14*2+CONST]
1965
+ [r12+rax*2]
1966
+ [r10+r13*8]
1967
+ cmpltpd
1968
+ [r10+rdi*4+CONST]
1969
+ [rsp+r10*4+CONST+var_xxx]
1970
+ [rsp+r9*4+CONST+var_xxx]
1971
+ [rsp+r15*4+CONST+var_xxx]
1972
+ [rax+r15*8+CONST]
1973
+ [r9+rbp]
1974
+ [r15+r11]
1975
+ [r10+r11]
1976
+ [rdx+rbx*2]
1977
+ [rdx+r13*2]
1978
+ [rdx+r11*2]
1979
+ [rdx+r12*2]
1980
+ [rdx+r14*2]
1981
+ [rdx+rbp*2]
1982
+ [r11+rbp*2]
1983
+ [r11+rsi*2]
1984
+ [r11+r10*2]
1985
+ [rbx+r14*2]
1986
+ [r15+r10*2]
1987
+ [r13+r15*2+CONST]
1988
+ [r14+r15*2]
1989
+ [rbx+r11*2]
1990
+ [CONST_VAR+rbp*2]
1991
+ [CONST_VAR+r10*2]
1992
+ [CONST_VAR+r11*2]
1993
+ [r11+r13*8+CONST]
1994
+ [rdx+r12*8+CONST]
1995
+ [r9+r8*4]
1996
+ [r14+r8+CONST]
1997
+ [r14+r9*8]
1998
+ [r8+rcx*4+CONST]
1999
+ [rsp+rdx*4+CONST+CONST_VAR]
2000
+ [r8+r13*8]
2001
+ [rax+rdi*8+CONST]
2002
+ [r14+rbp+CONST]
2003
+ [r15+rbp*2]
2004
+ [rdx+r14*4+CONST]
2005
+ [rcx+r14*4+CONST]
2006
+ [rbx+r13*2]
2007
+ [rbp+r10*4+CONST]
2008
+ [r8+rsi*2]
2009
+ [r8+rdi*4]
2010
+ pause
2011
+ [r11+rbx*4]
2012
+ [r10+rbx*4]
2013
+ [rax+r9*4+CONST]
2014
+ maxps
2015
+ [r14+rbx*4+CONST]
2016
+ [r8+r9*8+CONST]
2017
+ [r15+r11*4+CONST]
2018
+ [r15+rdi*4+CONST]
2019
+ [r15+r10*4+CONST]
2020
+ [r15+r8*4+CONST]
2021
+ [r10+rax*2]
2022
+ [r15+rdx*2]
2023
+ [r14+r10*8]
2024
+ [r15+r9*4]
2025
+ [r11+r8+CONST]
2026
+ [r8+r11+CONST]
2027
+ [r8+rbx+CONST]
2028
+ [r13+r11*8+CONST]
2029
+ [CONST_VAR+r11+CONST]
2030
+ [rax+r8*2]
2031
+ [rbx+rbp*2]
2032
+ [r15+r15+CONST]
2033
+ [r14+rbp*2]
2034
+ [rbx+r12*2]
2035
+ [rax+r12*2]
2036
+ +24h
2037
+ +48h
2038
+ [rdx+rbp+CONST]
2039
+ [r15+r15*8]
2040
+ [r13+r13*8+CONST]
2041
+ [rbx+r15*2]
2042
+ rdtsc
2043
+ [rdx+r8*2]
2044
+ [rsp]
2045
+ [r15+r8*8+CONST]
2046
+ [r15+rdi*8+CONST]
2047
+ [rcx+r8*8+CONST]
2048
+ [r15+r9+CONST]
2049
+ [rsp+r14+CONST+CONST_VAR]
2050
+ fsubr
2051
+ [rdx+rbp*2+CONST]
2052
+ [r15+rdx*2+CONST]
2053
+ [r14+rbx*2+CONST]
2054
+ [r14+r9*8+CONST]
2055
+ [r10+r9*8+CONST]
2056
+ [r14+r13*2]
2057
+ [rdx+rdi*8+CONST]
2058
+ [r14+rdx*2]
2059
+ [r9+r14*4]
2060
+ [r9+rdi*8+CONST]
2061
+ psubusb
2062
+ [r10+r15*8]
2063
+ [rsp+r15*8+CONST+var_xxx]
2064
+ [r12+r11*8+CONST]
2065
+ [r12+r8*8+CONST]
2066
+ [r12+r9*8+CONST]
2067
+ [r10+r14+CONST]
2068
+ [r8+r15*8]
2069
+ [CONST_VAR+r15*8+CONST]
2070
+ [rdx+r15*8+CONST]
2071
+ [r10+rbp*8]
2072
+ cbw
2073
+ [rbx+rbp*4+CONST]
2074
+ [rbx+r15*4+CONST]
2075
+ [r9+rdi*4+CONST]
2076
+ [rdx+rbx*2+CONST]
2077
+ [rcx+r11+CONST]
2078
+ cmpltss
2079
+ [r10+r9*4]
2080
+ [r9+r14*8]
2081
+ esp
2082
+ [rdx+rdi*4+CONST]
2083
+ [r11+r10*4]
2084
+ [r15+r8+CONST]
2085
+ [r15+r10+CONST]
2086
+ [r15+rcx*2]
2087
+ [r14+r11+CONST]
2088
+ cmpneqpd
2089
