agomberto commited on
Commit
4c59f28
1 Parent(s): 190b633

Upload 12 files

Browse files
config.json ADDED
@@ -0,0 +1,2177 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_commit_hash": null,
3
+ "architectures": [
4
+ "VisionEncoderDecoderModel"
5
+ ],
6
+ "decoder": {
7
+ "_name_or_path": "camembert-base",
8
+ "add_cross_attention": true,
9
+ "architectures": [
10
+ "CamembertForMaskedLM"
11
+ ],
12
+ "attention_probs_dropout_prob": 0.1,
13
+ "bad_words_ids": null,
14
+ "begin_suppress_tokens": null,
15
+ "bos_token_id": 5,
16
+ "chunk_size_feed_forward": 0,
17
+ "classifier_dropout": null,
18
+ "cross_attention_hidden_size": null,
19
+ "decoder_start_token_id": null,
20
+ "diversity_penalty": 0.0,
21
+ "do_sample": false,
22
+ "early_stopping": false,
23
+ "encoder_no_repeat_ngram_size": 0,
24
+ "eos_token_id": 6,
25
+ "exponential_decay_length_penalty": null,
26
+ "finetuning_task": null,
27
+ "forced_bos_token_id": null,
28
+ "forced_eos_token_id": null,
29
+ "hidden_act": "gelu",
30
+ "hidden_dropout_prob": 0.1,
31
+ "hidden_size": 768,
32
+ "id2label": {
33
+ "0": "LABEL_0",
34
+ "1": "LABEL_1"
35
+ },
36
+ "initializer_range": 0.02,
37
+ "intermediate_size": 3072,
38
+ "is_decoder": true,
39
+ "is_encoder_decoder": false,
40
+ "label2id": {
41
+ "LABEL_0": 0,
42
+ "LABEL_1": 1
43
+ },
44
+ "layer_norm_eps": 1e-05,
45
+ "length_penalty": 1.0,
46
+ "max_length": 20,
47
+ "max_position_embeddings": 514,
48
+ "min_length": 0,
49
+ "model_type": "camembert",
50
+ "no_repeat_ngram_size": 0,
51
+ "num_attention_heads": 12,
52
+ "num_beam_groups": 1,
53
+ "num_beams": 1,
54
+ "num_hidden_layers": 12,
55
+ "num_return_sequences": 1,
56
+ "output_attentions": false,
57
+ "output_hidden_states": false,
58
+ "output_past": true,
59
+ "output_scores": false,
60
+ "pad_token_id": 1,
61
+ "position_embedding_type": "absolute",
62
+ "prefix": null,
63
+ "problem_type": null,
64
+ "pruned_heads": {},
65
+ "remove_invalid_values": false,
66
+ "repetition_penalty": 1.0,
67
+ "return_dict": true,
68
+ "return_dict_in_generate": false,
69
+ "sep_token_id": null,
70
+ "suppress_tokens": null,
71
+ "task_specific_params": null,
72
+ "temperature": 1.0,
73
+ "tf_legacy_loss": false,
74
+ "tie_encoder_decoder": false,
75
+ "tie_word_embeddings": true,
76
+ "tokenizer_class": null,
77
+ "top_k": 50,
78
+ "top_p": 1.0,
79
+ "torch_dtype": null,
80
+ "torchscript": false,
81
+ "transformers_version": "4.28.1",
82
+ "type_vocab_size": 1,
83
+ "typical_p": 1.0,
84
+ "use_bfloat16": false,
85
+ "use_cache": true,
86
+ "vocab_size": 32005
87
+ },
88
+ "decoder_start_token_id": 0,
89
+ "early_stopping": true,
90
+ "encoder": {
91
+ "_name_or_path": "facebook/deit-base-distilled-patch16-384",
92
+ "add_cross_attention": false,
93
+ "architectures": [
94
+ "DeiTForImageClassificationWithTeacher"
95
+ ],
96
+ "attention_probs_dropout_prob": 0.0,
97
+ "bad_words_ids": null,
98
+ "begin_suppress_tokens": null,
99
+ "bos_token_id": null,
100
+ "chunk_size_feed_forward": 0,
101
+ "cross_attention_hidden_size": null,
102
+ "decoder_start_token_id": null,
103
+ "diversity_penalty": 0.0,
104
+ "do_sample": false,
105
+ "early_stopping": false,
106
+ "encoder_no_repeat_ngram_size": 0,
107
+ "encoder_stride": 16,
108
+ "eos_token_id": null,
109
+ "exponential_decay_length_penalty": null,
110
+ "finetuning_task": null,
111
+ "forced_bos_token_id": null,
112
+ "forced_eos_token_id": null,
113
+ "hidden_act": "gelu",
114
+ "hidden_dropout_prob": 0.0,
115
+ "hidden_size": 768,
116
+ "id2label": {
117
+ "0": "tench, Tinca tinca",
118
+ "1": "goldfish, Carassius auratus",
119
+ "2": "great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias",
120
+ "3": "tiger shark, Galeocerdo cuvieri",
121
+ "4": "hammerhead, hammerhead shark",
122
+ "5": "electric ray, crampfish, numbfish, torpedo",
123
+ "6": "stingray",
124
+ "7": "cock",
125
+ "8": "hen",
126
+ "9": "ostrich, Struthio camelus",
127
+ "10": "brambling, Fringilla montifringilla",
128
+ "11": "goldfinch, Carduelis carduelis",
129
+ "12": "house finch, linnet, Carpodacus mexicanus",
130
+ "13": "junco, snowbird",
131
+ "14": "indigo bunting, indigo finch, indigo bird, Passerina cyanea",
132
+ "15": "robin, American robin, Turdus migratorius",
133
+ "16": "bulbul",
134
+ "17": "jay",
135
+ "18": "magpie",
136
+ "19": "chickadee",
137
+ "20": "water ouzel, dipper",
138
+ "21": "kite",
139
+ "22": "bald eagle, American eagle, Haliaeetus leucocephalus",
140
+ "23": "vulture",
141
+ "24": "great grey owl, great gray owl, Strix nebulosa",
142
+ "25": "European fire salamander, Salamandra salamandra",
143
+ "26": "common newt, Triturus vulgaris",
144
+ "27": "eft",
145
+ "28": "spotted salamander, Ambystoma maculatum",
146
+ "29": "axolotl, mud puppy, Ambystoma mexicanum",
147
+ "30": "bullfrog, Rana catesbeiana",
148
+ "31": "tree frog, tree-frog",
149
+ "32": "tailed frog, bell toad, ribbed toad, tailed toad, Ascaphus trui",
150
+ "33": "loggerhead, loggerhead turtle, Caretta caretta",
151
+ "34": "leatherback turtle, leatherback, leathery turtle, Dermochelys coriacea",
152
+ "35": "mud turtle",
153
+ "36": "terrapin",
154
+ "37": "box turtle, box tortoise",
155
+ "38": "banded gecko",
156
+ "39": "common iguana, iguana, Iguana iguana",
157
+ "40": "American chameleon, anole, Anolis carolinensis",
158
+ "41": "whiptail, whiptail lizard",
159
+ "42": "agama",
160
+ "43": "frilled lizard, Chlamydosaurus kingi",
161
+ "44": "alligator lizard",
162
+ "45": "Gila monster, Heloderma suspectum",
163
+ "46": "green lizard, Lacerta viridis",
164
+ "47": "African chameleon, Chamaeleo chamaeleon",
165
+ "48": "Komodo dragon, Komodo lizard, dragon lizard, giant lizard, Varanus komodoensis",
166
+ "49": "African crocodile, Nile crocodile, Crocodylus niloticus",
167
+ "50": "American alligator, Alligator mississipiensis",
168
+ "51": "triceratops",
169
+ "52": "thunder snake, worm snake, Carphophis amoenus",
170
+ "53": "ringneck snake, ring-necked snake, ring snake",
171
+ "54": "hognose snake, puff adder, sand viper",
172
+ "55": "green snake, grass snake",
173
+ "56": "king snake, kingsnake",
174
+ "57": "garter snake, grass snake",
175
+ "58": "water snake",
176
+ "59": "vine snake",
177
+ "60": "night snake, Hypsiglena torquata",
178
+ "61": "boa constrictor, Constrictor constrictor",
179
+ "62": "rock python, rock snake, Python sebae",
180
+ "63": "Indian cobra, Naja naja",
181
+ "64": "green mamba",
182
+ "65": "sea snake",
183
+ "66": "horned viper, cerastes, sand viper, horned asp, Cerastes cornutus",
184
+ "67": "diamondback, diamondback rattlesnake, Crotalus adamanteus",
185
+ "68": "sidewinder, horned rattlesnake, Crotalus cerastes",
186
+ "69": "trilobite",
187
+ "70": "harvestman, daddy longlegs, Phalangium opilio",
188
+ "71": "scorpion",
189
+ "72": "black and gold garden spider, Argiope aurantia",
190
+ "73": "barn spider, Araneus cavaticus",
191
+ "74": "garden spider, Aranea diademata",
192
+ "75": "black widow, Latrodectus mactans",
193
+ "76": "tarantula",
194
+ "77": "wolf spider, hunting spider",
195
+ "78": "tick",
196
+ "79": "centipede",
197
+ "80": "black grouse",
198
+ "81": "ptarmigan",
199
+ "82": "ruffed grouse, partridge, Bonasa umbellus",
200
+ "83": "prairie chicken, prairie grouse, prairie fowl",
201
+ "84": "peacock",
202
+ "85": "quail",
203
+ "86": "partridge",
204
+ "87": "African grey, African gray, Psittacus erithacus",
205
+ "88": "macaw",
206
+ "89": "sulphur-crested cockatoo, Kakatoe galerita, Cacatua galerita",
207
+ "90": "lorikeet",
208
+ "91": "coucal",
209
+ "92": "bee eater",
210
+ "93": "hornbill",
211
+ "94": "hummingbird",
212
+ "95": "jacamar",
213
+ "96": "toucan",
214
+ "97": "drake",
215
+ "98": "red-breasted merganser, Mergus serrator",
216
+ "99": "goose",
217
+ "100": "black swan, Cygnus atratus",
218
+ "101": "tusker",
219
+ "102": "echidna, spiny anteater, anteater",
220
+ "103": "platypus, duckbill, duckbilled platypus, duck-billed platypus, Ornithorhynchus anatinus",
221
+ "104": "wallaby, brush kangaroo",
222
+ "105": "koala, koala bear, kangaroo bear, native bear, Phascolarctos cinereus",
223
+ "106": "wombat",
224
+ "107": "jellyfish",
225
+ "108": "sea anemone, anemone",
226
+ "109": "brain coral",
227
+ "110": "flatworm, platyhelminth",
228
+ "111": "nematode, nematode worm, roundworm",
229
+ "112": "conch",
230
+ "113": "snail",
231
+ "114": "slug",
232
+ "115": "sea slug, nudibranch",
233
+ "116": "chiton, coat-of-mail shell, sea cradle, polyplacophore",
234
+ "117": "chambered nautilus, pearly nautilus, nautilus",
235
+ "118": "Dungeness crab, Cancer magister",
236
+ "119": "rock crab, Cancer irroratus",
237
+ "120": "fiddler crab",
238
+ "121": "king crab, Alaska crab, Alaskan king crab, Alaska king crab, Paralithodes camtschatica",
239
+ "122": "American lobster, Northern lobster, Maine lobster, Homarus americanus",
240
+ "123": "spiny lobster, langouste, rock lobster, crawfish, crayfish, sea crawfish",
241
+ "124": "crayfish, crawfish, crawdad, crawdaddy",
242
+ "125": "hermit crab",
243
+ "126": "isopod",
244
+ "127": "white stork, Ciconia ciconia",
245
+ "128": "black stork, Ciconia nigra",
246
+ "129": "spoonbill",
247
+ "130": "flamingo",
248
+ "131": "little blue heron, Egretta caerulea",
249
+ "132": "American egret, great white heron, Egretta albus",
250
+ "133": "bittern",
251
+ "134": "crane",
252
+ "135": "limpkin, Aramus pictus",
253
+ "136": "European gallinule, Porphyrio porphyrio",
254
+ "137": "American coot, marsh hen, mud hen, water hen, Fulica americana",
255
+ "138": "bustard",
256
+ "139": "ruddy turnstone, Arenaria interpres",
257
+ "140": "red-backed sandpiper, dunlin, Erolia alpina",
258
+ "141": "redshank, Tringa totanus",
259
+ "142": "dowitcher",
260
+ "143": "oystercatcher, oyster catcher",
261
+ "144": "pelican",
262
+ "145": "king penguin, Aptenodytes patagonica",
263
+ "146": "albatross, mollymawk",
264
+ "147": "grey whale, gray whale, devilfish, Eschrichtius gibbosus, Eschrichtius robustus",
265
+ "148": "killer whale, killer, orca, grampus, sea wolf, Orcinus orca",
266
+ "149": "dugong, Dugong dugon",
267
+ "150": "sea lion",
268
+ "151": "Chihuahua",
269
+ "152": "Japanese spaniel",
270
+ "153": "Maltese dog, Maltese terrier, Maltese",
271
+ "154": "Pekinese, Pekingese, Peke",
272
+ "155": "Shih-Tzu",
273
+ "156": "Blenheim spaniel",
274
+ "157": "papillon",
275
+ "158": "toy terrier",
276
+ "159": "Rhodesian ridgeback",
277
+ "160": "Afghan hound, Afghan",
278
+ "161": "basset, basset hound",
279
+ "162": "beagle",
280
+ "163": "bloodhound, sleuthhound",
281
+ "164": "bluetick",
282
+ "165": "black-and-tan coonhound",
283
+ "166": "Walker hound, Walker foxhound",
284
+ "167": "English foxhound",
285
+ "168": "redbone",
286
+ "169": "borzoi, Russian wolfhound",
287
+ "170": "Irish wolfhound",
288
+ "171": "Italian greyhound",
289
+ "172": "whippet",
290
+ "173": "Ibizan hound, Ibizan Podenco",
291
+ "174": "Norwegian elkhound, elkhound",
292
+ "175": "otterhound, otter hound",
293
+ "176": "Saluki, gazelle hound",
294
+ "177": "Scottish deerhound, deerhound",
295
+ "178": "Weimaraner",
296
+ "179": "Staffordshire bullterrier, Staffordshire bull terrier",
297
+ "180": "American Staffordshire terrier, Staffordshire terrier, American pit bull terrier, pit bull terrier",
298
+ "181": "Bedlington terrier",
299
+ "182": "Border terrier",
300
+ "183": "Kerry blue terrier",
301
+ "184": "Irish terrier",
302
+ "185": "Norfolk terrier",
303
+ "186": "Norwich terrier",
304
+ "187": "Yorkshire terrier",
305
+ "188": "wire-haired fox terrier",
306
+ "189": "Lakeland terrier",
307
+ "190": "Sealyham terrier, Sealyham",
308
+ "191": "Airedale, Airedale terrier",
309
+ "192": "cairn, cairn terrier",
310
+ "193": "Australian terrier",
311
+ "194": "Dandie Dinmont, Dandie Dinmont terrier",
312
+ "195": "Boston bull, Boston terrier",
313
+ "196": "miniature schnauzer",
314
+ "197": "giant schnauzer",
315
+ "198": "standard schnauzer",
316
+ "199": "Scotch terrier, Scottish terrier, Scottie",
317
+ "200": "Tibetan terrier, chrysanthemum dog",
318
+ "201": "silky terrier, Sydney silky",
319
+ "202": "soft-coated wheaten terrier",
320
+ "203": "West Highland white terrier",
321
+ "204": "Lhasa, Lhasa apso",
322
+ "205": "flat-coated retriever",
323
+ "206": "curly-coated retriever",
324
+ "207": "golden retriever",
325
+ "208": "Labrador retriever",
326
+ "209": "Chesapeake Bay retriever",
327
+ "210": "German short-haired pointer",
328
+ "211": "vizsla, Hungarian pointer",
329
+ "212": "English setter",
330
+ "213": "Irish setter, red setter",
331
+ "214": "Gordon setter",
332
+ "215": "Brittany spaniel",
333
+ "216": "clumber, clumber spaniel",
334
+ "217": "English springer, English springer spaniel",
335
+ "218": "Welsh springer spaniel",
336
+ "219": "cocker spaniel, English cocker spaniel, cocker",
337
+ "220": "Sussex spaniel",
338
+ "221": "Irish water spaniel",
339
+ "222": "kuvasz",
340
+ "223": "schipperke",
341
+ "224": "groenendael",
342
+ "225": "malinois",
343
+ "226": "briard",
344
+ "227": "kelpie",
345
+ "228": "komondor",
346
