laszlokiss27
commited on
Commit
•
5bd74a2
1
Parent(s):
cf3e670
Upload 8 files
Browse files- all_results.json +13 -0
- config.json +737 -0
- model.safetensors +3 -0
- preprocessor_config.json +32 -0
- test_results.json +8 -0
- train_results.json +8 -0
- trainer_state.json +792 -0
- training_args.bin +3 -0
all_results.json
ADDED
@@ -0,0 +1,13 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"epoch": 5.0,
|
3 |
+
"eval_accuracy": 0.774412,
|
4 |
+
"eval_loss": 0.8919877409934998,
|
5 |
+
"eval_runtime": 138.4801,
|
6 |
+
"eval_samples_per_second": 1805.314,
|
7 |
+
"eval_steps_per_second": 7.055,
|
8 |
+
"total_flos": 1.93274424e+18,
|
9 |
+
"train_loss": 0.9357909288237652,
|
10 |
+
"train_runtime": 45635.435,
|
11 |
+
"train_samples_per_second": 493.038,
|
12 |
+
"train_steps_per_second": 1.926
|
13 |
+
}
|
config.json
ADDED
@@ -0,0 +1,737 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"_name_or_path": "apple/mobilevitv2-1.0-imagenet1k-256",
|
3 |
+
"architectures": [
|
4 |
+
"MobileViTV2ForImageClassification"
|
5 |
+
],
|
6 |
+
"aspp_dropout_prob": 0.1,
|
7 |
+
"aspp_out_channels": 512,
|
8 |
+
"atrous_rates": [
|
9 |
+
6,
|
10 |
+
12,
|
11 |
+
18
|
12 |
+
],
|
13 |
+
"attn_dropout": 0.0,
|
14 |
+
"base_attn_unit_dims": [
|
15 |
+
128,
|
16 |
+
192,
|
17 |
+
256
|
18 |
+
],
|
19 |
+
"classifier_dropout_prob": 0.1,
|
20 |
+
"conv_kernel_size": 3,
|
21 |
+
"expand_ratio": 2.0,
|
22 |
+
"ffn_dropout": 0.0,
|
23 |
+
"ffn_multiplier": 2,
|
24 |
+
"hidden_act": "swish",
|
25 |
+
"id2label": {
|
26 |
+
"0": "aircraft carrier",
|
27 |
+
"1": "airplane",
|
28 |
+
"10": "asparagus",
|
29 |
+
"100": "dumbbell",
|
30 |
+
"101": "ear",
|
31 |
+
"102": "elbow",
|
32 |
+
"103": "elephant",
|
33 |
+
"104": "envelope",
|
34 |
+
"105": "eraser",
|
35 |
+
"106": "eye",
|
36 |
+
"107": "eyeglasses",
|
37 |
+
"108": "face",
|
38 |
+
"109": "fan",
|
39 |
+
"11": "axe",
|
40 |
+
"110": "feather",
|
41 |
+
"111": "fence",
|
42 |
+
"112": "finger",
|
43 |
+
"113": "fire hydrant",
|
44 |
+
"114": "fireplace",
|
45 |
+
"115": "firetruck",
|
46 |
+
"116": "fish",
|
47 |
+
"117": "flamingo",
|
48 |
+
"118": "flashlight",
|
49 |
+
"119": "flip flops",
|
50 |
+
"12": "backpack",
|
51 |
+
"120": "floor lamp",
|
52 |
+
"121": "flower",
|
53 |
+
"122": "flying saucer",
|
54 |
+
"123": "foot",
|
55 |
+
"124": "fork",
|
56 |
+
"125": "frog",
|
57 |
+
"126": "frying pan",
|
58 |
+
"127": "garden hose",
|
59 |
+
"128": "garden",
|
60 |
+
"129": "giraffe",
|
61 |
+
"13": "banana",
|
62 |
+
"130": "goatee",
|
63 |
+
"131": "golf club",
|
64 |
+
"132": "grapes",
|
65 |
+
"133": "grass",
|
66 |
+
"134": "guitar",
|
67 |
+
"135": "hamburger",
|
68 |
+
"136": "hammer",
|
69 |
+
"137": "hand",
|
70 |
+
"138": "harp",
|
71 |
+
"139": "hat",
|
72 |
+
"14": "bandage",
|
73 |
+
"140": "headphones",
|
74 |
+
"141": "hedgehog",
|
75 |
+
"142": "helicopter",
|
76 |
+
"143": "helmet",
|
77 |
+
"144": "hexagon",
|
78 |
+
"145": "hockey puck",
|
79 |
+
"146": "hockey stick",
|
80 |
+
"147": "horse",
|
81 |
+
"148": "hospital",
|
82 |
+
"149": "hot air balloon",
|
83 |
+
"15": "barn",
|
84 |
+
"150": "hot dog",
|
85 |
+
"151": "hot tub",
|
86 |
+
"152": "hourglass",
|
87 |
+
"153": "house plant",
|
88 |
+
"154": "house",
|
89 |
+
"155": "hurricane",
|
90 |
+
"156": "ice cream",
|
91 |
+
"157": "jacket",
|
92 |
+
"158": "jail",
|
93 |
+
"159": "kangaroo",
|
94 |
+
"16": "baseball bat",
|
95 |
+
"160": "key",
|
96 |
+
"161": "keyboard",
|
97 |
+
"162": "knee",
|
98 |
+
"163": "knife",
|
99 |
+
"164": "ladder",
|
100 |
+
"165": "lantern",
|
101 |
+
"166": "laptop",
|
102 |
+
"167": "leaf",
|
103 |
+
"168": "leg",
|
104 |
+
"169": "light bulb",
|
105 |
+
"17": "baseball",
|
106 |
+
"170": "lighter",
|
107 |
+
"171": "lighthouse",
|
108 |
+
"172": "lightning",
|
109 |
+
"173": "line",
|
110 |
+
"174": "lion",
|
111 |
+
"175": "lipstick",
|
112 |
+
"176": "lobster",
|
113 |
+
"177": "lollipop",
|
114 |
+
"178": "mailbox",
|
115 |
+
"179": "map",