+ cmpeqpd
2090
+ cmpneqps
2091
+ cmpeqps
2092
+ [rbx+r9*4]
2093
+ [rbx+rsi*2]
2094
+ [rbx+rsi*2+CONST]
2095
+ [r14+r8*8+CONST]
2096
+ [rsp+r9+CONST+var_xxx]
2097
+ [r15+r8*8]
2098
+ [r11+r8*8+CONST]
2099
+ [rsp+rbx*8+CONST+var_xxx+CONST]
2100
+ [CONST_VAR+r14*2]
2101
+ [rbp+r12*2+CONST]
2102
+ [CONST_VAR+r13*2]
2103
+ [CONST_VAR+r12*2]
2104
+ [r11+r12*2]
2105
+ [CONST_VAR+rbx*2]
2106
+ [rbx+rdi*2]
2107
+ [rbp+r14*2+CONST]
2108
+ [r9+r13]
2109
+ [r9+rcx*2+CONST]
2110
+ [rsp+r12*2+arg_xxx]
2111
+ [rsp+rcx*2+arg_xxx]
2112
+ [rsp+rsi*2+arg_xxx]
2113
+ [rsp+rcx+arg_xxx]
2114
+ [rsp+CONST_VAR+arg_xxx]
2115
+ [rsp+rbx*2+arg_xxx]
2116
+ [rsp+rdx+arg_xxx]
2117
+ xgetbv
2118
+ cpuid
2119
+ [rsp+r10+CONST+var_xxx]
2120
+ [rsp+rbx*2+CONST+var_xxx]
2121
+ [rcx+r8*2+CONST]
2122
+ [r10+rsi*2]
2123
+ [rsp+rcx+CONST]
2124
+ [rsp+CONST_VAR+CONST]
2125
+ [rsp+rax+CONST]
2126
+ [rsp+rsi*2+CONST+var_xxx]
2127
+ [CONST_VAR+r10*2+CONST]
2128
+ [rsp+rdx+CONST]
2129
+ [CONST_VAR+r11*4+CONST]
2130
+ [rbp+rax+CONST_VAR]
2131
+ [rbp+rdx+CONST_VAR]
2132
+ [rsp+rcx+CONST+var_xxx+CONST]
2133
+ [rax+rax*8+CONST]
2134
+ [rsp+rcx+CONST+CONST_VAR]
2135
+ [rdx+r14*2+CONST]
2136
+ [r15+r13*2]
2137
+ [r15+rbp*2+CONST]
2138
+ [rax+r15*2+CONST]
2139
+ [r15+r13*2+CONST]
2140
+ [rax+r9*8+CONST]
2141
+ [rax+r14*4+CONST]
2142
+ [rdx+r10*8+CONST]
2143
+ [r15+rbx*2]
2144
+ [r10+rdx*2+CONST]
2145
+ [r10+rdx*2]
2146
+ [r12+rbp*2+CONST]
2147
+ [r12+r8*2+CONST]
2148
+ [rbx+r8*2+CONST]
2149
+ [rbx+r10*2]
2150
+ [rbp+rax+CONST_VAR+CONST]
2151
+ [rbp+rdx+CONST_VAR+CONST]
2152
+ [r13+rcx*2+CONST]
2153
+ [r14+rcx*2]
2154
+ [r12+rsi*2]
2155
+ [rsp+r15*2+CONST+var_xxx]
2156
+ [r8+r12*2+CONST]
2157
+ [r8+r14*2+CONST]
2158
+ [CONST_VAR+r13*2+CONST]
2159
+ [CONST_VAR+rbx*2+CONST]
2160
+ [rbx+r13*2+CONST]
2161
+ [r11+r13*4]
2162
+ psadbw
2163
+ [r11+rax*2]
2164
+ [r9+r14+CONST]
2165
+ [rsp+rax*4+CONST+CONST_VAR]
2166
+ [rsp+r15+CONST+var_xxx+CONST]
2167
+ [rsp+r13+CONST]
2168
+ [rsp+rbp+CONST]
2169
+ [rsp+rbx+CONST+var_xxx+CONST]
2170
+ [rsp+r12+CONST]
2171
+ [rcx+r13*2+CONST]
2172
+ [rcx+r13*2]
2173
+ [rsp+r14+CONST+var_xxx+CONST]
2174
+ [r11+rbp]
2175
+ [r11+r9+CONST]
2176
+ [r10+r15+CONST]
2177
+ [rsp+rbp+CONST+CONST_VAR]
2178
+ [rsp+rax+CONST+CONST_VAR+CONST]
2179
+ [rsp+r9+CONST+CONST_VAR]
2180
+ [rsp+rbx+CONST+CONST_VAR+CONST]
2181
+ [r8+rbp+CONST]
2182
+ [rsp+rax*2+CONST+var_xxx]
2183
+ [rsp+r8*2+CONST+var_xxx]
2184
+ [rsp+rcx*2+CONST+var_xxx]
2185
+ [rsp+rdi*2+CONST+var_xxx]
2186
+ [rsp+rdx*2+CONST+var_xxx]
2187
+ [rsp+rbp*2+CONST+var_xxx]
2188
+ [rbp+r8+var_xxx]
2189
+ [r12+rdx*2+CONST]
2190
+ [r8+r12+CONST]
2191
+ [rsp+rbp+CONST+var_xxx+CONST]
2192
+ [rsp+r8+CONST+CONST_VAR+CONST]