+ "229": "Old English sheepdog, bobtail",
347
+ "230": "Shetland sheepdog, Shetland sheep dog, Shetland",
348
+ "231": "collie",
349
+ "232": "Border collie",
350
+ "233": "Bouvier des Flandres, Bouviers des Flandres",
351
+ "234": "Rottweiler",
352
+ "235": "German shepherd, German shepherd dog, German police dog, alsatian",
353
+ "236": "Doberman, Doberman pinscher",
354
+ "237": "miniature pinscher",
355
+ "238": "Greater Swiss Mountain dog",
356
+ "239": "Bernese mountain dog",
357
+ "240": "Appenzeller",
358
+ "241": "EntleBucher",
359
+ "242": "boxer",
360
+ "243": "bull mastiff",
361
+ "244": "Tibetan mastiff",
362
+ "245": "French bulldog",
363
+ "246": "Great Dane",
364
+ "247": "Saint Bernard, St Bernard",
365
+ "248": "Eskimo dog, husky",
366
+ "249": "malamute, malemute, Alaskan malamute",
367
+ "250": "Siberian husky",
368
+ "251": "dalmatian, coach dog, carriage dog",
369
+ "252": "affenpinscher, monkey pinscher, monkey dog",
370
+ "253": "basenji",
371
+ "254": "pug, pug-dog",
372
+ "255": "Leonberg",
373
+ "256": "Newfoundland, Newfoundland dog",
374
+ "257": "Great Pyrenees",
375
+ "258": "Samoyed, Samoyede",
376
+ "259": "Pomeranian",
377
+ "260": "chow, chow chow",
378
+ "261": "keeshond",
379
+ "262": "Brabancon griffon",
380
+ "263": "Pembroke, Pembroke Welsh corgi",
381
+ "264": "Cardigan, Cardigan Welsh corgi",
382
+ "265": "toy poodle",
383
+ "266": "miniature poodle",
384
+ "267": "standard poodle",
385
+ "268": "Mexican hairless",
386
+ "269": "timber wolf, grey wolf, gray wolf, Canis lupus",
387
+ "270": "white wolf, Arctic wolf, Canis lupus tundrarum",
388
+ "271": "red wolf, maned wolf, Canis rufus, Canis niger",
389
+ "272": "coyote, prairie wolf, brush wolf, Canis latrans",
390
+ "273": "dingo, warrigal, warragal, Canis dingo",
391
+ "274": "dhole, Cuon alpinus",
392
+ "275": "African hunting dog, hyena dog, Cape hunting dog, Lycaon pictus",
393
+ "276": "hyena, hyaena",
394
+ "277": "red fox, Vulpes vulpes",
395
+ "278": "kit fox, Vulpes macrotis",
396
+ "279": "Arctic fox, white fox, Alopex lagopus",
397
+ "280": "grey fox, gray fox, Urocyon cinereoargenteus",
398
+ "281": "tabby, tabby cat",
399
+ "282": "tiger cat",
400
+ "283": "Persian cat",
401
+ "284": "Siamese cat, Siamese",
402
+ "285": "Egyptian cat",
403
+ "286": "cougar, puma, catamount, mountain lion, painter, panther, Felis concolor",
404
+ "287": "lynx, catamount",
405
+ "288": "leopard, Panthera pardus",
406
+ "289": "snow leopard, ounce, Panthera uncia",
407
+ "290": "jaguar, panther, Panthera onca, Felis onca",
408
+ "291": "lion, king of beasts, Panthera leo",
409
+ "292": "tiger, Panthera tigris",
410
+ "293": "cheetah, chetah, Acinonyx jubatus",
411
+ "294": "brown bear, bruin, Ursus arctos",
412
+ "295": "American black bear, black bear, Ursus americanus, Euarctos americanus",
413
+ "296": "ice bear, polar bear, Ursus Maritimus, Thalarctos maritimus",
414
+ "297": "sloth bear, Melursus ursinus, Ursus ursinus",
415
+ "298": "mongoose",
416
+ "299": "meerkat, mierkat",
417
+ "300": "tiger beetle",
418
+ "301": "ladybug, ladybeetle, lady beetle, ladybird, ladybird beetle",
419
+ "302": "ground beetle, carabid beetle",
420
+ "303": "long-horned beetle, longicorn, longicorn beetle",
421
+ "304": "leaf beetle, chrysomelid",
422
+ "305": "dung beetle",
423
+ "306": "rhinoceros beetle",
424
+ "307": "weevil",
425
+ "308": "fly",
426
+ "309": "bee",
427
+ "310": "ant, emmet, pismire",
428
+ "311": "grasshopper, hopper",
429
+ "312": "cricket",
430
+ "313": "walking stick, walkingstick, stick insect",
431
+ "314": "cockroach, roach",
432
+ "315": "mantis, mantid",
433
+ "316": "cicada, cicala",
434
+ "317": "leafhopper",
435
+ "318": "lacewing, lacewing fly",
436
+ "319": "dragonfly, darning needle, devil's darning needle, sewing needle, snake feeder, snake doctor, mosquito hawk, skeeter hawk",
437
+ "320": "damselfly",
438
+ "321": "admiral",
439
+ "322": "ringlet, ringlet butterfly",
440
+ "323": "monarch, monarch butterfly, milkweed butterfly, Danaus plexippus",
441
+ "324": "cabbage butterfly",
442
+ "325": "sulphur butterfly, sulfur butterfly",
443
+ "326": "lycaenid, lycaenid butterfly",
444
+ "327": "starfish, sea star",
445
+ "328": "sea urchin",
446
+ "329": "sea cucumber, holothurian",
447
+ "330": "wood rabbit, cottontail, cottontail rabbit",
448
+ "331": "hare",
449
+ "332": "Angora, Angora rabbit",
450
+ "333": "hamster",
451
+ "334": "porcupine, hedgehog",
452
+ "335": "fox squirrel, eastern fox squirrel, Sciurus niger",
453
+ "336": "marmot",
454
+ "337": "beaver",
455
+ "338": "guinea pig, Cavia cobaya",
456
+ "339": "sorrel",
457
+ "340": "zebra",
458
+ "341": "hog, pig, grunter, squealer, Sus scrofa",
459
+ "342": "wild boar, boar, Sus scrofa",
460
+ "343": "warthog",
461
+ "344": "hippopotamus, hippo, river horse, Hippopotamus amphibius",
462
+ "345": "ox",
463
+ "346": "water buffalo, water ox, Asiatic buffalo, Bubalus bubalis",
464
+ "347": "bison",
465
+ "348": "ram, tup",
466
+ "349": "bighorn, bighorn sheep, cimarron, Rocky Mountain bighorn, Rocky Mountain sheep, Ovis canadensis",
467
+ "350": "ibex, Capra ibex",
468
+ "351": "hartebeest",
469
+ "352": "impala, Aepyceros melampus",
470
+ "353": "gazelle",
471
+ "354": "Arabian camel, dromedary, Camelus dromedarius",
472
+ "355": "llama",
473
+ "356": "weasel",
474
+ "357": "mink",
475
+ "358": "polecat, fitch, foulmart, foumart, Mustela putorius",
476
+ "359": "black-footed ferret, ferret, Mustela nigripes",
477
+ "360": "otter",
478
+ "361": "skunk, polecat, wood pussy",
479
+ "362": "badger",
480
+ "363": "armadillo",
481
+ "364": "three-toed sloth, ai, Bradypus tridactylus",
482
+ "365": "orangutan, orang, orangutang, Pongo pygmaeus",
483
+ "366": "gorilla, Gorilla gorilla",
484
+ "367": "chimpanzee, chimp, Pan troglodytes",
485
+ "368": "gibbon, Hylobates lar",
486
+ "369": "siamang, Hylobates syndactylus, Symphalangus syndactylus",
487
+ "370": "guenon, guenon monkey",
488
+ "371": "patas, hussar monkey, Erythrocebus patas",
489
+ "372": "baboon",
490
+ "373": "macaque",
491
+ "374": "langur",
492
+ "375": "colobus, colobus monkey",
493
+ "376": "proboscis monkey, Nasalis larvatus",
494
+ "377": "marmoset",
495
+ "378": "capuchin, ringtail, Cebus capucinus",
496
+ "379": "howler monkey, howler",
497
+ "380": "titi, titi monkey",
498
+ "381": "spider monkey, Ateles geoffroyi",
499
+ "382": "squirrel monkey, Saimiri sciureus",
500
+ "383": "Madagascar cat, ring-tailed lemur, Lemur catta",
501
+ "384": "indri, indris, Indri indri, Indri brevicaudatus",
502
+ "385": "Indian elephant, Elephas maximus",
503
+ "386": "African elephant, Loxodonta africana",
504
+ "387": "lesser panda, red panda, panda, bear cat, cat bear, Ailurus fulgens",
505
+ "388": "giant panda, panda, panda bear, coon bear, Ailuropoda melanoleuca",
506
+ "389": "barracouta, snoek",
507
+ "390": "eel",
508
+ "391": "coho, cohoe, coho salmon, blue jack, silver salmon, Oncorhynchus kisutch",
509
+ "392": "rock beauty, Holocanthus tricolor",
510
+ "393": "anemone fish",
511
+ "394": "sturgeon",
512
+ "395": "gar, garfish, garpike, billfish, Lepisosteus osseus",
513
+ "396": "lionfish",
514
+ "397": "puffer, pufferfish, blowfish, globefish",
515
+ "398": "abacus",
516
+ "399": "abaya",
517
+ "400": "academic gown, academic robe, judge's robe",
518
+ "401": "accordion, piano accordion, squeeze box",
519
+ "402": "acoustic guitar",
520
+ "403": "aircraft carrier, carrier, flattop, attack aircraft carrier",
521
+ "404": "airliner",
522
+ "405": "airship, dirigible",
523
+ "406": "altar",
524
+ "407": "ambulance",
525
+ "408": "amphibian, amphibious vehicle",
526
+ "409": "analog clock",
527
+ "410": "apiary, bee house",
528
+ "411": "apron",
529
+ "412": "ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin",
530
+ "413": "assault rifle, assault gun",
531
+ "414": "backpack, back pack, knapsack, packsack, rucksack, haversack",
532
+ "415": "bakery, bakeshop, bakehouse",
533
+ "416": "balance beam, beam",
534
+ "417": "balloon",
535
+ "418": "ballpoint, ballpoint pen, ballpen, Biro",
536
+ "419": "Band Aid",
537
+ "420": "banjo",
538
+ "421": "bannister, banister, balustrade, balusters, handrail",
539
+ "422": "barbell",
540
+ "423": "barber chair",
541
+ "424": "barbershop",
542
+ "425": "barn",
543
+ "426": "barometer",
544
+ "427": "barrel, cask",
545
+ "428": "barrow, garden cart, lawn cart, wheelbarrow",
546
+ "429": "baseball",
547
+ "430": "basketball",
548
+ "431": "bassinet",
549
+ "432": "bassoon",
550
+ "433": "bathing cap, swimming cap",
551
+ "434": "bath towel",
552
+ "435": "bathtub, bathing tub, bath, tub",
553
+ "436": "beach wagon, station wagon, wagon, estate car, beach waggon, station waggon, waggon",
554
+ "437": "beacon, lighthouse, beacon light, pharos",
555
+ "438": "beaker",
556
+ "439": "bearskin, busby, shako",
557
+ "440": "beer bottle",
558
+ "441": "beer glass",
559
+ "442": "bell cote, bell cot",
560
+ "443": "bib",
561
+ "444": "bicycle-built-for-two, tandem bicycle, tandem",
562
+ "445": "bikini, two-piece",
563
+ "446": "binder, ring-binder",
564
+ "447": "binoculars, field glasses, opera glasses",
565
+ "448": "birdhouse",
566
+ "449": "boathouse",
567
+ "450": "bobsled, bobsleigh, bob",
568
+ "451": "bolo tie, bolo, bola tie, bola",
569
+ "452": "bonnet, poke bonnet",
570
+ "453": "bookcase",
571
+ "454": "bookshop, bookstore, bookstall",
572
+ "455": "bottlecap",
573
+ "456": "bow",
574
+ "457": "bow tie, bow-tie, bowtie",
575
+ "458": "brass, memorial tablet, plaque",
576
+ "459": "brassiere, bra, bandeau",
577
+ "460": "breakwater, groin, groyne, mole, bulwark, seawall, jetty",
578
+ "461": "breastplate, aegis, egis",
579
+ "462": "broom",
580
+ "463": "bucket, pail",
581
+ "464": "buckle",
582
+ "465": "bulletproof vest",
583
+ "466": "bullet train, bullet",
584
+ "467": "butcher shop, meat market",
585
+ "468": "cab, hack, taxi, taxicab",
586
+ "469": "caldron, cauldron",
587
+ "470": "candle, taper, wax light",
588
+ "471": "cannon",
589
+ "472": "canoe",
590
+ "473": "can opener, tin opener",
591
+ "474": "cardigan",
592
+ "475": "car mirror",
593
+ "476": "carousel, carrousel, merry-go-round, roundabout, whirligig",
594
+ "477": "carpenter's kit, tool kit",
595
+ "478": "carton",
596
+ "479": "car wheel",
597
+ "480": "cash machine, cash dispenser, automated teller machine, automatic teller machine, automated teller, automatic teller, ATM",
598
+ "481": "cassette",
599
+ "482": "cassette player",
600
+ "483": "castle",
601
+ "484": "catamaran",
602
+ "485": "CD player",
603
+ "486": "cello, violoncello",
604
+ "487": "cellular telephone, cellular phone, cellphone, cell, mobile phone",
605
+ "488": "chain",
606
+ "489": "chainlink fence",
607
+ "490": "chain mail, ring mail, mail, chain armor, chain armour, ring armor, ring armour",
608
+ "491": "chain saw, chainsaw",
609
+ "492": "chest",
610
+ "493": "chiffonier, commode",
611
+ "494": "chime, bell, gong",
612
+ "495": "china cabinet, china closet",
613
+ "496": "Christmas stocking",
614
+ "497": "church, church building",
615
+ "498": "cinema, movie theater, movie theatre, movie house, picture palace",
616
+ "499": "cleaver, meat cleaver, chopper",
617
+ "500": "cliff dwelling",
618
+ "501": "cloak",
619
+ "502": "clog, geta, patten, sabot",
620
+ "503": "cocktail shaker",
621
+ "504": "coffee mug",
622
+ "505": "coffeepot",
623
+ "506": "coil, spiral, volute, whorl, helix",
624
+ "507": "combination lock",
625
+ "508": "computer keyboard, keypad",
626
+ "509": "confectionery, confectionary, candy store",
627
+ "510": "container ship, containership, container vessel",
628
+ "511": "convertible",
629
+ "512": "corkscrew, bottle screw",
630
+ "513": "cornet, horn, trumpet, trump",
631
+ "514": "cowboy boot",
632
+ "515": "cowboy hat, ten-gallon hat",
633
+ "516": "cradle",
634
+ "517": "crane",
635
+ "518": "crash helmet",
636
+ "519": "crate",
637
+ "520": "crib, cot",
638
+ "521": "Crock Pot",
639
+ "522": "croquet ball",
640
+ "523": "crutch",
641
+ "524": "cuirass",
642
+ "525": "dam, dike, dyke",
643
+ "526": "desk",
644
+ "527": "desktop computer",
645
+ "528": "dial telephone, dial phone",
646
+ "529": "diaper, nappy, napkin",
647
+ "530": "digital clock",
648
+ "531": "digital watch",
649
+ "532": "dining table, board",
650
+ "533": "dishrag, dishcloth",
651
+ "534": "dishwasher, dish washer, dishwashing machine",
652
+ "535": "disk brake, disc brake",
653
+ "536": "dock, dockage, docking facility",
654
+ "537": "dogsled, dog sled, dog sleigh",
655
+ "538": "dome",
656
+ "539": "doormat, welcome mat",
657
+ "540": "drilling platform, offshore rig",
658
+ "541": "drum, membranophone, tympan",
659
+ "542": "drumstick",
660
+ "543": "dumbbell",
661
+ "544": "Dutch oven",
662
+ "545": "electric fan, blower",
663
+ "546": "electric guitar",
664
+ "547": "electric locomotive",
665
+ "548": "entertainment center",
666
+ "549": "envelope",
667
+ "550": "espresso maker",
668
+ "551": "face powder",
669
+ "552": "feather boa, boa",
670
+ "553": "file, file cabinet, filing cabinet",
671
+ "554": "fireboat",
672
+ "555": "fire engine, fire truck",