|
116 |
+
"18": "basket",
|
117 |
+
"180": "marker",
|
118 |
+
"181": "matches",
|
119 |
+
"182": "megaphone",
|
120 |
+
"183": "mermaid",
|
121 |
+
"184": "microphone",
|
122 |
+
"185": "microwave",
|
123 |
+
"186": "monkey",
|
124 |
+
"187": "moon",
|
125 |
+
"188": "mosquito",
|
126 |
+
"189": "motorbike",
|
127 |
+
"19": "basketball",
|
128 |
+
"190": "mountain",
|
129 |
+
"191": "mouse",
|
130 |
+
"192": "moustache",
|
131 |
+
"193": "mouth",
|
132 |
+
"194": "mug",
|
133 |
+
"195": "mushroom",
|
134 |
+
"196": "nail",
|
135 |
+
"197": "necklace",
|
136 |
+
"198": "nose",
|
137 |
+
"199": "ocean",
|
138 |
+
"2": "alarm clock",
|
139 |
+
"20": "bat",
|
140 |
+
"200": "octagon",
|
141 |
+
"201": "octopus",
|
142 |
+
"202": "onion",
|
143 |
+
"203": "oven",
|
144 |
+
"204": "owl",
|
145 |
+
"205": "paint can",
|
146 |
+
"206": "paintbrush",
|
147 |
+
"207": "palm tree",
|
148 |
+
"208": "panda",
|
149 |
+
"209": "pants",
|
150 |
+
"21": "bathtub",
|
151 |
+
"210": "paper clip",
|
152 |
+
"211": "parachute",
|
153 |
+
"212": "parrot",
|
154 |
+
"213": "passport",
|
155 |
+
"214": "peanut",
|
156 |
+
"215": "pear",
|
157 |
+
"216": "peas",
|
158 |
+
"217": "pencil",
|
159 |
+
"218": "penguin",
|
160 |
+
"219": "piano",
|
161 |
+
"22": "beach",
|
162 |
+
"220": "pickup truck",
|
163 |
+
"221": "picture frame",
|
164 |
+
"222": "pig",
|
165 |
+
"223": "pillow",
|
166 |
+
"224": "pineapple",
|
167 |
+
"225": "pizza",
|
168 |
+
"226": "pliers",
|
169 |
+
"227": "police car",
|
170 |
+
"228": "pond",
|
171 |
+
"229": "pool",
|
172 |
+
"23": "bear",
|
173 |
+
"230": "popsicle",
|
174 |
+
"231": "postcard",
|
175 |
+
"232": "potato",
|
176 |
+
"233": "power outlet",
|
177 |
+
"234": "purse",
|
178 |
+
"235": "rabbit",
|
179 |
+
"236": "raccoon",
|
180 |
+
"237": "radio",
|
181 |
+
"238": "rain",
|
182 |
+
"239": "rainbow",
|
183 |
+
"24": "beard",
|
184 |
+
"240": "rake",
|
185 |
+
"241": "remote control",
|
186 |
+
"242": "rhinoceros",
|
187 |
+
"243": "rifle",
|
188 |
+
"244": "river",
|
189 |
+
"245": "roller coaster",
|
190 |
+
"246": "rollerskates",
|
191 |
+
"247": "sailboat",
|
192 |
+
"248": "sandwich",
|
193 |
+
"249": "saw",
|
194 |
+
"25": "bed",
|
195 |
+
"250": "saxophone",
|
196 |
+
"251": "school bus",
|
197 |
+
"252": "scissors",
|
198 |
+
"253": "scorpion",
|
199 |
+
"254": "screwdriver",
|
200 |
+
"255": "sea turtle",
|
201 |
+
"256": "see saw",
|
202 |
+
"257": "shark",
|
203 |
+
"258": "sheep",
|
204 |
+
"259": "shoe",
|
205 |
+
"26": "bee",
|
206 |
+
"260": "shorts",
|
207 |
+
"261": "shovel",
|
208 |
+
"262": "sink",
|
209 |
+
"263": "skateboard",
|
210 |
+
"264": "skull",
|
211 |
+
"265": "skyscraper",
|
212 |
+
"266": "sleeping bag",
|
213 |
+
"267": "smiley face",
|
214 |
+
"268": "snail",
|
215 |
+
"269": "snake",
|
216 |
+
"27": "belt",
|
217 |
+
"270": "snorkel",
|
218 |
+
"271": "snowflake",
|
219 |
+
"272": "snowman",
|
220 |
+
"273": "soccer ball",
|
221 |
+
"274": "sock",
|
222 |
+
"275": "speedboat",
|
223 |
+
"276": "spider",
|
224 |
+
"277": "spoon",
|
225 |
+
"278": "spreadsheet",
|
226 |
+
"279": "square",
|
227 |
+
"28": "bench",
|
228 |
+
"280": "squiggle",
|
229 |
+
"281": "squirrel",
|
230 |
+
"282": "stairs",
|
231 |
+
"283": "star",
|
232 |
+
"284": "steak",
|
233 |
+
"285": "stereo",
|
234 |
+
"286": "stethoscope",
|
235 |
+
"287": "stitches",
|
236 |
+
"288": "stop sign",
|
237 |
+
"289": "stove",
|
238 |
+
"29": "bicycle",
|
239 |
+
"290": "strawberry",
|
240 |
+
"291": "streetlight",
|
241 |
+
"292": "string bean",
|
242 |
+
"293": "submarine",
|
243 |
+
"294": "suitcase",
|
244 |
+
"295": "sun",
|
245 |
+
"296": "swan",
|
246 |
+
"297": "sweater",
|
247 |
+
"298": "swing set",
|
248 |
+
"299": "sword",
|
249 |
+
"3": "ambulance",
|
250 |
+
"30": "binoculars",
|
251 |
+
"300": "syringe",
|
252 |
+
"301": "t-shirt",
|
253 |
+
"302": "table",
|
254 |
+
"303": "teapot",
|
255 |
+
"304": "teddy-bear",
|
256 |
+
"305": "telephone",
|
257 |
+
"306": "television",