2193
+ [r12+r10+CONST]
2194
+ [r15+rsi*2]
2195
+ [rbx+r14*2+CONST]
2196
+ [r14+r9+CONST]
2197
+ [rdx+r10*2]
2198
+ [rsp+rdx*2+CONST+var_xxx+CONST]
2199
+ [rsp+r10*2+CONST+var_xxx]
2200
+ [rdx+r9*2]
2201
+ [rsp+r12*2+CONST+var_xxx]
2202
+ [r10+rbx*2]
2203
+ [rsp+r14*2+CONST+var_xxx]
2204
+ [rsp+r15*2+CONST+var_xxx+CONST]
2205
+ [rsp+r13*2+CONST+var_xxx]
2206
+ [r11+r14]
2207
+ [r10+r9*2]
2208
+ [rsp+r10*8+CONST+var_xxx]
2209
+ [CONST_VAR+rdi*4+CONST]
2210
+ cmovp
2211
+ [rbp+r14*8+var_xxx]
2212
+ [CONST_VAR+r10*4+CONST]
2213
+ [rbp+r11*8+var_xxx]
2214
+ vpcmpeqd
2215
+ vmovdqa
2216
+ vpxor
2217
+ popcnt
2218
+ vpor
2219
+ vpand
2220
+ vpandn
2221
+ vmovq
2222
+ vpextrq
2223
+ ymm1
2224
+ vandps
2225
+ ymm0
2226
+ vzeroupper
2227
+ vorps
2228
+ ymm2
2229
+ ymm4
2230
+ ymm5
2231
+ ymm3
2232
+ ymm6
2233
+ ymm7
2234
+ ymm9
2235
+ ymm8
2236
+ vextracti128
2237
+ vpternlogd
2238
+ zmm0
2239
+ vmovdqa32
2240
+ zmm1
2241
+ zmm2
2242
+ zmm5
2243
+ vpxord
2244
+ zmm4
2245
+ vpord
2246
+ zmm6
2247
+ vpandd
2248
+ zmm3
2249
+ zmm7
2250
+ zmm8
2251
+ zmm9
2252
+ vpandnd
2253
+ [CONST_VAR+rbp*2+CONST]
2254
+ [rax+rbp*4+CONST]
2255
+ [r14+r13*4+CONST]
2256
+ [r8+rsi*4+CONST]
2257
+ [rdx+r9*8+CONST]
2258
+ [r10+r11*8+CONST]
2259
+ [r11+r15*4]
2260
+ [r11+rbx+CONST]
2261
+ [r12+r11+CONST]
2262
+ [r12+r9+CONST]
2263
+ [r14+rbx*2]
2264
+ [rbp+rdx*2+CONST]
2265
+ [rsp+rax*4+var_xxx]
2266
+ [r8+rdi*4+CONST]
2267
+ [r8+r13*4+CONST]
2268
+ [r8+r15*4+CONST]
2269
+ [r8+r14*4+CONST]
2270
+ [CONST_VAR+rbp*8+CONST]
2271
+ [r9+r15*8]
2272
+ [r11+r14+CONST]
2273
+ [rdx+r11*8+CONST]
2274
+ [rax+r11*8+CONST]
2275
+ [r15+rdi*2]
2276
+ [rbp+rdi*2+CONST]
2277
+ [rbp+rsi*2+CONST]
2278
+ cmpless
2279
+ [r14+r13*2+CONST]
2280
+ [rbx+r15*2+CONST]
2281
+ [rax+r11*2]
2282
+ cmpleps
2283
+ [r14+r12*2]
2284
+ [r15+r12*2]
2285
+ [r9+rbp*8]
2286
+ [CONST_VAR+r9*4+CONST]
2287
+ [r12+rbx*2+CONST]
2288
+ [rsp+rdx*8+CONST+CONST_VAR]
2289
+ [r13+rbp*2+CONST]
2290
+ [rsp+rdi*8+CONST+CONST_VAR]
2291
+ [rsp+r14*8+CONST+CONST_VAR]
2292
+ [rdx+rbx*4+CONST]
2293
+ [rcx+rdi*8+CONST]
2294
+ [r9+r11*2]
2295
+ [r9+r8*2]
2296
+ [r8+r9*2]
2297
+ [r8+r9*4+CONST]
2298
+ psubw
2299
+ [r10+rcx*2]
2300
+ [rsp+r8*8+CONST+var_xxx]
2301
+ [rsp+r9*8+CONST+var_xxx]
2302
+ [rsp+r11*8+CONST+var_xxx]
2303
+ fyl2x
2304
+ fldl2e
2305
+ frndint
2306
+ f2xm1
2307
+ faddp
2308
+ fscale
2309
+ cvtsd2si
2310
+ fldln2
2311
+ fldlg2
2312
+ fsin
2313
+ fcos
2314
+ fptan
2315
+ int
2316
+ fpatan
2317
+ [r14+rdx*4+CONST]
2318
+ tzcnt
2319
+ [rdx+r9*4+CONST]
2320
+ [r9+r10*4+CONST]
2321
+ [edi]
2322
+ [rbp+r8*2+CONST]
2323
+ [rdx+r15*2]
2324
+ [rbx+rdx*2+CONST]
2325
+ [CONST_VAR+r14*2+CONST]
2326