673
+ "556": "fire screen, fireguard",
674
+ "557": "flagpole, flagstaff",
675
+ "558": "flute, transverse flute",
676
+ "559": "folding chair",
677
+ "560": "football helmet",
678
+ "561": "forklift",
679
+ "562": "fountain",
680
+ "563": "fountain pen",
681
+ "564": "four-poster",
682
+ "565": "freight car",
683
+ "566": "French horn, horn",
684
+ "567": "frying pan, frypan, skillet",
685
+ "568": "fur coat",
686
+ "569": "garbage truck, dustcart",
687
+ "570": "gasmask, respirator, gas helmet",
688
+ "571": "gas pump, gasoline pump, petrol pump, island dispenser",
689
+ "572": "goblet",
690
+ "573": "go-kart",
691
+ "574": "golf ball",
692
+ "575": "golfcart, golf cart",
693
+ "576": "gondola",
694
+ "577": "gong, tam-tam",
695
+ "578": "gown",
696
+ "579": "grand piano, grand",
697
+ "580": "greenhouse, nursery, glasshouse",
698
+ "581": "grille, radiator grille",
699
+ "582": "grocery store, grocery, food market, market",
700
+ "583": "guillotine",
701
+ "584": "hair slide",
702
+ "585": "hair spray",
703
+ "586": "half track",
704
+ "587": "hammer",
705
+ "588": "hamper",
706
+ "589": "hand blower, blow dryer, blow drier, hair dryer, hair drier",
707
+ "590": "hand-held computer, hand-held microcomputer",
708
+ "591": "handkerchief, hankie, hanky, hankey",
709
+ "592": "hard disc, hard disk, fixed disk",
710
+ "593": "harmonica, mouth organ, harp, mouth harp",
711
+ "594": "harp",
712
+ "595": "harvester, reaper",
713
+ "596": "hatchet",
714
+ "597": "holster",
715
+ "598": "home theater, home theatre",
716
+ "599": "honeycomb",
717
+ "600": "hook, claw",
718
+ "601": "hoopskirt, crinoline",
719
+ "602": "horizontal bar, high bar",
720
+ "603": "horse cart, horse-cart",
721
+ "604": "hourglass",
722
+ "605": "iPod",
723
+ "606": "iron, smoothing iron",
724
+ "607": "jack-o'-lantern",
725
+ "608": "jean, blue jean, denim",
726
+ "609": "jeep, landrover",
727
+ "610": "jersey, T-shirt, tee shirt",
728
+ "611": "jigsaw puzzle",
729
+ "612": "jinrikisha, ricksha, rickshaw",
730
+ "613": "joystick",
731
+ "614": "kimono",
732
+ "615": "knee pad",
733
+ "616": "knot",
734
+ "617": "lab coat, laboratory coat",
735
+ "618": "ladle",
736
+ "619": "lampshade, lamp shade",
737
+ "620": "laptop, laptop computer",
738
+ "621": "lawn mower, mower",
739
+ "622": "lens cap, lens cover",
740
+ "623": "letter opener, paper knife, paperknife",
741
+ "624": "library",
742
+ "625": "lifeboat",
743
+ "626": "lighter, light, igniter, ignitor",
744
+ "627": "limousine, limo",
745
+ "628": "liner, ocean liner",
746
+ "629": "lipstick, lip rouge",
747
+ "630": "Loafer",
748
+ "631": "lotion",
749
+ "632": "loudspeaker, speaker, speaker unit, loudspeaker system, speaker system",
750
+ "633": "loupe, jeweler's loupe",
751
+ "634": "lumbermill, sawmill",
752
+ "635": "magnetic compass",
753
+ "636": "mailbag, postbag",
754
+ "637": "mailbox, letter box",
755
+ "638": "maillot",
756
+ "639": "maillot, tank suit",
757
+ "640": "manhole cover",
758
+ "641": "maraca",
759
+ "642": "marimba, xylophone",
760
+ "643": "mask",
761
+ "644": "matchstick",
762
+ "645": "maypole",
763
+ "646": "maze, labyrinth",
764
+ "647": "measuring cup",
765
+ "648": "medicine chest, medicine cabinet",
766
+ "649": "megalith, megalithic structure",
767
+ "650": "microphone, mike",
768
+ "651": "microwave, microwave oven",
769
+ "652": "military uniform",
770
+ "653": "milk can",
771
+ "654": "minibus",
772
+ "655": "miniskirt, mini",
773
+ "656": "minivan",
774
+ "657": "missile",
775
+ "658": "mitten",
776
+ "659": "mixing bowl",
777
+ "660": "mobile home, manufactured home",
778
+ "661": "Model T",
779
+ "662": "modem",
780
+ "663": "monastery",
781
+ "664": "monitor",
782
+ "665": "moped",
783
+ "666": "mortar",
784
+ "667": "mortarboard",
785
+ "668": "mosque",
786
+ "669": "mosquito net",
787
+ "670": "motor scooter, scooter",
788
+ "671": "mountain bike, all-terrain bike, off-roader",
789
+ "672": "mountain tent",
790
+ "673": "mouse, computer mouse",
791
+ "674": "mousetrap",
792
+ "675": "moving van",
793
+ "676": "muzzle",
794
+ "677": "nail",
795
+ "678": "neck brace",
796
+ "679": "necklace",
797
+ "680": "nipple",
798
+ "681": "notebook, notebook computer",
799
+ "682": "obelisk",
800
+ "683": "oboe, hautboy, hautbois",
801
+ "684": "ocarina, sweet potato",
802
+ "685": "odometer, hodometer, mileometer, milometer",
803
+ "686": "oil filter",
804
+ "687": "organ, pipe organ",
805
+ "688": "oscilloscope, scope, cathode-ray oscilloscope, CRO",
806
+ "689": "overskirt",
807
+ "690": "oxcart",
808
+ "691": "oxygen mask",
809
+ "692": "packet",
810
+ "693": "paddle, boat paddle",
811
+ "694": "paddlewheel, paddle wheel",
812
+ "695": "padlock",
813
+ "696": "paintbrush",
814
+ "697": "pajama, pyjama, pj's, jammies",
815
+ "698": "palace",
816
+ "699": "panpipe, pandean pipe, syrinx",
817
+ "700": "paper towel",
818
+ "701": "parachute, chute",
819
+ "702": "parallel bars, bars",
820
+ "703": "park bench",
821
+ "704": "parking meter",
822
+ "705": "passenger car, coach, carriage",
823
+ "706": "patio, terrace",
824
+ "707": "pay-phone, pay-station",
825
+ "708": "pedestal, plinth, footstall",
826
+ "709": "pencil box, pencil case",
827
+ "710": "pencil sharpener",
828
+ "711": "perfume, essence",
829
+ "712": "Petri dish",
830
+ "713": "photocopier",
831
+ "714": "pick, plectrum, plectron",
832
+ "715": "pickelhaube",
833
+ "716": "picket fence, paling",
834
+ "717": "pickup, pickup truck",
835
+ "718": "pier",
836
+ "719": "piggy bank, penny bank",
837
+ "720": "pill bottle",
838
+ "721": "pillow",
839
+ "722": "ping-pong ball",
840
+ "723": "pinwheel",
841
+ "724": "pirate, pirate ship",
842
+ "725": "pitcher, ewer",
843
+ "726": "plane, carpenter's plane, woodworking plane",
844
+ "727": "planetarium",
845
+ "728": "plastic bag",
846
+ "729": "plate rack",
847
+ "730": "plow, plough",
848
+ "731": "plunger, plumber's helper",
849
+ "732": "Polaroid camera, Polaroid Land camera",
850
+ "733": "pole",
851
+ "734": "police van, police wagon, paddy wagon, patrol wagon, wagon, black Maria",
852
+ "735": "poncho",
853
+ "736": "pool table, billiard table, snooker table",
854
+ "737": "pop bottle, soda bottle",
855
+ "738": "pot, flowerpot",
856
+ "739": "potter's wheel",
857
+ "740": "power drill",
858
+ "741": "prayer rug, prayer mat",
859
+ "742": "printer",
860
+ "743": "prison, prison house",
861
+ "744": "projectile, missile",
862
+ "745": "projector",
863
+ "746": "puck, hockey puck",
864
+ "747": "punching bag, punch bag, punching ball, punchball",
865
+ "748": "purse",
866
+ "749": "quill, quill pen",
867
+ "750": "quilt, comforter, comfort, puff",
868
+ "751": "racer, race car, racing car",
869
+ "752": "racket, racquet",
870
+ "753": "radiator",
871
+ "754": "radio, wireless",
872
+ "755": "radio telescope, radio reflector",
873
+ "756": "rain barrel",
874
+ "757": "recreational vehicle, RV, R.V.",
875
+ "758": "reel",
876
+ "759": "reflex camera",
877
+ "760": "refrigerator, icebox",
878
+ "761": "remote control, remote",
879
+ "762": "restaurant, eating house, eating place, eatery",
880
+ "763": "revolver, six-gun, six-shooter",
881
+ "764": "rifle",
882
+ "765": "rocking chair, rocker",
883
+ "766": "rotisserie",
884
+ "767": "rubber eraser, rubber, pencil eraser",
885
+ "768": "rugby ball",
886
+ "769": "rule, ruler",
887
+ "770": "running shoe",
888
+ "771": "safe",
889
+ "772": "safety pin",
890
+ "773": "saltshaker, salt shaker",
891
+ "774": "sandal",
892
+ "775": "sarong",
893
+ "776": "sax, saxophone",
894
+ "777": "scabbard",
895
+ "778": "scale, weighing machine",
896
+ "779": "school bus",
897
+ "780": "schooner",
898
+ "781": "scoreboard",
899
+ "782": "screen, CRT screen",
900
+ "783": "screw",
901
+ "784": "screwdriver",
902
+ "785": "seat belt, seatbelt",
903
+ "786": "sewing machine",
904
+ "787": "shield, buckler",
905
+ "788": "shoe shop, shoe-shop, shoe store",
906
+ "789": "shoji",
907
+ "790": "shopping basket",
908
+ "791": "shopping cart",
909
+ "792": "shovel",
910
+ "793": "shower cap",
911
+ "794": "shower curtain",
912
+ "795": "ski",
913
+ "796": "ski mask",
914
+ "797": "sleeping bag",
915
+ "798": "slide rule, slipstick",
916
+ "799": "sliding door",
917
+ "800": "slot, one-armed bandit",
918
+ "801": "snorkel",
919
+ "802": "snowmobile",
920
+ "803": "snowplow, snowplough",
921
+ "804": "soap dispenser",
922
+ "805": "soccer ball",
923
+ "806": "sock",
924
+ "807": "solar dish, solar collector, solar furnace",
925
+ "808": "sombrero",
926
+ "809": "soup bowl",
927
+ "810": "space bar",
928
+ "811": "space heater",
929
+ "812": "space shuttle",
930
+ "813": "spatula",
931
+ "814": "speedboat",
932
+ "815": "spider web, spider's web",
933
+ "816": "spindle",
934
+ "817": "sports car, sport car",
935
+ "818": "spotlight, spot",
936
+ "819": "stage",
937
+ "820": "steam locomotive",
938
+ "821": "steel arch bridge",
939
+ "822": "steel drum",
940
+ "823": "stethoscope",
941
+ "824": "stole",
942
+ "825": "stone wall",
943
+ "826": "stopwatch, stop watch",
944
+ "827": "stove",
945
+ "828": "strainer",
946
+ "829": "streetcar, tram, tramcar, trolley, trolley car",
947
+ "830": "stretcher",
948
+ "831": "studio couch, day bed",
949
+ "832": "stupa, tope",
950
+ "833": "submarine, pigboat, sub, U-boat",
951
+ "834": "suit, suit of clothes",
952
+ "835": "sundial",
953
+ "836": "sunglass",
954
+ "837": "sunglasses, dark glasses, shades",
955
+ "838": "sunscreen, sunblock, sun blocker",
956
+ "839": "suspension bridge",
957
+ "840": "swab, swob, mop",
958
+ "841": "sweatshirt",
959
+ "842": "swimming trunks, bathing trunks",
960
+ "843": "swing",
961
+ "844": "switch, electric switch, electrical switch",
962
+ "845": "syringe",
963
+ "846": "table lamp",
964
+ "847": "tank, army tank, armored combat vehicle, armoured combat vehicle",
965
+ "848": "tape player",
966
+ "849": "teapot",
967
+ "850": "teddy, teddy bear",
968
+ "851": "television, television system",
969
+ "852": "tennis ball",
970
+ "853": "thatch, thatched roof",
971
+ "854": "theater curtain, theatre curtain",
972
+ "855": "thimble",
973
+ "856": "thresher, thrasher, threshing machine",
974
+ "857": "throne",
975
+ "858": "tile roof",
976
+ "859": "toaster",
977
+ "860": "tobacco shop, tobacconist shop, tobacconist",
978
+ "861": "toilet seat",
979
+ "862": "torch",
980
+ "863": "totem pole",
981
+ "864": "tow truck, tow car, wrecker",
982
+ "865": "toyshop",
983
+ "866": "tractor",
984
+ "867": "trailer truck, tractor trailer, trucking rig, rig, articulated lorry, semi",
985
+ "868": "tray",
986
+ "869": "trench coat",
987
+ "870": "tricycle, trike, velocipede",
988
+ "871": "trimaran",
989
+ "872": "tripod",
990
+ "873": "triumphal arch",
991
+ "874": "trolleybus, trolley coach, trackless trolley",
992
+ "875": "trombone",
993
+ "876": "tub, vat",
994
+ "877": "turnstile",
995
+ "878": "typewriter keyboard",
996
+ "879": "umbrella",
997
+ "880": "unicycle, monocycle",
998
+ "881": "upright, upright piano",
999
+ "882": "vacuum, vacuum cleaner",
1000
+ "883": "vase",
1001
+ "884": "vault",
1002
+ "885": "velvet",
1003
+ "886": "vending machine",
1004
+ "887": "vestment",
1005
+ "888": "viaduct",
1006
+ "889": "violin, fiddle",
1007
+ "890": "volleyball",
1008
+ "891": "waffle iron",
1009
+ "892": "wall clock",
1010
+ "893": "wallet, billfold, notecase, pocketbook",
1011
+ "894": "wardrobe, closet, press",
1012
+ "895": "warplane, military plane",
1013
+ "896": "washbasin, handbasin, washbowl, lavabo, wash-hand basin",
1014
+ "897": "washer, automatic washer, washing machine",
1015
+ "898": "water bottle",
1016
+ "899": "water jug",
1017
+ "900": "water tower",
1018
+ "901": "whiskey jug",
1019
+ "902": "whistle",
1020
+ "903": "wig",
1021
+ "904": "window screen",
1022
+ "905": "window shade",
1023
+ "906": "Windsor tie",
1024
+ "907": "wine bottle",
1025
+ "908": "wing",
1026
+ "909": "wok",
1027
+ "910": "wooden spoon",
1028
+ "911": "wool, woolen, woollen",
1029
+ "912": "worm fence, snake fence, snake-rail fence, Virginia fence",
1030
+ "913": "wreck",
1031
+ "914": "yawl",
1032
+ "915": "yurt",
1033
+ "916": "web site, website, internet site, site",
1034
+ "917": "comic book",
1035
+ "918": "crossword puzzle, crossword",
1036
+ "919": "street sign",
1037
+ "920": "traffic light, traffic signal, stoplight",
1038
+ "921": "book jacket, dust cover, dust jacket, dust wrapper",
1039
+ "922": "menu",
1040
+ "923": "plate",
1041
+ "924": "guacamole",
1042
+ "925": "consomme",
1043
+ "926": "hot pot, hotpot",
1044
+ "927": "trifle",
1045
+ "928": "ice cream, icecream",
1046
+ "929": "ice lolly, lolly, lollipop, popsicle",
1047
+ "930": "French loaf",
1048
+ "931": "bagel, beigel",
1049
+ "932": "pretzel",
1050
+ "933": "cheeseburger",
1051
+ "934": "hotdog, hot dog, red hot",
1052
+ "935": "mashed potato",
1053
+ "936": "head cabbage",
1054
+ "937": "broccoli",
1055
+ "938": "cauliflower",
1056
+ "939": "zucchini, courgette",
1057
+ "940": "spaghetti squash",
1058
+ "941": "acorn squash",
1059
+ "942": "butternut squash",
1060
+ "943": "cucumber, cuke",
1061
+ "944": "artichoke, globe artichoke",