|
258 |
+
"307": "tennis racquet",
|
259 |
+
"308": "tent",
|
260 |
+
"309": "The Eiffel Tower",
|
261 |
+
"31": "bird",
|
262 |
+
"310": "The Great Wall of China",
|
263 |
+
"311": "The Mona Lisa",
|
264 |
+
"312": "tiger",
|
265 |
+
"313": "toaster",
|
266 |
+
"314": "toe",
|
267 |
+
"315": "toilet",
|
268 |
+
"316": "tooth",
|
269 |
+
"317": "toothbrush",
|
270 |
+
"318": "toothpaste",
|
271 |
+
"319": "tornado",
|
272 |
+
"32": "birthday cake",
|
273 |
+
"320": "tractor",
|
274 |
+
"321": "traffic light",
|
275 |
+
"322": "train",
|
276 |
+
"323": "tree",
|
277 |
+
"324": "triangle",
|
278 |
+
"325": "trombone",
|
279 |
+
"326": "truck",
|
280 |
+
"327": "trumpet",
|
281 |
+
"328": "umbrella",
|
282 |
+
"329": "underwear",
|
283 |
+
"33": "blackberry",
|
284 |
+
"330": "van",
|
285 |
+
"331": "vase",
|
286 |
+
"332": "violin",
|
287 |
+
"333": "washing machine",
|
288 |
+
"334": "watermelon",
|
289 |
+
"335": "waterslide",
|
290 |
+
"336": "whale",
|
291 |
+
"337": "wheel",
|
292 |
+
"338": "windmill",
|
293 |
+
"339": "wine bottle",
|
294 |
+
"34": "blueberry",
|
295 |
+
"340": "wine glass",
|
296 |
+
"341": "wristwatch",
|
297 |
+
"342": "yoga",
|
298 |
+
"343": "zebra",
|
299 |
+
"344": "zigzag",
|
300 |
+
"35": "book",
|
301 |
+
"36": "boomerang",
|
302 |
+
"37": "bottlecap",
|
303 |
+
"38": "bowtie",
|
304 |
+
"39": "bracelet",
|
305 |
+
"4": "angel",
|
306 |
+
"40": "brain",
|
307 |
+
"41": "bread",
|
308 |
+
"42": "bridge",
|
309 |
+
"43": "broccoli",
|
310 |
+
"44": "broom",
|
311 |
+
"45": "bucket",
|
312 |
+
"46": "bulldozer",
|
313 |
+
"47": "bus",
|
314 |
+
"48": "bush",
|
315 |
+
"49": "butterfly",
|
316 |
+
"5": "animal migration",
|
317 |
+
"50": "cactus",
|
318 |
+
"51": "cake",
|
319 |
+
"52": "calculator",
|
320 |
+
"53": "calendar",
|
321 |
+
"54": "camel",
|
322 |
+
"55": "camera",
|
323 |
+
"56": "camouflage",
|
324 |
+
"57": "campfire",
|
325 |
+
"58": "candle",
|
326 |
+
"59": "cannon",
|
327 |
+
"6": "ant",
|
328 |
+
"60": "canoe",
|
329 |
+
"61": "car",
|
330 |
+
"62": "carrot",
|
331 |
+
"63": "castle",
|
332 |
+
"64": "cat",
|
333 |
+
"65": "ceiling fan",
|
334 |
+
"66": "cell phone",
|
335 |
+
"67": "cello",
|
336 |
+
"68": "chair",
|
337 |
+
"69": "chandelier",
|
338 |
+
"7": "anvil",
|
339 |
+
"70": "church",
|
340 |
+
"71": "circle",
|
341 |
+
"72": "clarinet",
|
342 |
+
"73": "clock",
|
343 |
+
"74": "cloud",
|
344 |
+
"75": "coffee cup",
|
345 |
+
"76": "compass",
|
346 |
+
"77": "computer",
|
347 |
+
"78": "cookie",
|
348 |
+
"79": "cooler",
|
349 |
+
"8": "apple",
|
350 |
+
"80": "couch",
|
351 |
+
"81": "cow",
|
352 |
+
"82": "crab",
|
353 |
+
"83": "crayon",
|
354 |
+
"84": "crocodile",
|
355 |
+
"85": "crown",
|
356 |
+
"86": "cruise ship",
|
357 |
+
"87": "cup",
|
358 |
+
"88": "diamond",
|
359 |
+
"89": "dishwasher",
|
360 |
+
"9": "arm",
|
361 |
+
"90": "diving board",
|
362 |
+
"91": "dog",
|
363 |
+
"92": "dolphin",
|
364 |
+
"93": "donut",
|
365 |
+
"94": "door",
|
366 |
+
"95": "dragon",
|
367 |
+
"96": "dresser",
|
368 |
+
"97": "drill",
|
369 |
+
"98": "drums",
|
370 |
+
"99": "duck"
|
371 |
+
},
|
372 |
+
"image_size": 64,
|
373 |
+
"initializer_range": 0.02,
|
374 |
+
"label2id": {
|
375 |
+
"The Eiffel Tower": "309",
|
376 |
+
"The Great Wall of China": "310",
|
377 |
+
"The Mona Lisa": "311",
|
378 |
+
"aircraft carrier": "0",
|
379 |
+
"airplane": "1",
|
380 |
+
"alarm clock": "2",
|
381 |
+
"ambulance": "3",
|
382 |
+
"angel": "4",
|
383 |
+
"animal migration": "5",
|
384 |
+
"ant": "6",
|
385 |
+
"anvil": "7",
|
386 |
+
"apple": "8",
|
387 |
+
"arm": "9",
|
388 |
+
"asparagus": "10",
|
389 |
+
"axe": "11",
|
390 |
+
"backpack": "12",
|
391 |
+
"banana": "13",
|
392 |
+
"bandage": "14",
|
393 |
+
"barn": "15",
|
394 |
+
"baseball": "17",
|
395 |
+
"baseball bat": "16",
|
396 |
+
"basket": "18",
|
397 |
+
"basketball": "19",
|
398 |
+
"bat": "20",
|
399 |
+
"bathtub": "21",
|
400 |
+
"beach": "22",
|
401 |
+
"bear": "23",
|