+ [rax+r14*2+CONST]
2327
+ [r15+r9*2]
2328
+ [r11+rax*2+CONST]
2329
+ [rsp+rdi*2+CONST+var_xxx+CONST]
2330
+ [r11+rdi*8+CONST]
2331
+ [r11+rsi*8+CONST]
2332
+ [rbx+rbp*2+CONST]
2333
+ [r12+r8+CONST]
2334
+ [r14+rdx*2+CONST]
2335
+ [rbx+rcx*2+CONST]
2336
+ [esi]
2337
+ [rbx+r11*8]
2338
+ [r15+r15*2+CONST]
2339
+ [r15+r14*4+CONST]
2340
+ [rsp+r14*4+CONST+var_xxx+CONST]
2341
+ [r11+rdi*4+CONST]
2342
+ [r11+rbx*4+CONST]
2343
+ [r9+rsi*4+CONST]
2344
+ [rdx+r8*4+CONST]
2345
+ [rcx+rsi*2]
2346
+ cmovnp
2347
+ [r10+rax*2+CONST]
2348
+ [r15+r14*2+CONST]
2349
+ bnd
2350
+ [rsp+r8*8+CONST+CONST_VAR]
2351
+ [rbp+r9*2+CONST]
2352
+ [r11+r9*2]
2353
+ [rsp+rbp*4+CONST+var_xxx]
2354
+ [r10+rdi*2]
2355
+ [r10+rbp*2]
2356
+ [r11+r8*2]
2357
+ [r10+r8*2]
2358
+ [r11+rcx*2]
2359
+ [r9+rcx*4+CONST]
2360
+ [r14+rcx*4+CONST]
2361
+ [rsp+rax+var_xxx]
2362
+ [rcx+r8*2]
2363
+ [rcx+r12*2]
2364
+ [r12+r15*2]
2365
+ [r14+r10*4+CONST]
2366
+ [rbx+r8*2]
2367
+ [rax+r10*2]
2368
+ [r10+r10+CONST]
2369
+ [r9+rdi*2]
2370
+ [r9+rbp*2]
2371
+ [r8+r11*2]
2372
+ [rcx+r15*2]
2373
+ [r8+r15*2]
2374
+ [CONST_VAR+r15*4+CONST]
2375
+ [rcx+r11*2]
2376
+ [r10+rbx*2+CONST]
2377
+ [rbx+r9*2]
2378
+ [r10+rdi*2+CONST]
2379
+ [rcx+r9*2]
2380
+ [r10+r9*2+CONST]
2381
+ [r8+rdi*2]
2382
+ [r10+r14*4]
2383
+ [r14+r11*4]
2384
+ [r14+rdi*4]
2385
+ [r14+rsi*4+CONST]
2386
+ [r9+r12+CONST]
2387
+ [r8+r15+CONST]
2388
+ [r15+rbx*2+CONST]
2389
+ [rsp+r12+CONST+CONST_VAR]
2390
+ [r10+rbx*8]
2391
+ [rdx+rdx*4+CONST]
2392
+ fild
2393
+ [r8+r8*4+CONST]
2394
+ fadd
2395
+ [rbx+rbx*4+CONST]
2396
+ [r10+r11*2]
2397
+ pmaddwd
2398
+ [r9+rbx*2]
2399
+ [r14+r9*2]
2400
+ [r12+r10*2]
2401
+ [r12+r9*2]
2402
+ [rdx+r9*2+CONST]
2403
+ [rsp+rax*8+CONST+arg_xxx]
2404
+ [r11+r9*4+CONST]
2405
+ [r10+r9*4+CONST]
2406
+ [r11+r12*8+CONST]
2407
+ [rax+r12*4+CONST]
2408
+ [CONST_VAR+r13*4+CONST]
2409
+ [r9+rbx*4+CONST]
2410
+ +3
2411
+ [r12+rbp*4+CONST]
2412
+ [r15+r9*8+CONST]
2413
+ [r11+r9*8+CONST]
2414
+ [rbx+r10*8+CONST]
2415
+ [r9+r9*2+CONST]
2416
+ [rsp+r11*4+CONST+var_xxx]
2417
+ [r9+r8*8+CONST]
2418
+ [r14+r11*8+CONST]
2419
+ [rdx+rbp*4+CONST]
2420
+ [rsp+rax*4+CONST+var_xxx+CONST]
2421
+ [rsp+rax*8+CONST+var_xxx+CONST]
2422
+ [rsp+rcx*4+CONST+var_xxx+CONST]
2423
+ [rsp+rdx*8+CONST+var_xxx+CONST]
2424
+ [rsp+rdx*4+CONST+var_xxx+CONST]
2425
+ [rsp+rbp*8+CONST+var_xxx+CONST]
2426
+ [r10+r10*2+CONST]
2427
+ [CONST_VAR+r15*2+CONST]
2428
+ [rbp+rdx*4+var_xxx]
2429
+ [rbp+rdi*4+var_xxx]
2430
+ [rbp+r8*8+var_xxx]
2431
+ [rbp+r11+var_xxx]
2432
+ [rbp+rax*4+var_xxx]
2433
+ [rbp+rsi*4+var_xxx]
2434
+ [rbp+r13+var_xxx]
2435
+ [r11+r10*4+CONST]
2436
+ [r11+r10*2+CONST]
2437
+ [r11+r8*4+CONST]
2438
+ [r13+r10*2+CONST]