1062
+ "945": "bell pepper",
1063
+ "946": "cardoon",
1064
+ "947": "mushroom",
1065
+ "948": "Granny Smith",
1066
+ "949": "strawberry",
1067
+ "950": "orange",
1068
+ "951": "lemon",
1069
+ "952": "fig",
1070
+ "953": "pineapple, ananas",
1071
+ "954": "banana",
1072
+ "955": "jackfruit, jak, jack",
1073
+ "956": "custard apple",
1074
+ "957": "pomegranate",
1075
+ "958": "hay",
1076
+ "959": "carbonara",
1077
+ "960": "chocolate sauce, chocolate syrup",
1078
+ "961": "dough",
1079
+ "962": "meat loaf, meatloaf",
1080
+ "963": "pizza, pizza pie",
1081
+ "964": "potpie",
1082
+ "965": "burrito",
1083
+ "966": "red wine",
1084
+ "967": "espresso",
1085
+ "968": "cup",
1086
+ "969": "eggnog",
1087
+ "970": "alp",
1088
+ "971": "bubble",
1089
+ "972": "cliff, drop, drop-off",
1090
+ "973": "coral reef",
1091
+ "974": "geyser",
1092
+ "975": "lakeside, lakeshore",
1093
+ "976": "promontory, headland, head, foreland",
1094
+ "977": "sandbar, sand bar",
1095
+ "978": "seashore, coast, seacoast, sea-coast",
1096
+ "979": "valley, vale",
1097
+ "980": "volcano",
1098
+ "981": "ballplayer, baseball player",
1099
+ "982": "groom, bridegroom",
1100
+ "983": "scuba diver",
1101
+ "984": "rapeseed",
1102
+ "985": "daisy",
1103
+ "986": "yellow lady's slipper, yellow lady-slipper, Cypripedium calceolus, Cypripedium parviflorum",
1104
+ "987": "corn",
1105
+ "988": "acorn",
1106
+ "989": "hip, rose hip, rosehip",
1107
+ "990": "buckeye, horse chestnut, conker",
1108
+ "991": "coral fungus",
1109
+ "992": "agaric",
1110
+ "993": "gyromitra",
1111
+ "994": "stinkhorn, carrion fungus",
1112
+ "995": "earthstar",
1113
+ "996": "hen-of-the-woods, hen of the woods, Polyporus frondosus, Grifola frondosa",
1114
+ "997": "bolete",
1115
+ "998": "ear, spike, capitulum",
1116
+ "999": "toilet tissue, toilet paper, bathroom tissue"
1117
+ },
1118
+ "image_size": 384,
1119
+ "initializer_range": 0.02,
1120
+ "intermediate_size": 3072,
1121
+ "is_decoder": false,
1122
+ "is_encoder_decoder": false,
1123
+ "label2id": {
1124
+ "Afghan hound, Afghan": 160,
1125
+ "African chameleon, Chamaeleo chamaeleon": 47,
1126
+ "African crocodile, Nile crocodile, Crocodylus niloticus": 49,
1127
+ "African elephant, Loxodonta africana": 386,
1128
+ "African grey, African gray, Psittacus erithacus": 87,
1129
+ "African hunting dog, hyena dog, Cape hunting dog, Lycaon pictus": 275,
1130
+ "Airedale, Airedale terrier": 191,
1131
+ "American Staffordshire terrier, Staffordshire terrier, American pit bull terrier, pit bull terrier": 180,
1132
+ "American alligator, Alligator mississipiensis": 50,
1133
+ "American black bear, black bear, Ursus americanus, Euarctos americanus": 295,
1134
+ "American chameleon, anole, Anolis carolinensis": 40,
1135
+ "American coot, marsh hen, mud hen, water hen, Fulica americana": 137,
1136
+ "American egret, great white heron, Egretta albus": 132,
1137
+ "American lobster, Northern lobster, Maine lobster, Homarus americanus": 122,
1138
+ "Angora, Angora rabbit": 332,
1139
+ "Appenzeller": 240,
1140
+ "Arabian camel, dromedary, Camelus dromedarius": 354,
1141
+ "Arctic fox, white fox, Alopex lagopus": 279,
1142
+ "Australian terrier": 193,
1143
+ "Band Aid": 419,
1144
+ "Bedlington terrier": 181,
1145
+ "Bernese mountain dog": 239,
1146
+ "Blenheim spaniel": 156,
1147
+ "Border collie": 232,
1148
+ "Border terrier": 182,
1149
+ "Boston bull, Boston terrier": 195,
1150
+ "Bouvier des Flandres, Bouviers des Flandres": 233,
1151
+ "Brabancon griffon": 262,
1152
+ "Brittany spaniel": 215,
1153
+ "CD player": 485,
1154
+ "Cardigan, Cardigan Welsh corgi": 264,
1155
+ "Chesapeake Bay retriever": 209,
1156
+ "Chihuahua": 151,
1157
+ "Christmas stocking": 496,
1158
+ "Crock Pot": 521,
1159
+ "Dandie Dinmont, Dandie Dinmont terrier": 194,
1160
+ "Doberman, Doberman pinscher": 236,
1161
+ "Dungeness crab, Cancer magister": 118,
1162
+ "Dutch oven": 544,
1163
+ "Egyptian cat": 285,
1164
+ "English foxhound": 167,
1165
+ "English setter": 212,
1166
+ "English springer, English springer spaniel": 217,
1167
+ "EntleBucher": 241,
1168
+ "Eskimo dog, husky": 248,
1169
+ "European fire salamander, Salamandra salamandra": 25,
1170
+ "European gallinule, Porphyrio porphyrio": 136,
1171
+ "French bulldog": 245,
1172
+ "French horn, horn": 566,
1173
+ "French loaf": 930,
1174
+ "German shepherd, German shepherd dog, German police dog, alsatian": 235,
1175
+ "German short-haired pointer": 210,
1176
+ "Gila monster, Heloderma suspectum": 45,
1177
+ "Gordon setter": 214,
1178
+ "Granny Smith": 948,
1179
+ "Great Dane": 246,
1180
+ "Great Pyrenees": 257,
1181
+ "Greater Swiss Mountain dog": 238,
1182
+ "Ibizan hound, Ibizan Podenco": 173,
1183
+ "Indian cobra, Naja naja": 63,
1184
+ "Indian elephant, Elephas maximus": 385,
1185
+ "Irish setter, red setter": 213,
1186
+ "Irish terrier": 184,
1187
+ "Irish water spaniel": 221,
1188
+ "Irish wolfhound": 170,
1189
+ "Italian greyhound": 171,
1190
+ "Japanese spaniel": 152,
1191
+ "Kerry blue terrier": 183,
1192
+ "Komodo dragon, Komodo lizard, dragon lizard, giant lizard, Varanus komodoensis": 48,
1193
+ "Labrador retriever": 208,
1194
+ "Lakeland terrier": 189,
1195
+ "Leonberg": 255,
1196
+ "Lhasa, Lhasa apso": 204,
1197
+ "Loafer": 630,
1198
+ "Madagascar cat, ring-tailed lemur, Lemur catta": 383,
1199
+ "Maltese dog, Maltese terrier, Maltese": 153,
1200
+ "Mexican hairless": 268,
1201
+ "Model T": 661,
1202
+ "Newfoundland, Newfoundland dog": 256,
1203
+ "Norfolk terrier": 185,
1204
+ "Norwegian elkhound, elkhound": 174,
1205
+ "Norwich terrier": 186,
1206
+ "Old English sheepdog, bobtail": 229,
1207
+ "Pekinese, Pekingese, Peke": 154,
1208
+ "Pembroke, Pembroke Welsh corgi": 263,
1209
+ "Persian cat": 283,
1210
+ "Petri dish": 712,
1211
+ "Polaroid camera, Polaroid Land camera": 732,
1212
+ "Pomeranian": 259,
1213
+ "Rhodesian ridgeback": 159,
1214
+ "Rottweiler": 234,
1215
+ "Saint Bernard, St Bernard": 247,
1216
+ "Saluki, gazelle hound": 176,
1217
+ "Samoyed, Samoyede": 258,
1218
+ "Scotch terrier, Scottish terrier, Scottie": 199,
1219
+ "Scottish deerhound, deerhound": 177,
1220
+ "Sealyham terrier, Sealyham": 190,
1221
+ "Shetland sheepdog, Shetland sheep dog, Shetland": 230,
1222
+ "Shih-Tzu": 155,
1223
+ "Siamese cat, Siamese": 284,
1224
+ "Siberian husky": 250,
1225
+ "Staffordshire bullterrier, Staffordshire bull terrier": 179,
1226
+ "Sussex spaniel": 220,
1227
+ "Tibetan mastiff": 244,
1228
+ "Tibetan terrier, chrysanthemum dog": 200,
1229
+ "Walker hound, Walker foxhound": 166,
1230
+ "Weimaraner": 178,
1231
+ "Welsh springer spaniel": 218,
1232
+ "West Highland white terrier": 203,
1233
+ "Windsor tie": 906,
1234
+ "Yorkshire terrier": 187,
1235
+ "abacus": 398,
1236
+ "abaya": 399,
1237
+ "academic gown, academic robe, judge's robe": 400,
1238
+ "accordion, piano accordion, squeeze box": 401,
1239
+ "acorn": 988,
1240
+ "acorn squash": 941,
1241
+ "acoustic guitar": 402,
1242
+ "admiral": 321,
1243
+ "affenpinscher, monkey pinscher, monkey dog": 252,
1244
+ "agama": 42,
1245
+ "agaric": 992,
1246
+ "aircraft carrier, carrier, flattop, attack aircraft carrier": 403,
1247
+ "airliner": 404,
1248
+ "airship, dirigible": 405,
1249
+ "albatross, mollymawk": 146,
1250
+ "alligator lizard": 44,
1251
+ "alp": 970,
1252
+ "altar": 406,
1253
+ "ambulance": 407,
1254
+ "amphibian, amphibious vehicle": 408,
1255
+ "analog clock": 409,
1256
+ "anemone fish": 393,
1257
+ "ant, emmet, pismire": 310,
1258
+ "apiary, bee house": 410,
1259
+ "apron": 411,
1260
+ "armadillo": 363,
1261
+ "artichoke, globe artichoke": 944,
1262
+ "ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin": 412,
1263
+ "assault rifle, assault gun": 413,
1264
+ "axolotl, mud puppy, Ambystoma mexicanum": 29,
1265
+ "baboon": 372,
1266
+ "backpack, back pack, knapsack, packsack, rucksack, haversack": 414,
1267
+ "badger": 362,
1268
+ "bagel, beigel": 931,
1269
+ "bakery, bakeshop, bakehouse": 415,
1270
+ "balance beam, beam": 416,
1271
+ "bald eagle, American eagle, Haliaeetus leucocephalus": 22,
1272
+ "balloon": 417,
1273
+ "ballplayer, baseball player": 981,
1274
+ "ballpoint, ballpoint pen, ballpen, Biro": 418,
1275
+ "banana": 954,
1276
+ "banded gecko": 38,
1277
+ "banjo": 420,
1278
+ "bannister, banister, balustrade, balusters, handrail": 421,
1279
+ "barbell": 422,
1280
+ "barber chair": 423,
1281
+ "barbershop": 424,
1282
+ "barn": 425,
1283
+ "barn spider, Araneus cavaticus": 73,
1284
+ "barometer": 426,
1285
+ "barracouta, snoek": 389,
1286
+ "barrel, cask": 427,
1287
+ "barrow, garden cart, lawn cart, wheelbarrow": 428,
1288
+ "baseball": 429,
1289
+ "basenji": 253,
1290
+ "basketball": 430,
1291
+ "basset, basset hound": 161,
1292
+ "bassinet": 431,
1293
+ "bassoon": 432,
1294
+ "bath towel": 434,
1295
+ "bathing cap, swimming cap": 433,
1296
+ "bathtub, bathing tub, bath, tub": 435,
1297
+ "beach wagon, station wagon, wagon, estate car, beach waggon, station waggon, waggon": 436,
1298
+ "beacon, lighthouse, beacon light, pharos": 437,
1299
+ "beagle": 162,
1300
+ "beaker": 438,
1301
+ "bearskin, busby, shako": 439,
1302
+ "beaver": 337,
1303
+ "bee": 309,
1304
+ "bee eater": 92,
1305
+ "beer bottle": 440,
1306
+ "beer glass": 441,
1307
+ "bell cote, bell cot": 442,
1308
+ "bell pepper": 945,
1309
+ "bib": 443,
1310
+ "bicycle-built-for-two, tandem bicycle, tandem": 444,
1311
+ "bighorn, bighorn sheep, cimarron, Rocky Mountain bighorn, Rocky Mountain sheep, Ovis canadensis": 349,
1312
+ "bikini, two-piece": 445,
1313
+ "binder, ring-binder": 446,
1314
+ "binoculars, field glasses, opera glasses": 447,
1315
+ "birdhouse": 448,
1316
+ "bison": 347,
1317
+ "bittern": 133,
1318
+ "black and gold garden spider, Argiope aurantia": 72,
1319
+ "black grouse": 80,
1320
+ "black stork, Ciconia nigra": 128,
1321
+ "black swan, Cygnus atratus": 100,
1322
+ "black widow, Latrodectus mactans": 75,
1323
+ "black-and-tan coonhound": 165,
1324
+ "black-footed ferret, ferret, Mustela nigripes": 359,
1325
+ "bloodhound, sleuthhound": 163,
1326
+ "bluetick": 164,
1327
+ "boa constrictor, Constrictor constrictor": 61,
1328
+ "boathouse": 449,
1329
+ "bobsled, bobsleigh, bob": 450,
1330
+ "bolete": 997,
1331
+ "bolo tie, bolo, bola tie, bola": 451,
1332
+ "bonnet, poke bonnet": 452,
1333
+ "book jacket, dust cover, dust jacket, dust wrapper": 921,
1334
+ "bookcase": 453,
1335
+ "bookshop, bookstore, bookstall": 454,
1336
+ "borzoi, Russian wolfhound": 169,
1337
+ "bottlecap": 455,
1338
+ "bow": 456,
1339
+ "bow tie, bow-tie, bowtie": 457,
1340
+ "box turtle, box tortoise": 37,
1341
+ "boxer": 242,
1342
+ "brain coral": 109,
1343
+ "brambling, Fringilla montifringilla": 10,
1344
+ "brass, memorial tablet, plaque": 458,
1345
+ "brassiere, bra, bandeau": 459,
1346
+ "breakwater, groin, groyne, mole, bulwark, seawall, jetty": 460,
1347
+ "breastplate, aegis, egis": 461,
1348
+ "briard": 226,
1349
+ "broccoli": 937,
1350
+ "broom": 462,
1351
+ "brown bear, bruin, Ursus arctos": 294,
1352
+ "bubble": 971,
1353
+ "bucket, pail": 463,
1354
+ "buckeye, horse chestnut, conker": 990,
1355
+ "buckle": 464,
1356
+ "bulbul": 16,
1357
+ "bull mastiff": 243,
1358
+ "bullet train, bullet": 466,
1359
+ "bulletproof vest": 465,
1360
+ "bullfrog, Rana catesbeiana": 30,
1361
+ "burrito": 965,
1362
+ "bustard": 138,
1363
+ "butcher shop, meat market": 467,
1364
+ "butternut squash": 942,
1365
+ "cab, hack, taxi, taxicab": 468,
1366
+ "cabbage butterfly": 324,
1367
+ "cairn, cairn terrier": 192,
1368
+ "caldron, cauldron": 469,
1369
+ "can opener, tin opener": 473,
1370
+ "candle, taper, wax light": 470,
1371
+ "cannon": 471,
1372
+ "canoe": 472,
1373
+ "capuchin, ringtail, Cebus capucinus": 378,
1374
+ "car mirror": 475,
1375
+ "car wheel": 479,
1376
+ "carbonara": 959,
1377
+ "cardigan": 474,
1378
+ "cardoon": 946,
1379
+ "carousel, carrousel, merry-go-round, roundabout, whirligig": 476,
1380
+ "carpenter's kit, tool kit": 477,
1381
+ "carton": 478,
1382
+ "cash machine, cash dispenser, automated teller machine, automatic teller machine, automated teller, automatic teller, ATM": 480,
1383
+ "cassette": 481,
1384
+ "cassette player": 482,
1385
+ "castle": 483,
1386
+ "catamaran": 484,
1387
+ "cauliflower": 938,
1388
+ "cello, violoncello": 486,
1389
+ "cellular telephone, cellular phone, cellphone, cell, mobile phone": 487,
1390
+ "centipede": 79,
1391
+ "chain": 488,
1392
+ "chain mail, ring mail, mail, chain armor, chain armour, ring armor, ring armour": 490,
1393
+ "chain saw, chainsaw": 491,
1394
+ "chainlink fence": 489,
1395
+ "chambered nautilus, pearly nautilus, nautilus": 117,
1396
+ "cheeseburger": 933,
1397
+ "cheetah, chetah, Acinonyx jubatus": 293,
1398
+ "chest": 492,
1399
+ "chickadee": 19,
1400
+ "chiffonier, commode": 493,
1401
+ "chime, bell, gong": 494,
1402
+ "chimpanzee, chimp, Pan troglodytes": 367,
1403
+ "china cabinet, china closet": 495,
1404
+ "chiton, coat-of-mail shell, sea cradle, polyplacophore": 116,
1405
+ "chocolate sauce, chocolate syrup": 960,
1406
+ "chow, chow chow": 260,
1407
+ "church, church building": 497,
1408
+ "cicada, cicala": 316,