402 |
+
"beard": "24",
|
403 |
+
"bed": "25",
|
404 |
+
"bee": "26",
|
405 |
+
"belt": "27",
|
406 |
+
"bench": "28",
|
407 |
+
"bicycle": "29",
|
408 |
+
"binoculars": "30",
|
409 |
+
"bird": "31",
|
410 |
+
"birthday cake": "32",
|
411 |
+
"blackberry": "33",
|
412 |
+
"blueberry": "34",
|
413 |
+
"book": "35",
|
414 |
+
"boomerang": "36",
|
415 |
+
"bottlecap": "37",
|
416 |
+
"bowtie": "38",
|
417 |
+
"bracelet": "39",
|
418 |
+
"brain": "40",
|
419 |
+
"bread": "41",
|
420 |
+
"bridge": "42",
|
421 |
+
"broccoli": "43",
|
422 |
+
"broom": "44",
|
423 |
+
"bucket": "45",
|
424 |
+
"bulldozer": "46",
|
425 |
+
"bus": "47",
|
426 |
+
"bush": "48",
|
427 |
+
"butterfly": "49",
|
428 |
+
"cactus": "50",
|
429 |
+
"cake": "51",
|
430 |
+
"calculator": "52",
|
431 |
+
"calendar": "53",
|
432 |
+
"camel": "54",
|
433 |
+
"camera": "55",
|
434 |
+
"camouflage": "56",
|
435 |
+
"campfire": "57",
|
436 |
+
"candle": "58",
|
437 |
+
"cannon": "59",
|
438 |
+
"canoe": "60",
|
439 |
+
"car": "61",
|
440 |
+
"carrot": "62",
|
441 |
+
"castle": "63",
|
442 |
+
"cat": "64",
|
443 |
+
"ceiling fan": "65",
|
444 |
+
"cell phone": "66",
|
445 |
+
"cello": "67",
|
446 |
+
"chair": "68",
|
447 |
+
"chandelier": "69",
|
448 |
+
"church": "70",
|
449 |
+
"circle": "71",
|
450 |
+
"clarinet": "72",
|
451 |
+
"clock": "73",
|
452 |
+
"cloud": "74",
|
453 |
+
"coffee cup": "75",
|
454 |
+
"compass": "76",
|
455 |
+
"computer": "77",
|
456 |
+
"cookie": "78",
|
457 |
+
"cooler": "79",
|
458 |
+
"couch": "80",
|
459 |
+
"cow": "81",
|
460 |
+
"crab": "82",
|
461 |
+
"crayon": "83",
|
462 |
+
"crocodile": "84",
|
463 |
+
"crown": "85",
|
464 |
+
"cruise ship": "86",
|
465 |
+
"cup": "87",
|
466 |
+
"diamond": "88",
|
467 |
+
"dishwasher": "89",
|
468 |
+
"diving board": "90",
|
469 |
+
"dog": "91",
|
470 |
+
"dolphin": "92",
|
471 |
+
"donut": "93",
|
472 |
+
"door": "94",
|
473 |
+
"dragon": "95",
|
474 |
+
"dresser": "96",
|
475 |
+
"drill": "97",
|
476 |
+
"drums": "98",
|
477 |
+
"duck": "99",
|
478 |
+
"dumbbell": "100",
|
479 |
+
"ear": "101",
|
480 |
+
"elbow": "102",
|
481 |
+
"elephant": "103",
|
482 |
+
"envelope": "104",
|
483 |
+
"eraser": "105",
|
484 |
+
"eye": "106",
|
485 |
+
"eyeglasses": "107",
|
486 |
+
"face": "108",
|
487 |
+
"fan": "109",
|
488 |
+
"feather": "110",
|
489 |
+
"fence": "111",
|
490 |
+
"finger": "112",
|
491 |
+
"fire hydrant": "113",
|
492 |
+
"fireplace": "114",
|
493 |
+
"firetruck": "115",
|
494 |
+
"fish": "116",
|
495 |
+
"flamingo": "117",
|
496 |
+
"flashlight": "118",
|
497 |
+
"flip flops": "119",
|
498 |
+
"floor lamp": "120",
|
499 |
+
"flower": "121",
|
500 |
+
"flying saucer": "122",
|
501 |
+
"foot": "123",
|
502 |
+
"fork": "124",
|
503 |
+
"frog": "125",
|
504 |
+
"frying pan": "126",
|
505 |
+
"garden": "128",
|
506 |
+
"garden hose": "127",
|
507 |
+
"giraffe": "129",
|
508 |
+
"goatee": "130",
|
509 |
+
"golf club": "131",
|
510 |
+
"grapes": "132",
|
511 |
+
"grass": "133",
|
512 |
+
"guitar": "134",
|
513 |
+
"hamburger": "135",
|
514 |
+
"hammer": "136",
|
515 |
+
"hand": "137",
|
516 |
+
"harp": "138",
|
517 |
+
"hat": "139",
|
518 |
+
"headphones": "140",
|
519 |
+
"hedgehog": "141",
|
520 |
+
"helicopter": "142",
|
521 |
+
"helmet": "143",
|
522 |
+
"hexagon": "144",
|
523 |
+
"hockey puck": "145",
|
524 |
+
"hockey stick": "146",
|
525 |
+
"horse": "147",
|
526 |
+
"hospital": "148",
|
527 |
+
"hot air balloon": "149",
|
528 |
+
"hot dog": "150",
|
529 |
+
"hot tub": "151",
|
530 |
+
"hourglass": "152",
|
531 |
+
"house": "154",
|
532 |
+
"house plant": "153",
|
533 |
+
"hurricane": "155",
|
534 |
+
"ice cream": "156",
|
535 |
+
"jacket": "157",
|
536 |
+
"jail": "158",
|
537 |
+
"kangaroo": "159",
|
538 |
+
"key": "160",
|
539 |
+
"keyboard": "161",
|
540 |
+
"knee": "162",
|
541 |
+
"knife": "163",
|
542 |
+
"ladder": "164",
|
543 |
+
"lantern": "165",
|
544 |
+
"laptop": "166",
|
545 |
+
"leaf": "167",
|
546 |
+
"leg": "168",
|
547 |
+
"light bulb": "169",