2439
+ [r11+r8*2+CONST]
2440
+ [CONST_VAR+rbx*4+CONST]
2441
+ [rbx+rdi*2+CONST]
2442
+ [r10+rcx*2+CONST]
2443
+ [r13+rsi*2+CONST]
2444
+ [rsp+rbp*8+CONST+CONST_VAR]
2445
+ [rsp+rbx*4+CONST+var_xxx+CONST]
2446
+ [rsp+r12*4+CONST+var_xxx]
2447
+ [rsp+r12*4+CONST+var_xxx+CONST]
2448
+ [rcx+r12*4+CONST]
2449
+ minpd
2450
+ maxpd
2451
+ [rbp+r10*8+CONST]
2452
+ [rsp+r9*8+CONST+CONST_VAR]
2453
+ [rsp+rsi*8+CONST+CONST_VAR]
2454
+ +10h
2455
+ [r9+rsi*8+CONST]
2456
+ [rbp+r13*2+CONST]
2457
+ [rdx+r13*4+CONST]
2458
+ +0Ch
2459
+ bsf
2460
+ [rbx+r12*2+CONST]
2461
+ [r14+rcx*2+CONST]
2462
+ [r9+rax*2+CONST]
2463
+ [rcx+r10*4+CONST]
2464
+ [r12+r8*4+CONST]
2465
+ [r12+r9*4+CONST]
2466
+ [rcx+r11*4+CONST]
2467
+ [rsp+r9*2+CONST+var_xxx]
2468
+ [r14+r9*2+CONST]
2469
+ [r14+r8*2]
2470
+ [r14+r8*2+CONST]
2471
+ [r14+r10*2]
2472
+ [r14+r10*2+CONST]
2473
+ [r14+r11*2]
2474
+ [r14+r11*2+CONST]
2475
+ emms
2476
+ [r12+rbp*2]
2477
+ [r14+rsi*2+CONST]
2478
+ [CONST_VAR+r12*2+CONST]
2479
+ [r13+r9*2+CONST]
2480
+ [r9+rdi*2+CONST]
2481
+ [r9+r11*2+CONST]
2482
+ [r9+r15*2+CONST]
2483
+ [rsp+r11*2+CONST+var_xxx]
2484
+ [r9+rbx*2+CONST]
2485
+ [rsp+rbx*2+CONST_VAR+var_xxx]
2486
+ [rsp+r10*2+CONST_VAR+var_xxx]
2487
+ [rsp+r8*2+CONST_VAR+var_xxx]
2488
+ [rsp+rax*2+CONST_VAR+var_xxx]
2489
+ [r15+r8*2]
2490
+ [r8+r10*4+CONST]
2491
+ [r11+rcx*8+CONST]
2492
+ [r10+r13+CONST]
2493
+ [r10+r8+CONST]
2494
+ [rcx+rbx*4+CONST]
2495
+ [rcx+rdi*2+CONST]
2496
+ [r12+rcx*2+CONST]
2497
+ [r12+rsi*2+CONST]
2498
+ [rsp+r8+CONST+CONST_VAR]
2499
+ [r11+r15*8]
2500
+ seto
2501
+ [rdx+r12*2+CONST]
2502
+ [rcx+r12*2+CONST]
2503
+ [r10+r15*4]
2504
+ [r11+r12+CONST]
2505
+ [rsp+CONST_VAR+var_xxx+CONST_VAR]
2506
+ [rsp+CONST_VAR+CONST_VAR]
2507
+ [r11+r14*8]
2508
+ shld
2509
+ [rsp+rdx*8+CONST+arg_xxx]
2510
+ [r14+r15*4+CONST]
2511
+ [r10+r8*4+CONST]
2512
+ [rsp+rax*4+CONST+arg_xxx]
2513
+ [rsp+rdx*4+CONST+arg_xxx]
2514
+ [rsp+rbp*4+CONST+CONST_VAR]
2515
+ [rsp+r10+CONST+arg_xxx]
2516
+ [rsp+r9*4+CONST+arg_xxx]
2517
+ [rsp+rax+CONST+arg_xxx]
2518
+ [r8+r14*8]
2519
+ [rbp+r9+var_xxx]
2520
+ [rbp+r10+var_xxx]
2521
+ [r9+r15*4+CONST]
2522
+ [r14+r12*4+CONST]
2523
+ [r11+rbx*2]
2524
+ [r11+rbx*2+CONST]
2525
+ [r11+rdi*2]
2526
+ [r8+r14*2]
2527
+ [CONST_VAR+r15*2]
2528
+ [r9+r15*2]
2529
+ [rbp+r11*8+CONST]
2530
+ [r8+r10*2+CONST]
2531
+ [rcx+r11*2+CONST]
2532
+ [r10+r8*2+CONST]
2533
+ minps
2534
+ [r8+r13*2]
2535
+ [r8+r13*2+CONST]
2536
+ [r11+rdx*2+CONST]
2537
+ [r8+rbx*2]
2538
+ [rbx+r13*4+CONST]
2539
+ [r12+r14*2+CONST]
2540
+ [r8+rbp*4+CONST]
2541
+ [r12+rdi*2]
2542
+ [rbp+r10*2+CONST]
2543
+ [r8+rbp*2]
2544
+ [r14+rdi*2]
2545
+ [r12+r13*2]
2546
+ [r9+r9*4+CONST]
2547