1409
+ "cinema, movie theater, movie theatre, movie house, picture palace": 498,
1410
+ "cleaver, meat cleaver, chopper": 499,
1411
+ "cliff dwelling": 500,
1412
+ "cliff, drop, drop-off": 972,
1413
+ "cloak": 501,
1414
+ "clog, geta, patten, sabot": 502,
1415
+ "clumber, clumber spaniel": 216,
1416
+ "cock": 7,
1417
+ "cocker spaniel, English cocker spaniel, cocker": 219,
1418
+ "cockroach, roach": 314,
1419
+ "cocktail shaker": 503,
1420
+ "coffee mug": 504,
1421
+ "coffeepot": 505,
1422
+ "coho, cohoe, coho salmon, blue jack, silver salmon, Oncorhynchus kisutch": 391,
1423
+ "coil, spiral, volute, whorl, helix": 506,
1424
+ "collie": 231,
1425
+ "colobus, colobus monkey": 375,
1426
+ "combination lock": 507,
1427
+ "comic book": 917,
1428
+ "common iguana, iguana, Iguana iguana": 39,
1429
+ "common newt, Triturus vulgaris": 26,
1430
+ "computer keyboard, keypad": 508,
1431
+ "conch": 112,
1432
+ "confectionery, confectionary, candy store": 509,
1433
+ "consomme": 925,
1434
+ "container ship, containership, container vessel": 510,
1435
+ "convertible": 511,
1436
+ "coral fungus": 991,
1437
+ "coral reef": 973,
1438
+ "corkscrew, bottle screw": 512,
1439
+ "corn": 987,
1440
+ "cornet, horn, trumpet, trump": 513,
1441
+ "coucal": 91,
1442
+ "cougar, puma, catamount, mountain lion, painter, panther, Felis concolor": 286,
1443
+ "cowboy boot": 514,
1444
+ "cowboy hat, ten-gallon hat": 515,
1445
+ "coyote, prairie wolf, brush wolf, Canis latrans": 272,
1446
+ "cradle": 516,
1447
+ "crane": 517,
1448
+ "crash helmet": 518,
1449
+ "crate": 519,
1450
+ "crayfish, crawfish, crawdad, crawdaddy": 124,
1451
+ "crib, cot": 520,
1452
+ "cricket": 312,
1453
+ "croquet ball": 522,
1454
+ "crossword puzzle, crossword": 918,
1455
+ "crutch": 523,
1456
+ "cucumber, cuke": 943,
1457
+ "cuirass": 524,
1458
+ "cup": 968,
1459
+ "curly-coated retriever": 206,
1460
+ "custard apple": 956,
1461
+ "daisy": 985,
1462
+ "dalmatian, coach dog, carriage dog": 251,
1463
+ "dam, dike, dyke": 525,
1464
+ "damselfly": 320,
1465
+ "desk": 526,
1466
+ "desktop computer": 527,
1467
+ "dhole, Cuon alpinus": 274,
1468
+ "dial telephone, dial phone": 528,
1469
+ "diamondback, diamondback rattlesnake, Crotalus adamanteus": 67,
1470
+ "diaper, nappy, napkin": 529,
1471
+ "digital clock": 530,
1472
+ "digital watch": 531,
1473
+ "dingo, warrigal, warragal, Canis dingo": 273,
1474
+ "dining table, board": 532,
1475
+ "dishrag, dishcloth": 533,
1476
+ "dishwasher, dish washer, dishwashing machine": 534,
1477
+ "disk brake, disc brake": 535,
1478
+ "dock, dockage, docking facility": 536,
1479
+ "dogsled, dog sled, dog sleigh": 537,
1480
+ "dome": 538,
1481
+ "doormat, welcome mat": 539,
1482
+ "dough": 961,
1483
+ "dowitcher": 142,
1484
+ "dragonfly, darning needle, devil's darning needle, sewing needle, snake feeder, snake doctor, mosquito hawk, skeeter hawk": 319,
1485
+ "drake": 97,
1486
+ "drilling platform, offshore rig": 540,
1487
+ "drum, membranophone, tympan": 541,
1488
+ "drumstick": 542,
1489
+ "dugong, Dugong dugon": 149,
1490
+ "dumbbell": 543,
1491
+ "dung beetle": 305,
1492
+ "ear, spike, capitulum": 998,
1493
+ "earthstar": 995,
1494
+ "echidna, spiny anteater, anteater": 102,
1495
+ "eel": 390,
1496
+ "eft": 27,
1497
+ "eggnog": 969,
1498
+ "electric fan, blower": 545,
1499
+ "electric guitar": 546,
1500
+ "electric locomotive": 547,
1501
+ "electric ray, crampfish, numbfish, torpedo": 5,
1502
+ "entertainment center": 548,
1503
+ "envelope": 549,
1504
+ "espresso": 967,
1505
+ "espresso maker": 550,
1506
+ "face powder": 551,
1507
+ "feather boa, boa": 552,
1508
+ "fiddler crab": 120,
1509
+ "fig": 952,
1510
+ "file, file cabinet, filing cabinet": 553,
1511
+ "fire engine, fire truck": 555,
1512
+ "fire screen, fireguard": 556,
1513
+ "fireboat": 554,
1514
+ "flagpole, flagstaff": 557,
1515
+ "flamingo": 130,
1516
+ "flat-coated retriever": 205,
1517
+ "flatworm, platyhelminth": 110,
1518
+ "flute, transverse flute": 558,
1519
+ "fly": 308,
1520
+ "folding chair": 559,
1521
+ "football helmet": 560,
1522
+ "forklift": 561,
1523
+ "fountain": 562,
1524
+ "fountain pen": 563,
1525
+ "four-poster": 564,
1526
+ "fox squirrel, eastern fox squirrel, Sciurus niger": 335,
1527
+ "freight car": 565,
1528
+ "frilled lizard, Chlamydosaurus kingi": 43,
1529
+ "frying pan, frypan, skillet": 567,
1530
+ "fur coat": 568,
1531
+ "gar, garfish, garpike, billfish, Lepisosteus osseus": 395,
1532
+ "garbage truck, dustcart": 569,
1533
+ "garden spider, Aranea diademata": 74,
1534
+ "garter snake, grass snake": 57,
1535
+ "gas pump, gasoline pump, petrol pump, island dispenser": 571,
1536
+ "gasmask, respirator, gas helmet": 570,
1537
+ "gazelle": 353,
1538
+ "geyser": 974,
1539
+ "giant panda, panda, panda bear, coon bear, Ailuropoda melanoleuca": 388,
1540
+ "giant schnauzer": 197,
1541
+ "gibbon, Hylobates lar": 368,
1542
+ "go-kart": 573,
1543
+ "goblet": 572,
1544
+ "golden retriever": 207,
1545
+ "goldfinch, Carduelis carduelis": 11,
1546
+ "goldfish, Carassius auratus": 1,
1547
+ "golf ball": 574,
1548
+ "golfcart, golf cart": 575,
1549
+ "gondola": 576,
1550
+ "gong, tam-tam": 577,
1551
+ "goose": 99,
1552
+ "gorilla, Gorilla gorilla": 366,
1553
+ "gown": 578,
1554
+ "grand piano, grand": 579,
1555
+ "grasshopper, hopper": 311,
1556
+ "great grey owl, great gray owl, Strix nebulosa": 24,
1557
+ "great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias": 2,
1558
+ "green lizard, Lacerta viridis": 46,
1559
+ "green mamba": 64,
1560
+ "green snake, grass snake": 55,
1561
+ "greenhouse, nursery, glasshouse": 580,
1562
+ "grey fox, gray fox, Urocyon cinereoargenteus": 280,
1563
+ "grey whale, gray whale, devilfish, Eschrichtius gibbosus, Eschrichtius robustus": 147,
1564
+ "grille, radiator grille": 581,
1565
+ "grocery store, grocery, food market, market": 582,
1566
+ "groenendael": 224,
1567
+ "groom, bridegroom": 982,
1568
+ "ground beetle, carabid beetle": 302,
1569
+ "guacamole": 924,
1570
+ "guenon, guenon monkey": 370,
1571
+ "guillotine": 583,
1572
+ "guinea pig, Cavia cobaya": 338,
1573
+ "gyromitra": 993,
1574
+ "hair slide": 584,
1575
+ "hair spray": 585,
1576
+ "half track": 586,
1577
+ "hammer": 587,
1578
+ "hammerhead, hammerhead shark": 4,
1579
+ "hamper": 588,
1580
+ "hamster": 333,
1581
+ "hand blower, blow dryer, blow drier, hair dryer, hair drier": 589,
1582
+ "hand-held computer, hand-held microcomputer": 590,
1583
+ "handkerchief, hankie, hanky, hankey": 591,
1584
+ "hard disc, hard disk, fixed disk": 592,
1585
+ "hare": 331,
1586
+ "harmonica, mouth organ, harp, mouth harp": 593,
1587
+ "harp": 594,
1588
+ "hartebeest": 351,
1589
+ "harvester, reaper": 595,
1590
+ "harvestman, daddy longlegs, Phalangium opilio": 70,
1591
+ "hatchet": 596,
1592
+ "hay": 958,
1593
+ "head cabbage": 936,
1594
+ "hen": 8,
1595
+ "hen-of-the-woods, hen of the woods, Polyporus frondosus, Grifola frondosa": 996,
1596
+ "hermit crab": 125,
1597
+ "hip, rose hip, rosehip": 989,
1598
+ "hippopotamus, hippo, river horse, Hippopotamus amphibius": 344,
1599
+ "hog, pig, grunter, squealer, Sus scrofa": 341,
1600
+ "hognose snake, puff adder, sand viper": 54,
1601
+ "holster": 597,
1602
+ "home theater, home theatre": 598,
1603
+ "honeycomb": 599,
1604
+ "hook, claw": 600,
1605
+ "hoopskirt, crinoline": 601,
1606
+ "horizontal bar, high bar": 602,
1607
+ "hornbill": 93,
1608
+ "horned viper, cerastes, sand viper, horned asp, Cerastes cornutus": 66,
1609
+ "horse cart, horse-cart": 603,
1610
+ "hot pot, hotpot": 926,
1611
+ "hotdog, hot dog, red hot": 934,
1612
+ "hourglass": 604,
1613
+ "house finch, linnet, Carpodacus mexicanus": 12,
1614
+ "howler monkey, howler": 379,
1615
+ "hummingbird": 94,
1616
+ "hyena, hyaena": 276,
1617
+ "iPod": 605,
1618
+ "ibex, Capra ibex": 350,
1619
+ "ice bear, polar bear, Ursus Maritimus, Thalarctos maritimus": 296,
1620
+ "ice cream, icecream": 928,
1621
+ "ice lolly, lolly, lollipop, popsicle": 929,
1622
+ "impala, Aepyceros melampus": 352,
1623
+ "indigo bunting, indigo finch, indigo bird, Passerina cyanea": 14,
1624
+ "indri, indris, Indri indri, Indri brevicaudatus": 384,
1625
+ "iron, smoothing iron": 606,
1626
+ "isopod": 126,
1627
+ "jacamar": 95,
1628
+ "jack-o'-lantern": 607,
1629
+ "jackfruit, jak, jack": 955,
1630
+ "jaguar, panther, Panthera onca, Felis onca": 290,
1631
+ "jay": 17,
1632
+ "jean, blue jean, denim": 608,
1633
+ "jeep, landrover": 609,
1634
+ "jellyfish": 107,
1635
+ "jersey, T-shirt, tee shirt": 610,
1636
+ "jigsaw puzzle": 611,
1637
+ "jinrikisha, ricksha, rickshaw": 612,
1638
+ "joystick": 613,
1639
+ "junco, snowbird": 13,
1640
+ "keeshond": 261,
1641
+ "kelpie": 227,
1642
+ "killer whale, killer, orca, grampus, sea wolf, Orcinus orca": 148,
1643
+ "kimono": 614,
1644
+ "king crab, Alaska crab, Alaskan king crab, Alaska king crab, Paralithodes camtschatica": 121,
1645
+ "king penguin, Aptenodytes patagonica": 145,
1646
+ "king snake, kingsnake": 56,
1647
+ "kit fox, Vulpes macrotis": 278,
1648
+ "kite": 21,
1649
+ "knee pad": 615,
1650
+ "knot": 616,
1651
+ "koala, koala bear, kangaroo bear, native bear, Phascolarctos cinereus": 105,
1652
+ "komondor": 228,
1653
+ "kuvasz": 222,
1654
+ "lab coat, laboratory coat": 617,
1655
+ "lacewing, lacewing fly": 318,
1656
+ "ladle": 618,
1657
+ "ladybug, ladybeetle, lady beetle, ladybird, ladybird beetle": 301,
1658
+ "lakeside, lakeshore": 975,
1659
+ "lampshade, lamp shade": 619,
1660
+ "langur": 374,
1661
+ "laptop, laptop computer": 620,
1662
+ "lawn mower, mower": 621,
1663
+ "leaf beetle, chrysomelid": 304,
1664
+ "leafhopper": 317,
1665
+ "leatherback turtle, leatherback, leathery turtle, Dermochelys coriacea": 34,
1666
+ "lemon": 951,
1667
+ "lens cap, lens cover": 622,
1668
+ "leopard, Panthera pardus": 288,
1669
+ "lesser panda, red panda, panda, bear cat, cat bear, Ailurus fulgens": 387,
1670
+ "letter opener, paper knife, paperknife": 623,
1671
+ "library": 624,
1672
+ "lifeboat": 625,
1673
+ "lighter, light, igniter, ignitor": 626,
1674
+ "limousine, limo": 627,
1675
+ "limpkin, Aramus pictus": 135,
1676
+ "liner, ocean liner": 628,
1677
+ "lion, king of beasts, Panthera leo": 291,
1678
+ "lionfish": 396,
1679
+ "lipstick, lip rouge": 629,
1680
+ "little blue heron, Egretta caerulea": 131,
1681
+ "llama": 355,
1682
+ "loggerhead, loggerhead turtle, Caretta caretta": 33,
1683
+ "long-horned beetle, longicorn, longicorn beetle": 303,
1684
+ "lorikeet": 90,
1685
+ "lotion": 631,
1686
+ "loudspeaker, speaker, speaker unit, loudspeaker system, speaker system": 632,
1687
+ "loupe, jeweler's loupe": 633,
1688
+ "lumbermill, sawmill": 634,
1689
+ "lycaenid, lycaenid butterfly": 326,
1690
+ "lynx, catamount": 287,
1691
+ "macaque": 373,
1692
+ "macaw": 88,
1693
+ "magnetic compass": 635,
1694
+ "magpie": 18,
1695
+ "mailbag, postbag": 636,
1696
+ "mailbox, letter box": 637,
1697
+ "maillot": 638,
1698
+ "maillot, tank suit": 639,
1699
+ "malamute, malemute, Alaskan malamute": 249,
1700
+ "malinois": 225,
1701
+ "manhole cover": 640,
1702
+ "mantis, mantid": 315,
1703
+ "maraca": 641,
1704
+ "marimba, xylophone": 642,
1705
+ "marmoset": 377,
1706
+ "marmot": 336,
1707
+ "mashed potato": 935,
1708
+ "mask": 643,
1709
+ "matchstick": 644,
1710
+ "maypole": 645,
1711
+ "maze, labyrinth": 646,
1712
+ "measuring cup": 647,
1713
+ "meat loaf, meatloaf": 962,
1714
+ "medicine chest, medicine cabinet": 648,
1715
+ "meerkat, mierkat": 299,
1716
+ "megalith, megalithic structure": 649,
1717
+ "menu": 922,
1718
+ "microphone, mike": 650,
1719
+ "microwave, microwave oven": 651,
1720
+ "military uniform": 652,
1721
+ "milk can": 653,
1722
+ "miniature pinscher": 237,
1723
+ "miniature poodle": 266,
1724
+ "miniature schnauzer": 196,
1725
+ "minibus": 654,
1726
+ "miniskirt, mini": 655,
1727
+ "minivan": 656,
1728
+ "mink": 357,
1729
+ "missile": 657,
1730
+ "mitten": 658,
1731
+ "mixing bowl": 659,
1732
+ "mobile home, manufactured home": 660,
1733
+ "modem": 662,
1734
+ "monarch, monarch butterfly, milkweed butterfly, Danaus plexippus": 323,
1735
+ "monastery": 663,
1736
+ "mongoose": 298,
1737
+ "monitor": 664,
1738
+ "moped": 665,
1739
+ "mortar": 666,
1740
+ "mortarboard": 667,
1741
+ "mosque": 668,
1742
+ "mosquito net": 669,
1743
+ "motor scooter, scooter": 670,
1744
+ "mountain bike, all-terrain bike, off-roader": 671,
1745
+ "mountain tent": 672,
1746
+ "mouse, computer mouse": 673,
1747
+ "mousetrap": 674,
1748
+ "moving van": 675,
1749
+ "mud turtle": 35,
1750
+ "mushroom": 947,
1751
+ "muzzle": 676,
1752
+ "nail": 677,
1753
+ "neck brace": 678,
1754
+ "necklace": 679,
1755
+ "nematode, nematode worm, roundworm": 111,
1756
+ "night snake, Hypsiglena torquata": 60,
1757
+ "nipple": 680,
1758
+ "notebook, notebook computer": 681,
1759
+ "obelisk": 682,
1760
+ "oboe, hautboy, hautbois": 683,
1761
+ "ocarina, sweet potato": 684,
1762
+ "odometer, hodometer, mileometer, milometer": 685,
1763
+ "oil filter": 686,
1764
+ "orange": 950,
1765
+ "orangutan, orang, orangutang, Pongo pygmaeus": 365,
1766
+ "organ, pipe organ": 687,
1767
+ "oscilloscope, scope, cathode-ray oscilloscope, CRO": 688,