|
548 |
+
"lighter": "170",
|
549 |
+
"lighthouse": "171",
|
550 |
+
"lightning": "172",
|
551 |
+
"line": "173",
|
552 |
+
"lion": "174",
|
553 |
+
"lipstick": "175",
|
554 |
+
"lobster": "176",
|
555 |
+
"lollipop": "177",
|
556 |
+
"mailbox": "178",
|
557 |
+
"map": "179",
|
558 |
+
"marker": "180",
|
559 |
+
"matches": "181",
|
560 |
+
"megaphone": "182",
|
561 |
+
"mermaid": "183",
|
562 |
+
"microphone": "184",
|
563 |
+
"microwave": "185",
|
564 |
+
"monkey": "186",
|
565 |
+
"moon": "187",
|
566 |
+
"mosquito": "188",
|
567 |
+
"motorbike": "189",
|
568 |
+
"mountain": "190",
|
569 |
+
"mouse": "191",
|
570 |
+
"moustache": "192",
|
571 |
+
"mouth": "193",
|
572 |
+
"mug": "194",
|
573 |
+
"mushroom": "195",
|
574 |
+
"nail": "196",
|
575 |
+
"necklace": "197",
|
576 |
+
"nose": "198",
|
577 |
+
"ocean": "199",
|
578 |
+
"octagon": "200",
|
579 |
+
"octopus": "201",
|
580 |
+
"onion": "202",
|
581 |
+
"oven": "203",
|
582 |
+
"owl": "204",
|
583 |
+
"paint can": "205",
|
584 |
+
"paintbrush": "206",
|
585 |
+
"palm tree": "207",
|
586 |
+
"panda": "208",
|
587 |
+
"pants": "209",
|
588 |
+
"paper clip": "210",
|
589 |
+
"parachute": "211",
|
590 |
+
"parrot": "212",
|
591 |
+
"passport": "213",
|
592 |
+
"peanut": "214",
|
593 |
+
"pear": "215",
|
594 |
+
"peas": "216",
|
595 |
+
"pencil": "217",
|
596 |
+
"penguin": "218",
|
597 |
+
"piano": "219",
|
598 |
+
"pickup truck": "220",
|
599 |
+
"picture frame": "221",
|
600 |
+
"pig": "222",
|
601 |
+
"pillow": "223",
|
602 |
+
"pineapple": "224",
|
603 |
+
"pizza": "225",
|
604 |
+
"pliers": "226",
|
605 |
+
"police car": "227",
|
606 |
+
"pond": "228",
|
607 |
+
"pool": "229",
|
608 |
+
"popsicle": "230",
|
609 |
+
"postcard": "231",
|
610 |
+
"potato": "232",
|
611 |
+
"power outlet": "233",
|
612 |
+
"purse": "234",
|
613 |
+
"rabbit": "235",
|
614 |
+
"raccoon": "236",
|
615 |
+
"radio": "237",
|
616 |
+
"rain": "238",
|
617 |
+
"rainbow": "239",
|
618 |
+
"rake": "240",
|
619 |
+
"remote control": "241",
|
620 |
+
"rhinoceros": "242",
|
621 |
+
"rifle": "243",
|
622 |
+
"river": "244",
|
623 |
+
"roller coaster": "245",
|
624 |
+
"rollerskates": "246",
|
625 |
+
"sailboat": "247",
|
626 |
+
"sandwich": "248",
|
627 |
+
"saw": "249",
|
628 |
+
"saxophone": "250",
|
629 |
+
"school bus": "251",
|
630 |
+
"scissors": "252",
|
631 |
+
"scorpion": "253",
|
632 |
+
"screwdriver": "254",
|
633 |
+
"sea turtle": "255",
|
634 |
+
"see saw": "256",
|
635 |
+
"shark": "257",
|
636 |
+
"sheep": "258",
|
637 |
+
"shoe": "259",
|
638 |
+
"shorts": "260",
|
639 |
+
"shovel": "261",
|
640 |
+
"sink": "262",
|
641 |
+
"skateboard": "263",
|
642 |
+
"skull": "264",
|
643 |
+
"skyscraper": "265",
|
644 |
+
"sleeping bag": "266",
|
645 |
+
"smiley face": "267",
|
646 |
+
"snail": "268",
|
647 |
+
"snake": "269",
|
648 |
+
"snorkel": "270",
|
649 |
+
"snowflake": "271",
|
650 |
+
"snowman": "272",
|
651 |
+
"soccer ball": "273",
|
652 |
+
"sock": "274",
|
653 |
+
"speedboat": "275",
|
654 |
+
"spider": "276",
|
655 |
+
"spoon": "277",
|
656 |
+
"spreadsheet": "278",
|
657 |
+
"square": "279",
|
658 |
+
"squiggle": "280",
|
659 |
+
"squirrel": "281",
|
660 |
+
"stairs": "282",
|
661 |
+
"star": "283",
|
662 |
+
"steak": "284",
|
663 |
+
"stereo": "285",
|
664 |
+
"stethoscope": "286",
|
665 |
+
"stitches": "287",
|
666 |
+
"stop sign": "288",
|
667 |
+
"stove": "289",
|
668 |
+
"strawberry": "290",
|
669 |
+
"streetlight": "291",
|
670 |
+
"string bean": "292",
|
671 |
+
"submarine": "293",
|
672 |
+
"suitcase": "294",
|
673 |
+
"sun": "295",
|
674 |
+
"swan": "296",
|
675 |
+
"sweater": "297",
|
676 |
+
"swing set": "298",
|
677 |
+
"sword": "299",
|
678 |
+
"syringe": "300",
|
679 |
+
"t-shirt": "301",
|
680 |
+
"table": "302",
|
681 |
+
"teapot": "303",
|
682 |
+
"teddy-bear": "304",
|
683 |
+
"telephone": "305",
|
684 |
+
"television": "306",
|
685 |
+
"tennis racquet": "307",
|
686 |
+
"tent": "308",
|
687 |
+
"tiger": "312",
|
688 |
+