+ [rdx+r10*4+CONST]
2548
+ [r9+r8*2+CONST]
2549
+ [rbp+r13*4+var_xxx]
2550
+ [r14+r15*2+CONST]
2551
+ [rbp+r11*2+CONST]
2552
+ [r12+rdi*2+CONST]
2553
+ [rbp+rcx*4+var_xxx]
2554
+ [r9+r9*8+CONST]
2555
+ [rcx+rcx*8+CONST]
2556
+ [rbp+r13*8+var_xxx]
2557
+ [rbp+r15*4+var_xxx+CONST]
2558
+ [r14+rbp*4+CONST]
2559
+ spl
2560
+ prefetcht0
2561
+ [rcx+r11*8+CONST]
2562
+ [rdx+r15*4+CONST]
2563
+ [rbx+r9*4+CONST]
2564
+ vmovdqu
2565
+ vpinsrq
2566
+ vmovsd
2567
+ vpbroadcastq
2568
+ vxorps
2569
+ vcvtusi2sd
2570
+ vdivsd
2571
+ vcvtsi2sd
2572
+ rorx
2573
+ vxorpd
2574
+ vmovupd
2575
+ vmovss
2576
+ vcvtusi2ss
2577
+ vmulss
2578
+ vcvtss2sd
2579
+ vdivss
2580
+ vcvttss2usi
2581
+ vcvtsd2ss
2582
+ vucomisd
2583
+ kmovb
2584
+ k1
2585
+ k2
2586
+ kandb
2587
+ k0
2588
+ kortestb
2589
+ vinserti128
2590
+ movbe
2591
+ vmovd
2592
+ vpinsrd
2593
+ vmovdqu64
2594
+ vcomiss
2595
+ [r9+rdx*2+CONST]
2596
+ vpmovsxdq
2597
+ vmulsd
2598
+ vpbroadcastd
2599
+ vpaddq
2600
+ vpaddd
2601
+ vmovdqa64
2602
+ vextracti64x4
2603
+ vextracti32x8
2604
+ vextracti64x2
2605
+ vpextrd
2606
+ vaddsd
2607
+ [r13+CONST_VAR]
2608
+ shlx
2609
+ vcvttps2dq
2610
+ vpermt2w
2611
+ vpmovwb
2612
+ vinserti64x4
2613
+ vmovdqu8
2614
+ vpbroadcastw
2615
+ vpackuswb
2616
+ vpermq
2617
+ vcvttss2si
2618
+ vbroadcastss
2619
+ vaddps
2620
+ vpermi2w
2621
+ vaddss
2622
+ vmovdqu16
2623
+ vmovaps
2624
+ vmovdqu32
2625
+ vsubsd
2626
+ vfmadd231ps
2627
+ vfmadd231ss
2628
+ vfmadd213ss
2629
+ vfnmadd213ss
2630
+ vfmsub231ss
2631
+ vcmpordss
2632
+ vblendvps
2633
+ vcmpunordss
2634
+ vunpcklps
2635
+ vmovlps
2636
+ vucomiss
2637
+ shrx
2638
+ vshufpd
2639
+ vminps
2640
+ vmaxps
2641
+ vshufps
2642
+ vdivps
2643
+ vcvtsi2ss
2644
+ vsubps
2645
+ vmulps
2646
+ vfmsub132ps
2647
+ vsqrtps
2648
+ vpsubq
2649
+ vpsrlq
2650
+ vpminuq
2651
+ vcomisd
2652
+ vcvttsd2usi
2653
+ vandpd
2654
+ [rbp+rdx+var_xxx+CONST]
2655
+ vmovups
2656
+ vmovsldup
2657
+ vmovshdup
2658
+ vfmadd132ss
2659
+ vsqrtss
2660
+ vsubss
2661
+ vpunpcklqdq
2662
+ vfmadd132ps
2663
+ vpermt2ps
2664
+ vpermi2ps
2665
+ vpmullq
2666
+ vmaxsd
2667
+ andn
2668
+ [rdx+rdx*8+CONST]
2669
+ shrd
2670
+ fxam
2671
+ fnstsw
2672
+ [rsp+r9+CONST+var_xxx+CONST]
2673
+ [r13+rdi*2+CONST]
2674
+ [rbp+rcx+arg_xxx]
2675
+ [rsp+r10+CONST+var_xxx+CONST]
2676
+ [r9+r12*4+CONST]
2677
+ rdrand
2678
+ rdseed
2679
+ +28h
2680
+ [rax+r11*2+CONST]
2681
+ [r12+r10*4+CONST]
2682
+ [r14+r11*4+CONST]
2683
+ [rdx+r15*2+CONST]
2684
+ [rcx+r10*2]
2685
+ [rcx+r14*2]
2686
+ [r10+rsi*2+CONST]
2687
+ [rbp+rax*4+CONST_VAR]
2688
+ [rbp+rcx*4+CONST_VAR]
2689
+ syscall
2690
+ [r13+r11*2+CONST]
2691
+ [rsp+r13*8+CONST+CONST_VAR]
2692
+ [rsp+rdi*8+CONST+arg_xxx]
2693