1768
+ "ostrich, Struthio camelus": 9,
1769
+ "otter": 360,
1770
+ "otterhound, otter hound": 175,
1771
+ "overskirt": 689,
1772
+ "ox": 345,
1773
+ "oxcart": 690,
1774
+ "oxygen mask": 691,
1775
+ "oystercatcher, oyster catcher": 143,
1776
+ "packet": 692,
1777
+ "paddle, boat paddle": 693,
1778
+ "paddlewheel, paddle wheel": 694,
1779
+ "padlock": 695,
1780
+ "paintbrush": 696,
1781
+ "pajama, pyjama, pj's, jammies": 697,
1782
+ "palace": 698,
1783
+ "panpipe, pandean pipe, syrinx": 699,
1784
+ "paper towel": 700,
1785
+ "papillon": 157,
1786
+ "parachute, chute": 701,
1787
+ "parallel bars, bars": 702,
1788
+ "park bench": 703,
1789
+ "parking meter": 704,
1790
+ "partridge": 86,
1791
+ "passenger car, coach, carriage": 705,
1792
+ "patas, hussar monkey, Erythrocebus patas": 371,
1793
+ "patio, terrace": 706,
1794
+ "pay-phone, pay-station": 707,
1795
+ "peacock": 84,
1796
+ "pedestal, plinth, footstall": 708,
1797
+ "pelican": 144,
1798
+ "pencil box, pencil case": 709,
1799
+ "pencil sharpener": 710,
1800
+ "perfume, essence": 711,
1801
+ "photocopier": 713,
1802
+ "pick, plectrum, plectron": 714,
1803
+ "pickelhaube": 715,
1804
+ "picket fence, paling": 716,
1805
+ "pickup, pickup truck": 717,
1806
+ "pier": 718,
1807
+ "piggy bank, penny bank": 719,
1808
+ "pill bottle": 720,
1809
+ "pillow": 721,
1810
+ "pineapple, ananas": 953,
1811
+ "ping-pong ball": 722,
1812
+ "pinwheel": 723,
1813
+ "pirate, pirate ship": 724,
1814
+ "pitcher, ewer": 725,
1815
+ "pizza, pizza pie": 963,
1816
+ "plane, carpenter's plane, woodworking plane": 726,
1817
+ "planetarium": 727,
1818
+ "plastic bag": 728,
1819
+ "plate": 923,
1820
+ "plate rack": 729,
1821
+ "platypus, duckbill, duckbilled platypus, duck-billed platypus, Ornithorhynchus anatinus": 103,
1822
+ "plow, plough": 730,
1823
+ "plunger, plumber's helper": 731,
1824
+ "pole": 733,
1825
+ "polecat, fitch, foulmart, foumart, Mustela putorius": 358,
1826
+ "police van, police wagon, paddy wagon, patrol wagon, wagon, black Maria": 734,
1827
+ "pomegranate": 957,
1828
+ "poncho": 735,
1829
+ "pool table, billiard table, snooker table": 736,
1830
+ "pop bottle, soda bottle": 737,
1831
+ "porcupine, hedgehog": 334,
1832
+ "pot, flowerpot": 738,
1833
+ "potpie": 964,
1834
+ "potter's wheel": 739,
1835
+ "power drill": 740,
1836
+ "prairie chicken, prairie grouse, prairie fowl": 83,
1837
+ "prayer rug, prayer mat": 741,
1838
+ "pretzel": 932,
1839
+ "printer": 742,
1840
+ "prison, prison house": 743,
1841
+ "proboscis monkey, Nasalis larvatus": 376,
1842
+ "projectile, missile": 744,
1843
+ "projector": 745,
1844
+ "promontory, headland, head, foreland": 976,
1845
+ "ptarmigan": 81,
1846
+ "puck, hockey puck": 746,
1847
+ "puffer, pufferfish, blowfish, globefish": 397,
1848
+ "pug, pug-dog": 254,
1849
+ "punching bag, punch bag, punching ball, punchball": 747,
1850
+ "purse": 748,
1851
+ "quail": 85,
1852
+ "quill, quill pen": 749,
1853
+ "quilt, comforter, comfort, puff": 750,
1854
+ "racer, race car, racing car": 751,
1855
+ "racket, racquet": 752,
1856
+ "radiator": 753,
1857
+ "radio telescope, radio reflector": 755,
1858
+ "radio, wireless": 754,
1859
+ "rain barrel": 756,
1860
+ "ram, tup": 348,
1861
+ "rapeseed": 984,
1862
+ "recreational vehicle, RV, R.V.": 757,
1863
+ "red fox, Vulpes vulpes": 277,
1864
+ "red wine": 966,
1865
+ "red wolf, maned wolf, Canis rufus, Canis niger": 271,
1866
+ "red-backed sandpiper, dunlin, Erolia alpina": 140,
1867
+ "red-breasted merganser, Mergus serrator": 98,
1868
+ "redbone": 168,
1869
+ "redshank, Tringa totanus": 141,
1870
+ "reel": 758,
1871
+ "reflex camera": 759,
1872
+ "refrigerator, icebox": 760,
1873
+ "remote control, remote": 761,
1874
+ "restaurant, eating house, eating place, eatery": 762,
1875
+ "revolver, six-gun, six-shooter": 763,
1876
+ "rhinoceros beetle": 306,
1877
+ "rifle": 764,
1878
+ "ringlet, ringlet butterfly": 322,
1879
+ "ringneck snake, ring-necked snake, ring snake": 53,
1880
+ "robin, American robin, Turdus migratorius": 15,
1881
+ "rock beauty, Holocanthus tricolor": 392,
1882
+ "rock crab, Cancer irroratus": 119,
1883
+ "rock python, rock snake, Python sebae": 62,
1884
+ "rocking chair, rocker": 765,
1885
+ "rotisserie": 766,
1886
+ "rubber eraser, rubber, pencil eraser": 767,
1887
+ "ruddy turnstone, Arenaria interpres": 139,
1888
+ "ruffed grouse, partridge, Bonasa umbellus": 82,
1889
+ "rugby ball": 768,
1890
+ "rule, ruler": 769,
1891
+ "running shoe": 770,
1892
+ "safe": 771,
1893
+ "safety pin": 772,
1894
+ "saltshaker, salt shaker": 773,
1895
+ "sandal": 774,
1896
+ "sandbar, sand bar": 977,
1897
+ "sarong": 775,
1898
+ "sax, saxophone": 776,
1899
+ "scabbard": 777,
1900
+ "scale, weighing machine": 778,
1901
+ "schipperke": 223,
1902
+ "school bus": 779,
1903
+ "schooner": 780,
1904
+ "scoreboard": 781,
1905
+ "scorpion": 71,
1906
+ "screen, CRT screen": 782,
1907
+ "screw": 783,
1908
+ "screwdriver": 784,
1909
+ "scuba diver": 983,
1910
+ "sea anemone, anemone": 108,
1911
+ "sea cucumber, holothurian": 329,
1912
+ "sea lion": 150,
1913
+ "sea slug, nudibranch": 115,
1914
+ "sea snake": 65,
1915
+ "sea urchin": 328,
1916
+ "seashore, coast, seacoast, sea-coast": 978,
1917
+ "seat belt, seatbelt": 785,
1918
+ "sewing machine": 786,
1919
+ "shield, buckler": 787,
1920
+ "shoe shop, shoe-shop, shoe store": 788,
1921
+ "shoji": 789,
1922
+ "shopping basket": 790,
1923
+ "shopping cart": 791,
1924
+ "shovel": 792,
1925
+ "shower cap": 793,
1926
+ "shower curtain": 794,
1927
+ "siamang, Hylobates syndactylus, Symphalangus syndactylus": 369,
1928
+ "sidewinder, horned rattlesnake, Crotalus cerastes": 68,
1929
+ "silky terrier, Sydney silky": 201,
1930
+ "ski": 795,
1931
+ "ski mask": 796,
1932
+ "skunk, polecat, wood pussy": 361,
1933
+ "sleeping bag": 797,
1934
+ "slide rule, slipstick": 798,
1935
+ "sliding door": 799,
1936
+ "slot, one-armed bandit": 800,
1937
+ "sloth bear, Melursus ursinus, Ursus ursinus": 297,
1938
+ "slug": 114,
1939
+ "snail": 113,
1940
+ "snorkel": 801,
1941
+ "snow leopard, ounce, Panthera uncia": 289,
1942
+ "snowmobile": 802,
1943
+ "snowplow, snowplough": 803,
1944
+ "soap dispenser": 804,
1945
+ "soccer ball": 805,
1946
+ "sock": 806,
1947
+ "soft-coated wheaten terrier": 202,
1948
+ "solar dish, solar collector, solar furnace": 807,
1949
+ "sombrero": 808,
1950
+ "sorrel": 339,
1951
+ "soup bowl": 809,
1952
+ "space bar": 810,
1953
+ "space heater": 811,
1954
+ "space shuttle": 812,
1955
+ "spaghetti squash": 940,
1956
+ "spatula": 813,
1957
+ "speedboat": 814,
1958
+ "spider monkey, Ateles geoffroyi": 381,
1959
+ "spider web, spider's web": 815,
1960
+ "spindle": 816,
1961
+ "spiny lobster, langouste, rock lobster, crawfish, crayfish, sea crawfish": 123,
1962
+ "spoonbill": 129,
1963
+ "sports car, sport car": 817,
1964
+ "spotlight, spot": 818,
1965
+ "spotted salamander, Ambystoma maculatum": 28,
1966
+ "squirrel monkey, Saimiri sciureus": 382,
1967
+ "stage": 819,
1968
+ "standard poodle": 267,
1969
+ "standard schnauzer": 198,
1970
+ "starfish, sea star": 327,
1971
+ "steam locomotive": 820,
1972
+ "steel arch bridge": 821,
1973
+ "steel drum": 822,
1974
+ "stethoscope": 823,
1975
+ "stingray": 6,
1976
+ "stinkhorn, carrion fungus": 994,
1977
+ "stole": 824,
1978
+ "stone wall": 825,
1979
+ "stopwatch, stop watch": 826,
1980
+ "stove": 827,
1981
+ "strainer": 828,
1982
+ "strawberry": 949,
1983
+ "street sign": 919,
1984
+ "streetcar, tram, tramcar, trolley, trolley car": 829,
1985
+ "stretcher": 830,
1986
+ "studio couch, day bed": 831,
1987
+ "stupa, tope": 832,
1988
+ "sturgeon": 394,
1989
+ "submarine, pigboat, sub, U-boat": 833,
1990
+ "suit, suit of clothes": 834,
1991
+ "sulphur butterfly, sulfur butterfly": 325,
1992
+ "sulphur-crested cockatoo, Kakatoe galerita, Cacatua galerita": 89,
1993
+ "sundial": 835,
1994
+ "sunglass": 836,
1995
+ "sunglasses, dark glasses, shades": 837,
1996
+ "sunscreen, sunblock, sun blocker": 838,
1997
+ "suspension bridge": 839,
1998
+ "swab, swob, mop": 840,
1999
+ "sweatshirt": 841,
2000
+ "swimming trunks, bathing trunks": 842,
2001
+ "swing": 843,
2002
+ "switch, electric switch, electrical switch": 844,
2003
+ "syringe": 845,
2004
+ "tabby, tabby cat": 281,
2005
+ "table lamp": 846,
2006
+ "tailed frog, bell toad, ribbed toad, tailed toad, Ascaphus trui": 32,
2007
+ "tank, army tank, armored combat vehicle, armoured combat vehicle": 847,
2008
+ "tape player": 848,
2009
+ "tarantula": 76,
2010
+ "teapot": 849,
2011
+ "teddy, teddy bear": 850,
2012
+ "television, television system": 851,
2013
+ "tench, Tinca tinca": 0,
2014
+ "tennis ball": 852,
2015
+ "terrapin": 36,
2016
+ "thatch, thatched roof": 853,
2017
+ "theater curtain, theatre curtain": 854,
2018
+ "thimble": 855,
2019
+ "three-toed sloth, ai, Bradypus tridactylus": 364,
2020
+ "thresher, thrasher, threshing machine": 856,
2021
+ "throne": 857,
2022
+ "thunder snake, worm snake, Carphophis amoenus": 52,
2023
+ "tick": 78,
2024
+ "tiger beetle": 300,
2025
+ "tiger cat": 282,
2026
+ "tiger shark, Galeocerdo cuvieri": 3,
2027
+ "tiger, Panthera tigris": 292,
2028
+ "tile roof": 858,
2029
+ "timber wolf, grey wolf, gray wolf, Canis lupus": 269,
2030
+ "titi, titi monkey": 380,
2031
+ "toaster": 859,
2032
+ "tobacco shop, tobacconist shop, tobacconist": 860,
2033
+ "toilet seat": 861,
2034
+ "toilet tissue, toilet paper, bathroom tissue": 999,
2035
+ "torch": 862,
2036
+ "totem pole": 863,
2037
+ "toucan": 96,
2038
+ "tow truck, tow car, wrecker": 864,
2039
+ "toy poodle": 265,
2040
+ "toy terrier": 158,
2041
+ "toyshop": 865,
2042
+ "tractor": 866,
2043
+ "traffic light, traffic signal, stoplight": 920,
2044
+ "trailer truck, tractor trailer, trucking rig, rig, articulated lorry, semi": 867,
2045
+ "tray": 868,
2046
+ "tree frog, tree-frog": 31,
2047
+ "trench coat": 869,
2048
+ "triceratops": 51,
2049
+ "tricycle, trike, velocipede": 870,
2050
+ "trifle": 927,
2051
+ "trilobite": 69,
2052
+ "trimaran": 871,
2053
+ "tripod": 872,
2054
+ "triumphal arch": 873,
2055
+ "trolleybus, trolley coach, trackless trolley": 874,
2056
+ "trombone": 875,
2057
+ "tub, vat": 876,
2058
+ "turnstile": 877,
2059
+ "tusker": 101,
2060
+ "typewriter keyboard": 878,
2061
+ "umbrella": 879,
2062
+ "unicycle, monocycle": 880,
2063
+ "upright, upright piano": 881,
2064
+ "vacuum, vacuum cleaner": 882,
2065
+ "valley, vale": 979,
2066
+ "vase": 883,
2067
+ "vault": 884,
2068
+ "velvet": 885,
2069
+ "vending machine": 886,
2070
+ "vestment": 887,
2071
+ "viaduct": 888,
2072
+ "vine snake": 59,
2073
+ "violin, fiddle": 889,
2074
+ "vizsla, Hungarian pointer": 211,
2075
+ "volcano": 980,
2076
+ "volleyball": 890,
2077
+ "vulture": 23,
2078
+ "waffle iron": 891,
2079
+ "walking stick, walkingstick, stick insect": 313,
2080
+ "wall clock": 892,
2081
+ "wallaby, brush kangaroo": 104,
2082
+ "wallet, billfold, notecase, pocketbook": 893,
2083
+ "wardrobe, closet, press": 894,
2084
+ "warplane, military plane": 895,
2085
+ "warthog": 343,
2086
+ "washbasin, handbasin, washbowl, lavabo, wash-hand basin": 896,
2087
+ "washer, automatic washer, washing machine": 897,
2088
+ "water bottle": 898,
2089
+ "water buffalo, water ox, Asiatic buffalo, Bubalus bubalis": 346,
2090
+ "water jug": 899,
2091
+ "water ouzel, dipper": 20,
2092
+ "water snake": 58,
2093
+ "water tower": 900,
2094
+ "weasel": 356,
2095
+ "web site, website, internet site, site": 916,
2096
+ "weevil": 307,
2097
+ "whippet": 172,
2098
+ "whiptail, whiptail lizard": 41,
2099
+ "whiskey jug": 901,
2100
+ "whistle": 902,
2101
+ "white stork, Ciconia ciconia": 127,
2102
+ "white wolf, Arctic wolf, Canis lupus tundrarum": 270,
2103
+ "wig": 903,
2104
+ "wild boar, boar, Sus scrofa": 342,
2105
+ "window screen": 904,
2106
+ "window shade": 905,
2107
+ "wine bottle": 907,
2108
+ "wing": 908,
2109
+ "wire-haired fox terrier": 188,
2110
+ "wok": 909,
2111
+ "wolf spider, hunting spider": 77,
2112
+ "wombat": 106,
2113
+ "wood rabbit, cottontail, cottontail rabbit": 330,
2114
+ "wooden spoon": 910,
2115
+ "wool, woolen, woollen": 911,
2116
+ "worm fence, snake fence, snake-rail fence, Virginia fence": 912,
2117
+ "wreck": 913,
2118
+ "yawl": 914,
2119
+ "yellow lady's slipper, yellow lady-slipper, Cypripedium calceolus, Cypripedium parviflorum": 986,
2120
+ "yurt": 915,
2121
+ "zebra": 340,
2122
+ "zucchini, courgette": 939
2123
+ },
2124
+ "layer_norm_eps": 1e-12,
2125
+ "length_penalty": 1.0,
2126
+ "max_length": 20,
2127
+ "min_length": 0,
2128
+ "model_type": "deit",
2129
+ "no_repeat_ngram_size": 0,
2130
+ "num_attention_heads": 12,
2131
+ "num_beam_groups": 1,
2132
+ "num_beams": 1,
2133
+ "num_channels": 3,
2134
+ "num_hidden_layers": 12,
2135
+ "num_return_sequences": 1,
2136
+ "output_attentions": false,
2137
+ "output_hidden_states": false,
2138
+ "output_scores": false,
2139
+ "pad_token_id": null,
2140
+ "patch_size": 16,
2141
+ "prefix": null,
2142
+ "problem_type": null,
2143
+ "pruned_heads": {},
2144
+ "qkv_bias": true,
2145
+ "remove_invalid_values": false,
2146
+ "repetition_penalty": 1.0,
2147
+ "return_dict": true,
2148
+ "return_dict_in_generate": false,