"toaster": "313",
|
689 |
+
"toe": "314",
|
690 |
+
"toilet": "315",
|
691 |
+
"tooth": "316",
|
692 |
+
"toothbrush": "317",
|
693 |
+
"toothpaste": "318",
|
694 |
+
"tornado": "319",
|
695 |
+
"tractor": "320",
|
696 |
+
"traffic light": "321",
|
697 |
+
"train": "322",
|
698 |
+
"tree": "323",
|
699 |
+
"triangle": "324",
|
700 |
+
"trombone": "325",
|
701 |
+
"truck": "326",
|
702 |
+
"trumpet": "327",
|
703 |
+
"umbrella": "328",
|
704 |
+
"underwear": "329",
|
705 |
+
"van": "330",
|
706 |
+
"vase": "331",
|
707 |
+
"violin": "332",
|
708 |
+
"washing machine": "333",
|
709 |
+
"watermelon": "334",
|
710 |
+
"waterslide": "335",
|
711 |
+
"whale": "336",
|
712 |
+
"wheel": "337",
|
713 |
+
"windmill": "338",
|
714 |
+
"wine bottle": "339",
|
715 |
+
"wine glass": "340",
|
716 |
+
"wristwatch": "341",
|
717 |
+
"yoga": "342",
|
718 |
+
"zebra": "343",
|
719 |
+
"zigzag": "344"
|
720 |
+
},
|
721 |
+
"layer_norm_eps": 1e-05,
|
722 |
+
"mlp_ratio": 2.0,
|
723 |
+
"model_type": "mobilevitv2",
|
724 |
+
"n_attn_blocks": [
|
725 |
+
2,
|
726 |
+
4,
|
727 |
+
3
|
728 |
+
],
|
729 |
+
"num_channels": 1,
|
730 |
+
"output_stride": 32,
|
731 |
+
"patch_size": 2,
|
732 |
+
"problem_type": "single_label_classification",
|
733 |
+
"semantic_loss_ignore_index": 255,
|
734 |
+
"torch_dtype": "float32",
|
735 |
+
"transformers_version": "4.40.0",
|
736 |
+
"width_multiplier": 1.0
|
737 |
+
}
|
model.safetensors
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:28184813e695da9074eb277c8000be311e12d53352ec1ed2b6b268532b81b323
|
3 |
+
size 18360744
|
preprocessor_config.json
ADDED
@@ -0,0 +1,32 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"_valid_processor_keys": [
|
3 |
+
"images",
|
4 |
+
"segmentation_maps",
|
5 |
+
"do_resize",
|
6 |
+
"size",
|
7 |
+
"resample",
|
8 |
+
"do_rescale",
|
9 |
+
"rescale_factor",
|
10 |
+
"do_center_crop",
|
11 |
+
"crop_size",
|
12 |
+
"do_flip_channel_order",
|
13 |
+
"return_tensors",
|
14 |
+
"data_format",
|
15 |
+
"input_data_format"
|
16 |
+
],
|
17 |
+
"crop_size": {
|
18 |
+
"height": 56,
|
19 |
+
"width": 56
|
20 |
+
},
|
21 |
+
"do_center_crop": true,
|
22 |
+
"do_convert_rgb": false,
|
23 |
+
"do_flip_channel_order": false,
|
24 |
+
"do_rescale": true,
|
25 |
+
"do_resize": true,
|
26 |
+
"image_processor_type": "MobileViTImageProcessor",
|
27 |
+
"resample": 2,
|
28 |
+
"rescale_factor": 0.00392156862745098,
|
29 |
+
"size": {
|
30 |
+
"shortest_edge": 56
|
31 |
+
}
|
32 |
+
}
|
test_results.json
ADDED
@@ -0,0 +1,8 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"epoch": 5.0,
|
3 |
+
"eval_accuracy": 0.774412,
|
4 |
+
"eval_loss": 0.8919877409934998,
|
5 |
+
"eval_runtime": 138.4801,
|
6 |
+
"eval_samples_per_second": 1805.314,
|
7 |
+
"eval_steps_per_second": 7.055
|
8 |
+
}
|
train_results.json
ADDED
@@ -0,0 +1,8 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"epoch": 5.0,
|
3 |
+
"total_flos": 1.93274424e+18,
|
4 |
+
"train_loss": 0.9357909288237652,
|
5 |
+
"train_runtime": 45635.435,
|
6 |
+
"train_samples_per_second": 493.038,
|
7 |
+
"train_steps_per_second": 1.926
|
8 |
+
}
|
trainer_state.json
ADDED
@@ -0,0 +1,792 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"best_metric": null,
|
3 |
+
"best_model_checkpoint": null,
|
4 |
+
"epoch": 5.0,
|
5 |
+
"eval_steps": 5000,
|
6 |
+
"global_step": 87895,
|
7 |
+
"is_hyper_param_search": false,
|
8 |
+
"is_local_process_zero": true,
|
9 |
+
"is_world_process_zero": true,
|
10 |
+
"log_history": [
|
11 |
+
{
|
12 |
+
"epoch": 0.05688605722737357,
|
13 |
+
"grad_norm": 2.4062280654907227,
|
14 |
+
"learning_rate": 0.0007908982308436202,
|
15 |
+
"loss": 2.1918,
|
16 |
+
"step": 1000
|
17 |
+
},
|
18 |
+
{
|
19 |
+
"epoch": 0.11377211445474714,
|
20 |
+
"grad_norm": 1.431848406791687,
|
21 |
+
"learning_rate": 0.0007817964616872405,
|
22 |
+
"loss": 1.4818,
|
23 |
+
"step": 2000
|
24 |
+
},
|
25 |
+
{
|
26 |
+
"epoch": 0.17065817168212072,
|
27 |
+
"grad_norm": 1.5747077465057373,
|
28 |