+ [rsp+rsi*8+CONST+arg_xxx]
2694
+ [rsp+r14*8+CONST+arg_xxx]
2695
+ [rsp+r8*8+CONST+arg_xxx]
2696
+ [rsp+r13*8+CONST+arg_xxx]
2697
+ [r15+r15*4+CONST]
2698
+ [rax+r9*2+CONST]
2699
+ [rbx+rbx*8+CONST]
2700
+ [rbp+arg_xxx+CONST]
2701
+ [r15+r14*2]
2702
+ [CONST_VAR+rbp*4+CONST]
2703
+ pmulhw
2704
+ psraw
2705
+ packssdw
2706
+ [r8+r11*2+CONST]
2707
+ pmulhuw
2708
+ [rbx+r9*2+CONST]
2709
+ [rbx+r10*2+CONST]
2710
+ [r9+r11*4+CONST]
2711
+ [r15+r12*4+CONST]
2712
+ [rbp+r15*8+var_xxx]
2713
+ [rbp+r15*8+var_xxx+CONST]
2714
+ [rbp+rax*4+var_xxx+CONST]
2715
+ [rbp+rcx*4+var_xxx+CONST]
2716
+ [rsp+rbx+CONST+arg_xxx]
2717
+ [rsp+r13+CONST+var_xxx+CONST]
2718
+ [rsp+rax*2+arg_xxx]
2719
+ [rsp+rdx*2+arg_xxx]
2720
+ [r15+r11*2]
2721
+ [rsp+rbp*2+CONST+var_xxx+CONST]
2722
+ [r8+r15*2+CONST]
2723
+ [r14+r12*2+CONST]
2724
+ [rsp+rax+CONST+arg_xxx+CONST]
2725
+ [rsp+r15+CONST]
2726
+ [rsp+r8*4+CONST+CONST_VAR]
2727
+ [rsp+r10*4+CONST+CONST_VAR]
2728
+ [rsp+rbx+CONST]
2729
+ [rcx+r15*4+CONST]
2730
+ [r11+rdx*4+CONST]
2731
+ [rsp+rcx*8+CONST+var_xxx+CONST]
2732
+ [r10+r12*8]
2733
+ [rsp+rdi*8+arg_xxx]
2734
+ [rsp+rax*8+arg_xxx]
2735
+ [r15+r11*8+CONST]
2736
+ [rbp+r8*4+var_xxx]
2737
+ [rsp+rax*4+CONST+CONST_VAR+CONST]
2738
+ [rsp+rdx*4+CONST+CONST_VAR+CONST]
2739
+ [rsp+rsi*4+CONST+arg_xxx]
2740
+ [rsp+rax*4+CONST+arg_xxx+CONST]
2741
+ [rsp+r9*4+CONST+arg_xxx+CONST]
2742
+ [rcx+r9*8+CONST]
2743
+ [rsp+r10*8+CONST+CONST_VAR]
2744
+ [rsp+r11*8+CONST+CONST_VAR]
2745
+ [rsp+r15*8+CONST+CONST_VAR]
2746
+ [rsp+rbx*8+CONST+CONST_VAR]
2747
+ [rsp+r12*8+CONST+CONST_VAR]
2748
+ [r15+r10*8+CONST]
2749
+ [rbp+r14*4+var_xxx]
2750
+ [rcx+r10*8+CONST]
2751
+ [rsp+r8*4+CONST+arg_xxx+CONST]
2752
+ [rbp+rax*8+CONST_VAR]
2753
+ [r8+r8*8+CONST]
2754
+ [rbp+rbx+var_xxx+CONST]
2755
+ [r10+r11*4+CONST]
2756
+ [rsp+rbx*4+CONST+CONST_VAR]
2757
+ [rsp+rbp*4+CONST_VAR]
2758
+ +50h
2759
+ [r15+r9*4+CONST]
2760
+ [rcx+rbx*2+CONST]
2761
+ [rsp+r10*8+CONST+var_xxx+CONST]
2762
+ [rsp+r9*8+CONST+var_xxx+CONST]
2763
+ [rsp+rsi*8+CONST+var_xxx+CONST]
2764
+ [r15+rcx*2+CONST]
2765
+ [r15+rsi*2+CONST]
2766
+ [rsp+rbx*8+CONST+arg_xxx]
2767
+ [r11+rsi*4+CONST]
2768
+ [rsp+rax*2+CONST+var_xxx+CONST]
2769
+ [r14+rdi*2+CONST]
2770
+ [r15+r12*2+CONST]
2771
+ [rbx+r11*8+CONST]
2772
+ [r9+rsi*2+CONST]
2773
+ [rbp+rax*2+var_xxx]
2774
+ [rsp+CONST_VAR+CONST+arg_xxx]
2775
+ [rsp+rdx+CONST+arg_xxx]
2776
+ [r11+rbp*4+CONST]
2777
+ [r11+r13*2]
2778
+ [r13+rax+CONST_VAR]
2779
+ [r11+r15*2]
2780
+ sin
2781
+ [r9+r13*4+CONST]
2782
+ setns
2783
+ std
2784
+ [rsp+rax*4+CONST]
2785
+ [r11+rcx*2+CONST]
2786
+ [rsp+r9*8+CONST+arg_xxx]
2787
+ [rsp+r9+CONST+arg_xxx]
2788
+ [rbp+rcx+var_xxx+CONST]
2789