2149
+ "sep_token_id": null,
2150
+ "suppress_tokens": null,
2151
+ "task_specific_params": null,
2152
+ "temperature": 1.0,
2153
+ "tf_legacy_loss": false,
2154
+ "tie_encoder_decoder": false,
2155
+ "tie_word_embeddings": true,
2156
+ "tokenizer_class": null,
2157
+ "top_k": 50,
2158
+ "top_p": 1.0,
2159
+ "torch_dtype": null,
2160
+ "torchscript": false,
2161
+ "transformers_version": "4.28.1",
2162
+ "typical_p": 1.0,
2163
+ "use_bfloat16": false
2164
+ },
2165
+ "eos_token_id": 2,
2166
+ "is_encoder_decoder": true,
2167
+ "length_penalty": 2.0,
2168
+ "max_length": 32,
2169
+ "model_type": "vision-encoder-decoder",
2170
+ "no_repeat_ngram_size": 3,
2171
+ "num_beams": 4,
2172
+ "pad_token_id": 1,
2173
+ "tie_word_embeddings": false,
2174
+ "torch_dtype": "float32",
2175
+ "transformers_version": null,
2176
+ "vocab_size": 32005
2177
+ }
generation_config.json ADDED
@@ -0,0 +1,12 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bos_token_id": 5,
3
+ "decoder_start_token_id": 0,
4
+ "early_stopping": true,
5
+ "eos_token_id": 2,
6
+ "length_penalty": 2.0,
7
+ "max_length": 32,
8
+ "no_repeat_ngram_size": 3,
9
+ "num_beams": 4,
10
+ "pad_token_id": 1,
11
+ "transformers_version": "4.28.1"
12
+ }
optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f01d2fa698cd9f1b95f15542efeafbc9f63f4fc827b510976f498a0d9acbf253
3
+ size 1801219783
pytorch_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:bd1c5ad08c90dfefefe65d21ea838a11b1d8d32871d767be63d487236094d917
3
+ size 903004649
rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ee8d5021bec0c13c8f4ae57179321d5fa50b72faf1ab34a51fab510959d87aeb
3
+ size 14503
scaler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:08d5dc0021b57ea01ac4750781cd9ab77fd4817271bcfbab2a925338eee5d5e2
3
+ size 559
scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:3babdb022788a895d8847434cb86e00bc960db1c78070ffc627ec985775a43ed
3
+ size 623
special_tokens_map.json ADDED
@@ -0,0 +1,19 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "additional_special_tokens": [
3
+ "<s>NOTUSED",
4
+ "</s>NOTUSED"
5
+ ],
6
+ "bos_token": "<s>",
7
+ "cls_token": "<s>",
8
+ "eos_token": "</s>",
9
+ "mask_token": {
10
+ "content": "<mask>",
11
+ "lstrip": true,
12
+ "normalized": false,
13
+ "rstrip": false,
14
+ "single_word": false
15
+ },
16
+ "pad_token": "<pad>",
17
+ "sep_token": "</s>",
18
+ "unk_token": "<unk>"
19
+ }
tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
tokenizer_config.json ADDED
@@ -0,0 +1,23 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "additional_special_tokens": [
3
+ "<s>NOTUSED",
4
+ "</s>NOTUSED"
5
+ ],
6
+ "bos_token": "<s>",
7
+ "clean_up_tokenization_spaces": true,
8
+ "cls_token": "<s>",
9
+ "eos_token": "</s>",
10
+ "mask_token": {
11
+ "__type": "AddedToken",
12
+ "content": "<mask>",
13
+ "lstrip": true,
14
+ "normalized": true,
15
+ "rstrip": false,
16
+ "single_word": false
17
+ },
18
+ "model_max_length": 512,
19
+ "pad_token": "<pad>",
20
+ "sep_token": "</s>",
21
+ "tokenizer_class": "CamembertTokenizer",
22
+ "unk_token": "<unk>"
23
+ }
trainer_state.json ADDED
@@ -0,0 +1,1056 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": null,
3
+ "best_model_checkpoint": null,
4
+ "epoch": 7.867046907267184,
5
+ "global_step": 160000,
6
+ "is_hyper_param_search": false,
7
+ "is_local_process_zero": true,
8
+ "is_world_process_zero": true,
9
+ "log_history": [
10
+ {
11
+ "epoch": 0.05,
12
+ "learning_rate": 3.9921644212803626e-05,
13
+ "loss": 4.8649,
14
+ "step": 1000
15
+ },
16
+ {
17
+ "epoch": 0.1,
18
+ "learning_rate": 3.984297374373095e-05,
19
+ "loss": 4.2624,
20
+ "step": 2000
21
+ },
22
+ {
23
+ "epoch": 0.15,
24
+ "learning_rate": 3.9764303274658276e-05,
25
+ "loss": 4.1126,
26
+ "step": 3000
27
+ },
28
+ {
29
+ "epoch": 0.2,
30
+ "learning_rate": 3.9685711476054684e-05,
31
+ "loss": 3.9901,
32
+ "step": 4000
33
+ },
34
+ {
35
+ "epoch": 0.25,
36
+ "learning_rate": 3.9607041006982005e-05,
37
+ "loss": 3.8152,
38
+ "step": 5000
39
+ },
40
+ {
41
+ "epoch": 0.3,
42
+ "learning_rate": 3.9528370537909334e-05,
43
+ "loss": 3.4152,
44
+ "step": 6000
45
+ },
46
+ {
47
+ "epoch": 0.34,
48
+ "learning_rate": 3.944970006883666e-05,
49
+ "loss": 3.0102,
50
+ "step": 7000
51
+ },
52
+ {
53
+ "epoch": 0.39,
54
+ "learning_rate": 3.937102959976399e-05,
55
+ "loss": 2.6704,
56
+ "step": 8000
57
+ },
58
+ {
59
+ "epoch": 0.44,
60
+ "learning_rate": 3.929235913069132e-05,
61
+ "loss": 2.4043,
62
+ "step": 9000
63
+ },
64
+ {
65
+ "epoch": 0.49,
66
+ "learning_rate": 3.921376733208772e-05,
67
+ "loss": 2.1653,
68
+ "step": 10000
69
+ },
70
+ {
71
+ "epoch": 0.54,
72
+ "learning_rate": 3.913509686301505e-05,
73
+ "loss": 1.9766,
74
+ "step": 11000
75
+ },
76
+ {
77
+ "epoch": 0.59,
78
+ "learning_rate": 3.905642639394238e-05,
79
+ "loss": 1.7996,
80
+ "step": 12000
81
+ },
82
+ {
83
+ "epoch": 0.64,
84
+ "learning_rate": 3.897775592486971e-05,
85
+ "loss": 1.66,
86
+ "step": 13000
87
+ },
88
+ {
89
+ "epoch": 0.69,
90
+ "learning_rate": 3.8899085455797035e-05,
91
+ "loss": 1.5483,
92
+ "step": 14000
93
+ },
94
+ {
95
+ "epoch": 0.74,
96
+ "learning_rate": 3.8820414986724364e-05,
97
+ "loss": 1.4356,
98
+ "step": 15000
99
+ },
100
+ {
101
+ "epoch": 0.79,
102
+ "learning_rate": 3.8741823188120765e-05,
103
+ "loss": 1.335,
104
+ "step": 16000
105
+ },
106
+ {
107
+ "epoch": 0.84,
108
+ "learning_rate": 3.8663231389517165e-05,
109
+ "loss": 1.255,
110
+ "step": 17000
111
+ },
112
+ {
113
+ "epoch": 0.89,
114
+ "learning_rate": 3.8584560920444494e-05,
115
+ "loss": 1.1804,
116
+ "step": 18000
117
+ },
118
+ {
119
+ "epoch": 0.93,
120
+ "learning_rate": 3.8505969121840894e-05,
121
+ "loss": 1.1252,
122
+ "step": 19000
123
+ },
124
+ {
125
+ "epoch": 0.98,
126
+ "learning_rate": 3.8427377323237294e-05,
127
+ "loss": 1.0548,
128
+ "step": 20000
129
+ },
130
+ {
131
+ "epoch": 0.98,
132
+ "eval_cer": 0.390676029242807,
133
+ "eval_loss": 0.9201487302780151,
134
+ "eval_runtime": 4761.7643,
135
+ "eval_samples_per_second": 15.186,
136
+ "eval_steps_per_second": 0.475,
137
+ "eval_wer": 0.49385302835019235,
138
+ "step": 20000
139
+ },
140
+ {
141
+ "epoch": 1.03,
142
+ "learning_rate": 3.8348785524633695e-05,
143
+ "loss": 0.9557,
144
+ "step": 21000
145
+ },
146
+ {
147
+ "epoch": 1.08,
148
+ "learning_rate": 3.8270115055561024e-05,
149
+ "loss": 0.9954,
150
+ "step": 22000
151
+ },
152
+ {
153
+ "epoch": 1.13,
154
+ "learning_rate": 3.8191444586488346e-05,
155
+ "loss": 0.973,
156
+ "step": 23000
157
+ },
158
+ {
159
+ "epoch": 1.18,
160
+ "learning_rate": 3.811277411741568e-05,
161
+ "loss": 0.9175,
162
+ "step": 24000
163
+ },
164
+ {
165
+ "epoch": 1.23,
166
+ "learning_rate": 3.803410364834301e-05,
167
+ "loss": 0.8689,
168
+ "step": 25000
169
+ },
170
+ {
171
+ "epoch": 1.28,
172
+ "learning_rate": 3.795543317927033e-05,
173
+ "loss": 0.8241,
174
+ "step": 26000
175
+ },
176
+ {
177
+ "epoch": 1.33,
178
+ "learning_rate": 3.787692005113581e-05,
179
+ "loss": 0.802,
180
+ "step": 27000
181
+ },
182
+ {
183
+ "epoch": 1.38,
184
+ "learning_rate": 3.779824958206314e-05,
185
+ "loss": 0.7675,
186
+ "step": 28000
187
+ },
188
+ {
189
+ "epoch": 1.43,
190
+ "learning_rate": 3.771957911299046e-05,
191
+ "loss": 0.7455,
192
+ "step": 29000
193
+ },
194
+ {
195
+ "epoch": 1.48,
196
+ "learning_rate": 3.764106598485594e-05,
197
+ "loss": 0.7133,
198
+ "step": 30000
199
+ },
200
+ {
201
+ "epoch": 1.52,
202
+ "learning_rate": 3.756239551578327e-05,
203
+ "loss": 0.688,
204
+ "step": 31000
205
+ },
206
+ {
207
+ "epoch": 1.57,
208
+ "learning_rate": 3.748372504671059e-05,
209
+ "loss": 0.6583,
210
+ "step": 32000
211
+ },
212
+ {
213
+ "epoch": 1.62,
214
+ "learning_rate": 3.740505457763792e-05,
215
+ "loss": 0.6379,
216
+ "step": 33000
217
+ },
218
+ {
219
+ "epoch": 1.67,
220
+ "learning_rate": 3.7326462779034327e-05,
221
+ "loss": 0.6216,
222
+ "step": 34000
223
+ },
224
+ {
225
+ "epoch": 1.72,
226
+ "learning_rate": 3.724787098043072e-05,
227
+ "loss": 0.6076,
228
+ "step": 35000
229
+ },
230
+ {
231
+ "epoch": 1.77,
232
+ "learning_rate": 3.716920051135805e-05,
233
+ "loss": 0.5834,
234
+ "step": 36000
235
+ },
236
+ {
237
+ "epoch": 1.82,
238
+ "learning_rate": 3.7090530042285384e-05,
239
+ "loss": 0.5629,
240
+ "step": 37000
241
+ },
242
+ {
243
+ "epoch": 1.87,
244
+ "learning_rate": 3.7011859573212706e-05,
245
+ "loss": 0.552,
246
+ "step": 38000
247
+ },
248
+ {
249
+ "epoch": 1.92,
250
+ "learning_rate": 3.6933189104140035e-05,
251
+ "loss": 0.533,
252
+ "step": 39000
253
+ },
254
+ {
255
+ "epoch": 1.97,
256
+ "learning_rate": 3.685459730553644e-05,
257
+ "loss": 0.5201,
258
+ "step": 40000
259
+ },
260
+ {
261
+ "epoch": 1.97,
262
+ "eval_cer": 0.25913786335133093,
263
+ "eval_loss": 0.621722936630249,
264
+ "eval_runtime": 4764.6248,
265
+ "eval_samples_per_second": 15.177,
266
+ "eval_steps_per_second": 0.474,
267
+ "eval_wer": 0.32157834292047605,
268
+ "step": 40000
269
+ },
270
+ {
271
+ "epoch": 2.02,
272
+ "learning_rate": 3.6775926836463764e-05,
273
+ "loss": 0.4791,
274
+ "step": 41000
275
+ },
276
+ {
277
+ "epoch": 2.07,
278
+ "learning_rate": 3.669725636739109e-05,
279
+ "loss": 0.4229,
280
+ "step": 42000
281
+ },
282
+ {
283
+ "epoch": 2.11,
284
+ "learning_rate": 3.661858589831842e-05,
285
+ "loss": 0.4253,
286
+ "step": 43000
287
+ },
288
+ {
289
+ "epoch": 2.16,
290
+ "learning_rate": 3.653999409971482e-05,
291
+ "loss": 0.4222,
292
+ "step": 44000
293
+ },
294
+ {
295
+ "epoch": 2.21,
296
+ "learning_rate": 3.646140230111122e-05,
297
+ "loss": 0.3999,
298
+ "step": 45000
299
+ },
300
+ {
301
+ "epoch": 2.26,
302
+ "learning_rate": 3.638273183203855e-05,
303
+ "loss": 0.4048,
304
+ "step": 46000
305
+ },
306
+ {
307
+ "epoch": 2.31,
308
+ "learning_rate": 3.630406136296588e-05,
309
+ "loss": 0.3977,
310
+ "step": 47000
311
+ },
312
+ {
313
+ "epoch": 2.36,
314
+ "learning_rate": 3.622539089389321e-05,
315
+ "loss": 0.3918,
316
+ "step": 48000
317
+ },
318
+ {
319
+ "epoch": 2.41,
320
+ "learning_rate": 3.614672042482054e-05,
321
+ "loss": 0.387,
322
+ "step": 49000
323
+ },
324
+ {
325
+ "epoch": 2.46,
326
+ "learning_rate": 3.606812862621694e-05,
327
+ "loss": 0.3815,
328
+ "step": 50000
329
+ },
330
+ {
331
+ "epoch": 2.51,
332
+ "learning_rate": 3.5989458157144266e-05,
333
+ "loss": 0.3732,
334
+ "step": 51000
335
+ },
336
+ {
337
+ "epoch": 2.56,
338
+ "learning_rate": 3.591086635854067e-05,
339
+ "loss": 0.3737,
340
+ "step": 52000
341
+ },
342
+ {
343
+ "epoch": 2.61,
344
+ "learning_rate": 3.5832195889467995e-05,
345
+ "loss": 0.3589,
346
+ "step": 53000
347
+ },
348
+ {
349
+ "epoch": 2.66,
350
+ "learning_rate": 3.5753525420395324e-05,
351
+ "loss": 0.359,
352
+ "step": 54000
353
+ },
354
+ {
355
+ "epoch": 2.7,
356
+ "learning_rate": 3.5674854951322646e-05,
357
+ "loss": 0.3536,
358
+ "step": 55000
359
+ },
360
+ {
361
+ "epoch": 2.75,
362
+ "learning_rate": 3.5596341823188125e-05,
363
+ "loss": 0.346,
364
+ "step": 56000
365
+ },
366
+ {
367
+ "epoch": 2.8,
368
+ "learning_rate": 3.5517750024584525e-05,
369
+ "loss": 0.3398,
370
+ "step": 57000
371
+ },
372
+ {
373
+ "epoch": 2.85,
374
+ "learning_rate": 3.543907955551185e-05,
375
+ "loss": 0.3382,
376
+ "step": 58000
377
+ },
378
+ {
379
+ "epoch": 2.9,
380
+ "learning_rate": 3.536040908643918e-05,
381
+ "loss": 0.3305,
382
+ "step": 59000
383
+ },
384
+ {
385
+ "epoch": 2.95,
386
+ "learning_rate": 3.528173861736651e-05,
387
+ "loss": 0.3248,
388
+ "step": 60000
389
+ },
390
+ {
391
+ "epoch": 2.95,
392
+ "eval_cer": 0.19179082390807053,
393
+ "eval_loss": 0.41522958874702454,
394
+ "eval_runtime": 4766.524,
395
+ "eval_samples_per_second": 15.171,
396
+ "eval_steps_per_second": 0.474,
397
+ "eval_wer": 0.24954789141369815,
398
+ "step": 60000
399
+ },
400
+ {
401
+ "epoch": 3.0,
402
+ "learning_rate": 3.520306814829383e-05,
403
+ "loss": 0.3219,
404
+ "step": 61000
405
+ },
406
+ {
407
+ "epoch": 3.05,
408
+ "learning_rate": 3.512439767922116e-05,
409
+ "loss": 0.2627,
410
+ "step": 62000
411
+ },
412
+ {
413
+ "epoch": 3.1,
414
+ "learning_rate": 3.50457272101485e-05,
415
+ "loss": 0.2599,
416
+ "step": 63000
417
+ },
418
+ {
419
+ "epoch": 3.15,
420
+ "learning_rate": 3.496705674107582e-05,
421
+ "loss": 0.2617,
422
+ "step": 64000
423
+ },
424
+ {
425
+ "epoch": 3.2,
426
+ "learning_rate": 3.488838627200315e-05,
427
+ "loss": 0.2612,
428
+ "step": 65000
429
+ },
430
+ {
431
+ "epoch": 3.25,
432
+ "learning_rate": 3.480979447339955e-05,
433
+ "loss": 0.263,
434
+ "step": 66000
435
+ },
436
+ {
437
+ "epoch": 3.29,
438
+ "learning_rate": 3.473112400432688e-05,
439
+ "loss": 0.2573,
440
+ "step": 67000
441
+ },
442
+ {
443
+ "epoch": 3.34,
444
+ "learning_rate": 3.465253220572328e-05,
445
+ "loss": 0.2533,
446
+ "step": 68000
447
+ },
448
+ {
449
+ "epoch": 3.39,
450
+ "learning_rate": 3.4573861736650606e-05,
451
+ "loss": 0.256,
452
+ "step": 69000
453
+ },
454
+ {
455
+ "epoch": 3.44,
456
+ "learning_rate": 3.4495191267577935e-05,
457
+ "loss": 0.2498,
458
+ "step": 70000
459
+ },
460
+ {
461
+ "epoch": 3.49,
462
+ "learning_rate": 3.4416520798505264e-05,
463
+ "loss": 0.248,
464
+ "step": 71000