+
"learning_rate": 0.0007726946925308607,
|
29 |
+
"loss": 1.3634,
|
30 |
+
"step": 3000
|
31 |
+
},
|
32 |
+
{
|
33 |
+
"epoch": 0.22754422890949427,
|
34 |
+
"grad_norm": 1.4864206314086914,
|
35 |
+
"learning_rate": 0.0007635929233744809,
|
36 |
+
"loss": 1.2967,
|
37 |
+
"step": 4000
|
38 |
+
},
|
39 |
+
{
|
40 |
+
"epoch": 0.2844302861368678,
|
41 |
+
"grad_norm": 1.2000905275344849,
|
42 |
+
"learning_rate": 0.0007544911542181011,
|
43 |
+
"loss": 1.2574,
|
44 |
+
"step": 5000
|
45 |
+
},
|
46 |
+
{
|
47 |
+
"epoch": 0.2844302861368678,
|
48 |
+
"eval_accuracy": 0.689128,
|
49 |
+
"eval_loss": 1.238457202911377,
|
50 |
+
"eval_runtime": 203.0197,
|
51 |
+
"eval_samples_per_second": 1231.407,
|
52 |
+
"eval_steps_per_second": 4.812,
|
53 |
+
"step": 5000
|
54 |
+
},
|
55 |
+
{
|
56 |
+
"epoch": 0.34131634336424144,
|
57 |
+
"grad_norm": 1.2910780906677246,
|
58 |
+
"learning_rate": 0.0007453893850617214,
|
59 |
+
"loss": 1.2181,
|
60 |
+
"step": 6000
|
61 |
+
},
|
62 |
+
{
|
63 |
+
"epoch": 0.398202400591615,
|
64 |
+
"grad_norm": 1.1383774280548096,
|
65 |
+
"learning_rate": 0.0007362876159053416,
|
66 |
+
"loss": 1.1863,
|
67 |
+
"step": 7000
|
68 |
+
},
|
69 |
+
{
|
70 |
+
"epoch": 0.45508845781898855,
|
71 |
+
"grad_norm": 1.135689616203308,
|
72 |
+
"learning_rate": 0.0007271858467489618,
|
73 |
+
"loss": 1.1653,
|
74 |
+
"step": 8000
|
75 |
+
},
|
76 |
+
{
|
77 |
+
"epoch": 0.5119745150463622,
|
78 |
+
"grad_norm": 1.1965036392211914,
|
79 |
+
"learning_rate": 0.0007180840775925821,
|
80 |
+
"loss": 1.147,
|
81 |
+
"step": 9000
|
82 |
+
},
|
83 |
+
{
|
84 |
+
"epoch": 0.5688605722737357,
|
85 |
+
"grad_norm": 1.0561026334762573,
|
86 |
+
"learning_rate": 0.0007089823084362024,
|
87 |
+
"loss": 1.1281,
|
88 |
+
"step": 10000
|
89 |
+
},
|
90 |
+
{
|
91 |
+
"epoch": 0.5688605722737357,
|
92 |
+
"eval_accuracy": 0.715764,
|
93 |
+
"eval_loss": 1.1192152500152588,
|
94 |
+
"eval_runtime": 128.8781,
|
95 |
+
"eval_samples_per_second": 1939.817,
|
96 |
+
"eval_steps_per_second": 7.581,
|
97 |
+
"step": 10000
|
98 |
+
},
|
99 |
+
{
|
100 |
+
"epoch": 0.6257466295011093,
|
101 |
+
"grad_norm": 0.9711835980415344,
|
102 |
+
"learning_rate": 0.0006998805392798226,
|
103 |
+
"loss": 1.1232,
|
104 |
+
"step": 11000
|
105 |
+
},
|
106 |
+
{
|
107 |
+
"epoch": 0.6826326867284829,
|
108 |
+
"grad_norm": 0.8913602828979492,
|
109 |
+
"learning_rate": 0.0006907787701234428,
|
110 |
+
"loss": 1.0988,
|
111 |
+
"step": 12000
|
112 |
+
},
|
113 |
+
{
|
114 |
+
"epoch": 0.7395187439558564,
|
115 |
+
"grad_norm": 1.092698097229004,
|
116 |
+
"learning_rate": 0.000681677000967063,
|
117 |
+
"loss": 1.0897,
|
118 |
+
"step": 13000
|
119 |
+
},
|
120 |
+
{
|
121 |
+
"epoch": 0.79640480118323,
|
122 |
+
"grad_norm": 0.9319038391113281,
|
123 |
+
"learning_rate": 0.0006725752318106833,
|
124 |
+
"loss": 1.0826,
|
125 |
+
"step": 14000
|
126 |
+
},
|
127 |
+
{
|
128 |
+
"epoch": 0.8532908584106036,
|
129 |
+
"grad_norm": 1.0223675966262817,
|
130 |
+
"learning_rate": 0.0006634734626543035,
|
131 |
+
"loss": 1.0698,
|
132 |
+
"step": 15000
|
133 |
+
},
|
134 |
+
{
|
135 |
+
"epoch": 0.8532908584106036,
|
136 |
+
"eval_accuracy": 0.728676,
|
137 |
+
"eval_loss": 1.0653605461120605,
|
138 |
+
"eval_runtime": 128.0826,
|
139 |
+
"eval_samples_per_second": 1951.866,
|
140 |
+
"eval_steps_per_second": 7.628,
|
141 |
+
"step": 15000
|
142 |
+
},
|
143 |
+
{
|
144 |
+
"epoch": 0.9101769156379771,
|
145 |
+
"grad_norm": 0.8995338678359985,
|
146 |
+
"learning_rate": 0.0006543716934979237,
|
147 |
+
"loss": 1.0624,
|
148 |
+
"step": 16000
|
149 |
+
},
|
150 |
+
{
|
151 |
+
"epoch": 0.9670629728653507,
|
152 |
+
"grad_norm": 0.8418471217155457,
|
153 |
+
"learning_rate": 0.0006452699243415439,
|
154 |
+
"loss": 1.0538,
|
155 |
+
"step": 17000
|
156 |
+
},
|
157 |
+
{
|
158 |
+
"epoch": 1.0239490300927243,
|
159 |
+
"grad_norm": 1.024624228477478,
|
160 |
+
"learning_rate": 0.0006361681551851641,
|
161 |
+
"loss": 1.0311,