+ [rbp+r9*8+var_xxx]
2790
+ [rbp+r12*4+var_xxx]
2791
+ [rsp+rbp+var_xxx]
2792
+ [rbp+r12+var_xxx]
2793
+ [rsp+rbp*4+CONST+var_xxx+CONST]
2794
+ kmovd
2795
+ [rsp+r14*2+CONST+var_xxx+CONST]
2796
+ korb
2797
+ kmovq
2798
+ k3
2799
+ knotq
2800
+ k4
2801
+ k5
2802
+ k6
2803
+ k7
2804
+ [rbp+rbx+var_xxx]
2805
+ enter
2806
+ [r8+rbp*2+CONST]
2807
+ [rsp+r13+CONST+arg_xxx]
2808
+ [rsp+rdx*8+CONST]
2809
+ [rsp+rdx*8+arg_xxx]
2810
+ [r12+r15*2+CONST]
2811
+ [rax+r11*4+CONST]
2812
+ [rbp+rbx*4+var_xxx]
2813
+ [rsp+rbx*2+CONST+CONST_VAR]
2814
+ [rsp+rbx+CONST+arg_xxx+CONST]
2815
+ [r9+r12*2]
2816
+ [r9+r14*2+CONST]
2817
+ [rsp+rcx*4+CONST+CONST_VAR]
2818
+ [rsp+rsi*2+CONST+var_xxx+CONST]
2819
+ [rsp+rcx+var_xxx]
2820
+ [rsp+rax+var_xxx+CONST]
2821
+ [r14+rbp*2+CONST]
2822
+ [rbp+rdi*8+var_xxx]
2823
+ [rbp+r10*8+var_xxx]
2824
+ [r14+rdi*4+CONST]
2825
+ [rbp+r15*4+var_xxx]
2826
+ [r8+r11*4+CONST]
2827
+ [rsp+rbx*8+CONST+CONST_VAR+CONST]
2828
+ [r15+r9*2+CONST]
2829
+ [rdx+r11*2+CONST]
2830
+ [r15+r10*2+CONST]
2831
+ [r10+r14*2]
2832
+ [rcx+r9*2+CONST]
2833
+ [rbp+rbx*8+CONST_VAR]
2834
+ fsubp
2835
+ [rbp+rdx*8+CONST_VAR]
2836
+ [rbp+rdx*2+var_xxx]
2837
+ [rbp+rdx*4+CONST_VAR]
2838
+ [rbp+rax*2+CONST_VAR]
2839
+ +14h
2840
+ [rbp+rcx+CONST_VAR]
2841
+ [rbp+rdx*4+var_xxx+CONST]
2842
+ +0Ah
2843
+ [rbp+rax*8+var_xxx+CONST]
2844
+ a3
2845
+ a46
2846
+ vmovlhps
2847
+ mm1
2848
+ mm5
2849
+ cmpnleps
2850
+ [rcx+r13*4+CONST]
2851
+ [rsp+rcx*2+CONST+var_xxx+CONST]
2852
+ [r9+r12*2+CONST]
2853
+ [r8+rbx*4+CONST]
2854
+ [rbp+rbx*2+var_xxx]
2855
+ movsq
2856
+ movsw
2857
+ [rdx+r11*4+CONST]
2858
+ [r15+rdi*2+CONST]
2859
+ [r15+r11*2+CONST]
2860
+ [rcx+rbp*2+CONST]
2861
+ [rcx+r14*2+CONST]
2862
+ rcr
2863
+ [rsp+r14*8+CONST+var_xxx+CONST]
2864
+ [rcx+r10*2+CONST]
2865
+ [rbp+r8+var_xxx+CONST]
2866
+ [r15+r8*2+CONST]
2867
+ [r14+r9*4+CONST]
2868
+ [rsp+r15*4+CONST+var_xxx+CONST]
2869
+ [rbp+r14+var_xxx]
2870
+ [rbp+r14+var_xxx+CONST]
2871
+ [rbp+r15+var_xxx]
2872
+ [rsp+r8*4+CONST+var_xxx+CONST]
2873
+ [r12+r10*2+CONST]
2874
+ +8
2875
+ xlat
2876
+ [r8+rdi*2+CONST]
2877
+ [rsp+rdx+var_xxx]
2878
+ [rbp+r10*8+var_xxx+CONST]
2879
+ [rsp+rbp+CONST+arg_xxx]
2880
+ [rbp+rdx*2+var_xxx+CONST]
2881
+ [rsp+r13*2+CONST+var_xxx+CONST]
2882
+ [r11+rsi*2+CONST]
2883
+ [r14+r14*8+CONST]
2884
+ [rbp+r9*4+var_xxx]
2885
+ dest
2886
+ [r12+r11*2]
2887
+ [rbx+r11*2+CONST]
2888
+ [r11+r12*2+CONST]
2889
+ [r11+r9*2+CONST]
2890
+ [rcx+r15*2+CONST]
2891
+ [r11+rdi*2+CONST]
2892
+ [rsp+rax*2+CONST+CONST_VAR]
2893
+ [rsp+rdi*2+CONST+CONST_VAR]
2894
+ [rsp+rsi*2+CONST+CONST_VAR]
2895
+ [r9+r13*2]
2896
+ [rbp+rdx*8+var_xxx+CONST]
2897
+ JUMP_ADDR_EXCEEDED
2898
+ UNK_JUMP_ADDR