465
+ },
466
+ {
467
+ "epoch": 3.54,
468
+ "learning_rate": 3.4337928999901664e-05,
469
+ "loss": 0.2458,
470
+ "step": 72000
471
+ },
472
+ {
473
+ "epoch": 3.59,
474
+ "learning_rate": 3.4259337201298065e-05,
475
+ "loss": 0.2498,
476
+ "step": 73000
477
+ },
478
+ {
479
+ "epoch": 3.64,
480
+ "learning_rate": 3.418066673222539e-05,
481
+ "loss": 0.2423,
482
+ "step": 74000
483
+ },
484
+ {
485
+ "epoch": 3.69,
486
+ "learning_rate": 3.4102074933621794e-05,
487
+ "loss": 0.2374,
488
+ "step": 75000
489
+ },
490
+ {
491
+ "epoch": 3.74,
492
+ "learning_rate": 3.402340446454912e-05,
493
+ "loss": 0.2427,
494
+ "step": 76000
495
+ },
496
+ {
497
+ "epoch": 3.79,
498
+ "learning_rate": 3.394473399547645e-05,
499
+ "loss": 0.2374,
500
+ "step": 77000
501
+ },
502
+ {
503
+ "epoch": 3.84,
504
+ "learning_rate": 3.386606352640378e-05,
505
+ "loss": 0.24,
506
+ "step": 78000
507
+ },
508
+ {
509
+ "epoch": 3.88,
510
+ "learning_rate": 3.378739305733111e-05,
511
+ "loss": 0.2303,
512
+ "step": 79000
513
+ },
514
+ {
515
+ "epoch": 3.93,
516
+ "learning_rate": 3.370872258825844e-05,
517
+ "loss": 0.2337,
518
+ "step": 80000
519
+ },
520
+ {
521
+ "epoch": 3.93,
522
+ "eval_cer": 0.17718038202544326,
523
+ "eval_loss": 0.568325936794281,
524
+ "eval_runtime": 4765.8542,
525
+ "eval_samples_per_second": 15.173,
526
+ "eval_steps_per_second": 0.474,
527
+ "eval_wer": 0.23509144980666905,
528
+ "step": 80000
529
+ },
530
+ {
531
+ "epoch": 3.98,
532
+ "learning_rate": 3.3630052119185766e-05,
533
+ "loss": 0.2298,
534
+ "step": 81000
535
+ },
536
+ {
537
+ "epoch": 4.03,
538
+ "learning_rate": 3.355138165011309e-05,
539
+ "loss": 0.1984,
540
+ "step": 82000
541
+ },
542
+ {
543
+ "epoch": 4.08,
544
+ "learning_rate": 3.3472789851509495e-05,
545
+ "loss": 0.1805,
546
+ "step": 83000
547
+ },
548
+ {
549
+ "epoch": 4.13,
550
+ "learning_rate": 3.3394198052905895e-05,
551
+ "loss": 0.1812,
552
+ "step": 84000
553
+ },
554
+ {
555
+ "epoch": 4.18,
556
+ "learning_rate": 3.331552758383322e-05,
557
+ "loss": 0.1835,
558
+ "step": 85000
559
+ },
560
+ {
561
+ "epoch": 4.23,
562
+ "learning_rate": 3.323685711476055e-05,
563
+ "loss": 0.1796,
564
+ "step": 86000
565
+ },
566
+ {
567
+ "epoch": 4.28,
568
+ "learning_rate": 3.315818664568788e-05,
569
+ "loss": 0.186,
570
+ "step": 87000
571
+ },
572
+ {
573
+ "epoch": 4.33,
574
+ "learning_rate": 3.3079516176615203e-05,
575
+ "loss": 0.1844,
576
+ "step": 88000
577
+ },
578
+ {
579
+ "epoch": 4.38,
580
+ "learning_rate": 3.300084570754253e-05,
581
+ "loss": 0.1815,
582
+ "step": 89000
583
+ },
584
+ {
585
+ "epoch": 4.43,
586
+ "learning_rate": 3.292225390893893e-05,
587
+ "loss": 0.1796,
588
+ "step": 90000
589
+ },
590
+ {
591
+ "epoch": 4.47,
592
+ "learning_rate": 3.284366211033533e-05,
593
+ "loss": 0.1806,
594
+ "step": 91000
595
+ },
596
+ {
597
+ "epoch": 4.52,
598
+ "learning_rate": 3.276499164126266e-05,
599
+ "loss": 0.1789,
600
+ "step": 92000
601
+ },
602
+ {
603
+ "epoch": 4.57,
604
+ "learning_rate": 3.268639984265907e-05,
605
+ "loss": 0.1793,
606
+ "step": 93000
607
+ },
608
+ {
609
+ "epoch": 4.62,
610
+ "learning_rate": 3.260772937358639e-05,
611
+ "loss": 0.1771,
612
+ "step": 94000
613
+ },
614
+ {
615
+ "epoch": 4.67,
616
+ "learning_rate": 3.252905890451372e-05,
617
+ "loss": 0.1815,
618
+ "step": 95000
619
+ },
620
+ {
621
+ "epoch": 4.72,
622
+ "learning_rate": 3.245038843544105e-05,
623
+ "loss": 0.18,
624
+ "step": 96000
625
+ },
626
+ {
627
+ "epoch": 4.77,
628
+ "learning_rate": 3.237179663683745e-05,
629
+ "loss": 0.1767,
630
+ "step": 97000
631
+ },
632
+ {
633
+ "epoch": 4.82,
634
+ "learning_rate": 3.229312616776478e-05,
635
+ "loss": 0.1737,
636
+ "step": 98000
637
+ },
638
+ {
639
+ "epoch": 4.87,
640
+ "learning_rate": 3.2214455698692106e-05,
641
+ "loss": 0.1731,
642
+ "step": 99000
643
+ },
644
+ {
645
+ "epoch": 4.92,
646
+ "learning_rate": 3.2135863900088506e-05,
647
+ "loss": 0.1754,
648
+ "step": 100000
649
+ },
650
+ {
651
+ "epoch": 4.92,
652
+ "eval_cer": 0.18740275862352454,
653
+ "eval_loss": 0.3622461259365082,
654
+ "eval_runtime": 4765.3375,
655
+ "eval_samples_per_second": 15.175,
656
+ "eval_steps_per_second": 0.474,
657
+ "eval_wer": 0.2296571196445318,
658
+ "step": 100000
659
+ },
660
+ {
661
+ "epoch": 4.97,
662
+ "learning_rate": 3.205727210148491e-05,
663
+ "loss": 0.172,
664
+ "step": 101000
665
+ },
666
+ {
667
+ "epoch": 5.02,
668
+ "learning_rate": 3.1978601632412236e-05,
669
+ "loss": 0.1624,
670
+ "step": 102000
671
+ },
672
+ {
673
+ "epoch": 5.06,
674
+ "learning_rate": 3.1899931163339564e-05,
675
+ "loss": 0.1304,
676
+ "step": 103000
677
+ },
678
+ {
679
+ "epoch": 5.11,
680
+ "learning_rate": 3.182126069426689e-05,
681
+ "loss": 0.1349,
682
+ "step": 104000
683
+ },
684
+ {
685
+ "epoch": 5.16,
686
+ "learning_rate": 3.174259022519422e-05,
687
+ "loss": 0.1351,
688
+ "step": 105000
689
+ },
690
+ {
691
+ "epoch": 5.21,
692
+ "learning_rate": 3.166399842659062e-05,
693
+ "loss": 0.1366,
694
+ "step": 106000
695
+ },
696
+ {
697
+ "epoch": 5.26,
698
+ "learning_rate": 3.158532795751795e-05,
699
+ "loss": 0.1363,
700
+ "step": 107000
701
+ },
702
+ {
703
+ "epoch": 5.31,
704
+ "learning_rate": 3.150681482938342e-05,
705
+ "loss": 0.1348,
706
+ "step": 108000
707
+ },
708
+ {
709
+ "epoch": 5.36,
710
+ "learning_rate": 3.142814436031075e-05,
711
+ "loss": 0.1348,
712
+ "step": 109000
713
+ },
714
+ {
715
+ "epoch": 5.41,
716
+ "learning_rate": 3.134947389123808e-05,
717
+ "loss": 0.1371,
718
+ "step": 110000
719
+ },
720
+ {
721
+ "epoch": 5.46,
722
+ "learning_rate": 3.127088209263448e-05,
723
+ "loss": 0.1374,
724
+ "step": 111000
725
+ },
726
+ {
727
+ "epoch": 5.51,
728
+ "learning_rate": 3.119221162356181e-05,
729
+ "loss": 0.1333,
730
+ "step": 112000
731
+ },
732
+ {
733
+ "epoch": 5.56,
734
+ "learning_rate": 3.111354115448914e-05,
735
+ "loss": 0.1362,
736
+ "step": 113000
737
+ },
738
+ {
739
+ "epoch": 5.61,
740
+ "learning_rate": 3.103494935588554e-05,
741
+ "loss": 0.1355,
742
+ "step": 114000
743
+ },
744
+ {
745
+ "epoch": 5.65,
746
+ "learning_rate": 3.095627888681287e-05,
747
+ "loss": 0.1369,
748
+ "step": 115000
749
+ },
750
+ {
751
+ "epoch": 5.7,
752
+ "learning_rate": 3.0877608417740196e-05,
753
+ "loss": 0.1369,
754
+ "step": 116000
755
+ },
756
+ {
757
+ "epoch": 5.75,
758
+ "learning_rate": 3.079893794866752e-05,
759
+ "loss": 0.1368,
760
+ "step": 117000
761
+ },
762
+ {
763
+ "epoch": 5.8,
764
+ "learning_rate": 3.0720424820533e-05,
765
+ "loss": 0.1372,
766
+ "step": 118000
767
+ },
768
+ {
769
+ "epoch": 5.85,
770
+ "learning_rate": 3.0641754351460326e-05,
771
+ "loss": 0.1329,
772
+ "step": 119000
773
+ },
774
+ {
775
+ "epoch": 5.9,
776
+ "learning_rate": 3.056316255285672e-05,
777
+ "loss": 0.1339,
778
+ "step": 120000
779
+ },
780
+ {
781
+ "epoch": 5.9,
782
+ "eval_cer": 0.16900559795182515,
783
+ "eval_loss": 0.891129732131958,
784
+ "eval_runtime": 4771.5866,
785
+ "eval_samples_per_second": 15.155,
786
+ "eval_steps_per_second": 0.474,
787
+ "eval_wer": 0.2033450518809021,
788
+ "step": 120000
789
+ },
790
+ {
791
+ "epoch": 5.95,
792
+ "learning_rate": 3.048449208378405e-05,
793
+ "loss": 0.1319,
794
+ "step": 121000
795
+ },
796
+ {
797
+ "epoch": 6.0,
798
+ "learning_rate": 3.0405900285180455e-05,
799
+ "loss": 0.1363,
800
+ "step": 122000
801
+ },
802
+ {
803
+ "epoch": 6.05,
804
+ "learning_rate": 3.032722981610778e-05,
805
+ "loss": 0.1022,
806
+ "step": 123000
807
+ },
808
+ {
809
+ "epoch": 6.1,
810
+ "learning_rate": 3.024855934703511e-05,
811
+ "loss": 0.0999,
812
+ "step": 124000
813
+ },
814
+ {
815
+ "epoch": 6.15,
816
+ "learning_rate": 3.0169888877962438e-05,
817
+ "loss": 0.1014,
818
+ "step": 125000
819
+ },
820
+ {
821
+ "epoch": 6.2,
822
+ "learning_rate": 3.0091218408889763e-05,
823
+ "loss": 0.1034,
824
+ "step": 126000
825
+ },
826
+ {
827
+ "epoch": 6.24,
828
+ "learning_rate": 3.0012547939817095e-05,
829
+ "loss": 0.1034,
830
+ "step": 127000
831
+ },
832
+ {
833
+ "epoch": 6.29,
834
+ "learning_rate": 2.9933956141213496e-05,
835
+ "loss": 0.101,
836
+ "step": 128000
837
+ },
838
+ {
839
+ "epoch": 6.34,
840
+ "learning_rate": 2.985528567214082e-05,
841
+ "loss": 0.1054,
842
+ "step": 129000
843
+ },
844
+ {
845
+ "epoch": 6.39,
846
+ "learning_rate": 2.977661520306815e-05,
847
+ "loss": 0.1026,
848
+ "step": 130000
849
+ },
850
+ {
851
+ "epoch": 6.44,
852
+ "learning_rate": 2.969794473399548e-05,
853
+ "loss": 0.1068,
854
+ "step": 131000
855
+ },
856
+ {
857
+ "epoch": 6.49,
858
+ "learning_rate": 2.961943160586095e-05,
859
+ "loss": 0.1081,
860
+ "step": 132000
861
+ },
862
+ {
863
+ "epoch": 6.54,
864
+ "learning_rate": 2.954076113678828e-05,
865
+ "loss": 0.106,
866
+ "step": 133000
867
+ },
868
+ {
869
+ "epoch": 6.59,
870
+ "learning_rate": 2.946209066771561e-05,
871
+ "loss": 0.105,
872
+ "step": 134000
873
+ },
874
+ {
875
+ "epoch": 6.64,
876
+ "learning_rate": 2.9383498869112008e-05,
877
+ "loss": 0.1072,
878
+ "step": 135000
879
+ },
880
+ {
881
+ "epoch": 6.69,
882
+ "learning_rate": 2.9304828400039337e-05,
883
+ "loss": 0.1052,
884
+ "step": 136000
885
+ },
886
+ {
887
+ "epoch": 6.74,
888
+ "learning_rate": 2.922615793096667e-05,
889
+ "loss": 0.1069,
890
+ "step": 137000
891
+ },
892
+ {
893
+ "epoch": 6.79,
894
+ "learning_rate": 2.9147487461893994e-05,
895
+ "loss": 0.1075,
896
+ "step": 138000
897
+ },
898
+ {
899
+ "epoch": 6.83,
900
+ "learning_rate": 2.9068974333759466e-05,
901
+ "loss": 0.1057,
902
+ "step": 139000
903
+ },
904
+ {
905
+ "epoch": 6.88,
906
+ "learning_rate": 2.899038253515587e-05,
907
+ "loss": 0.1054,
908
+ "step": 140000
909
+ },
910
+ {
911
+ "epoch": 6.88,
912
+ "eval_cer": 0.152140834629885,
913
+ "eval_loss": 0.7343257069587708,
914
+ "eval_runtime": 4764.4162,
915
+ "eval_samples_per_second": 15.178,
916
+ "eval_steps_per_second": 0.474,
917
+ "eval_wer": 0.19141319665595113,
918
+ "step": 140000
919
+ },
920
+ {
921
+ "epoch": 6.93,
922
+ "learning_rate": 2.8911712066083196e-05,
923
+ "loss": 0.1085,
924
+ "step": 141000
925
+ },
926
+ {
927
+ "epoch": 6.98,
928
+ "learning_rate": 2.8833041597010524e-05,
929
+ "loss": 0.1064,
930
+ "step": 142000
931
+ },
932
+ {
933
+ "epoch": 7.03,
934
+ "learning_rate": 2.8754528468876e-05,
935
+ "loss": 0.0993,
936
+ "step": 143000
937
+ },
938
+ {
939
+ "epoch": 7.08,
940
+ "learning_rate": 2.8675857999803325e-05,
941
+ "loss": 0.079,
942
+ "step": 144000
943
+ },
944
+ {
945
+ "epoch": 7.13,
946
+ "learning_rate": 2.8597187530730654e-05,
947
+ "loss": 0.0799,
948
+ "step": 145000
949
+ },
950
+ {
951
+ "epoch": 7.18,
952
+ "learning_rate": 2.8518517061657986e-05,
953
+ "loss": 0.0803,
954
+ "step": 146000
955
+ },
956
+ {
957
+ "epoch": 7.23,
958
+ "learning_rate": 2.843984659258531e-05,
959
+ "loss": 0.0808,
960
+ "step": 147000
961
+ },
962
+ {
963
+ "epoch": 7.28,
964
+ "learning_rate": 2.8361412134919855e-05,
965
+ "loss": 0.1072,
966
+ "step": 148000
967
+ },
968
+ {
969
+ "epoch": 7.33,
970
+ "learning_rate": 2.8282741665847187e-05,
971
+ "loss": 0.0799,
972
+ "step": 149000
973
+ },
974
+ {
975
+ "epoch": 7.38,
976
+ "learning_rate": 2.8204071196774513e-05,
977
+ "loss": 0.0821,
978
+ "step": 150000
979
+ },
980
+ {
981
+ "epoch": 7.42,
982
+ "learning_rate": 2.812540072770184e-05,
983
+ "loss": 0.0838,
984
+ "step": 151000
985
+ },
986
+ {
987
+ "epoch": 7.47,
988
+ "learning_rate": 2.804673025862917e-05,
989
+ "loss": 0.0843,
990
+ "step": 152000
991
+ },
992
+ {
993
+ "epoch": 7.52,
994
+ "learning_rate": 2.7968059789556495e-05,
995
+ "loss": 0.0831,
996
+ "step": 153000
997
+ },
998
+ {
999
+ "epoch": 7.57,
1000
+ "learning_rate": 2.7889389320483827e-05,
1001
+ "loss": 0.0831,
1002
+ "step": 154000
1003
+ },
1004
+ {
1005
+ "epoch": 7.62,
1006
+ "learning_rate": 2.7810797521880228e-05,
1007
+ "loss": 0.0836,
1008
+ "step": 155000
1009
+ },
1010
+ {
1011
+ "epoch": 7.67,
1012
+ "learning_rate": 2.7732127052807553e-05,
1013
+ "loss": 0.0838,
1014
+ "step": 156000
1015
+ },
1016
+ {
1017
+ "epoch": 7.72,
1018
+ "learning_rate": 2.7653456583734882e-05,
1019
+ "loss": 0.0825,
1020
+ "step": 157000
1021
+ },
1022
+ {
1023
+ "epoch": 7.77,
1024
+ "learning_rate": 2.7574786114662214e-05,
1025
+ "loss": 0.0848,
1026
+ "step": 158000
1027
+ },
1028
+ {
1029
+ "epoch": 7.82,
1030
+ "learning_rate": 2.749611564558954e-05,
1031
+ "loss": 0.0865,
1032
+ "step": 159000
1033
+ },
1034
+ {
1035
+ "epoch": 7.87,
1036
+ "learning_rate": 2.7417445176516868e-05,
1037
+ "loss": 0.0847,
1038
+ "step": 160000
1039
+ },
1040
+ {
1041
+ "epoch": 7.87,
1042
+ "eval_cer": 0.1614900513208385,
1043
+ "eval_loss": 0.4246867895126343,
1044
+ "eval_runtime": 4767.9424,
1045
+ "eval_samples_per_second": 15.166,
1046
+ "eval_steps_per_second": 0.474,
1047
+ "eval_wer": 0.2072768669852908,
1048
+ "step": 160000
1049
+ }
1050
+ ],
1051
+ "max_steps": 508450,
1052
+ "num_train_epochs": 25,
1053
+ "total_flos": 2.727768050247581e+21,
1054
+ "trial_name": null,
1055
+ "trial_params": null
1056
+ }
training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:2b850eb348d1eb89db87c29386b5451d7f69ecaac997f63513c3ce4024c0e93c
3
+ size 3631