|
162 |
+
"step": 18000
|
163 |
+
},
|
164 |
+
{
|
165 |
+
"epoch": 1.0808350873200978,
|
166 |
+
"grad_norm": 0.9130891561508179,
|
167 |
+
"learning_rate": 0.0006270663860287844,
|
168 |
+
"loss": 0.999,
|
169 |
+
"step": 19000
|
170 |
+
},
|
171 |
+
{
|
172 |
+
"epoch": 1.1377211445474713,
|
173 |
+
"grad_norm": 0.8896342515945435,
|
174 |
+
"learning_rate": 0.0006179646168724045,
|
175 |
+
"loss": 1.0,
|
176 |
+
"step": 20000
|
177 |
+
},
|
178 |
+
{
|
179 |
+
"epoch": 1.1377211445474713,
|
180 |
+
"eval_accuracy": 0.739712,
|
181 |
+
"eval_loss": 1.0235533714294434,
|
182 |
+
"eval_runtime": 127.2585,
|
183 |
+
"eval_samples_per_second": 1964.505,
|
184 |
+
"eval_steps_per_second": 7.677,
|
185 |
+
"step": 20000
|
186 |
+
},
|
187 |
+
{
|
188 |
+
"epoch": 1.194607201774845,
|
189 |
+
"grad_norm": 0.7940112948417664,
|
190 |
+
"learning_rate": 0.0006088628477160248,
|
191 |
+
"loss": 0.9957,
|
192 |
+
"step": 21000
|
193 |
+
},
|
194 |
+
{
|
195 |
+
"epoch": 1.2514932590022185,
|
196 |
+
"grad_norm": 0.9015308618545532,
|
197 |
+
"learning_rate": 0.000599761078559645,
|
198 |
+
"loss": 0.9967,
|
199 |
+
"step": 22000
|
200 |
+
},
|
201 |
+
{
|
202 |
+
"epoch": 1.3083793162295922,
|
203 |
+
"grad_norm": 0.9106078147888184,
|
204 |
+
"learning_rate": 0.0005906593094032653,
|
205 |
+
"loss": 0.9939,
|
206 |
+
"step": 23000
|
207 |
+
},
|
208 |
+
{
|
209 |
+
"epoch": 1.3652653734569657,
|
210 |
+
"grad_norm": 0.9563422203063965,
|
211 |
+
"learning_rate": 0.0005815575402468854,
|
212 |
+
"loss": 0.9931,
|
213 |
+
"step": 24000
|
214 |
+
},
|
215 |
+
{
|
216 |
+
"epoch": 1.4221514306843392,
|
217 |
+
"grad_norm": 0.7646272778511047,
|
218 |
+
"learning_rate": 0.0005724557710905057,
|
219 |
+
"loss": 0.9774,
|
220 |
+
"step": 25000
|
221 |
+
},
|
222 |
+
{
|
223 |
+
"epoch": 1.4221514306843392,
|
224 |
+
"eval_accuracy": 0.743348,
|
225 |
+
"eval_loss": 1.0054922103881836,
|
226 |
+
"eval_runtime": 127.7729,
|
227 |
+
"eval_samples_per_second": 1956.596,
|
228 |
+
"eval_steps_per_second": 7.646,
|
229 |
+
"step": 25000
|
230 |
+
},
|
231 |
+
{
|
232 |
+
"epoch": 1.4790374879117127,
|
233 |
+
"grad_norm": 0.7779045104980469,
|
234 |
+
"learning_rate": 0.000563354001934126,
|
235 |
+
"loss": 0.9792,
|
236 |
+
"step": 26000
|
237 |
+
},
|
238 |
+
{
|
239 |
+
"epoch": 1.5359235451390862,
|
240 |
+
"grad_norm": 0.8506484627723694,
|
241 |
+
"learning_rate": 0.0005542522327777463,
|
242 |
+
"loss": 0.9778,
|
243 |
+
"step": 27000
|
244 |
+
},
|
245 |
+
{
|
246 |
+
"epoch": 1.59280960236646,
|
247 |
+
"grad_norm": 0.8443676829338074,
|
248 |
+
"learning_rate": 0.0005451504636213664,
|
249 |
+
"loss": 0.9715,
|
250 |
+
"step": 28000
|
251 |
+
},
|
252 |
+
{
|
253 |
+
"epoch": 1.6496956595938337,
|
254 |
+
"grad_norm": 0.9333568215370178,
|
255 |
+
"learning_rate": 0.0005360486944649867,
|
256 |
+
"loss": 0.9679,
|
257 |
+
"step": 29000
|
258 |
+
},
|
259 |
+
{
|
260 |
+
"epoch": 1.7065817168212072,
|
261 |
+
"grad_norm": 0.9501623511314392,
|
262 |
+
"learning_rate": 0.0005269469253086069,
|
263 |
+
"loss": 0.9684,
|
264 |
+
"step": 30000
|
265 |
+
},
|
266 |
+
{
|
267 |
+
"epoch": 1.7065817168212072,
|
268 |
+
"eval_accuracy": 0.749276,
|
269 |
+
"eval_loss": 0.9812818765640259,
|
270 |
+
"eval_runtime": 128.5758,
|
271 |
+
"eval_samples_per_second": 1944.379,
|
272 |
+
"eval_steps_per_second": 7.599,
|
273 |
+
"step": 30000
|
274 |
+
},
|
275 |
+
{
|
276 |
+
"epoch": 1.7634677740485807,
|
277 |
+
"grad_norm": 0.7442188262939453,
|
278 |
+
"learning_rate": 0.0005178451561522272,
|
279 |
+
"loss": 0.9636,
|
280 |
+
"step": 31000
|
281 |
+
},
|
282 |
+
{
|
283 |
+
"epoch": 1.8203538312759542,
|
284 |
+
"grad_norm": 0.7510819435119629,
|
285 |
+
"learning_rate": 0.0005087433869958473,
|
286 |
+
"loss": 0.9647,
|
287 |
+
"step": 32000
|
288 |
+
},
|
289 |
+
{
|
290 |
+
"epoch": 1.8772398885033277,
|
291 |
+
"grad_norm": 0.7448764443397522,
|
292 |
+
"learning_rate": 0.0004996416178394676,
|
293 |
+
"loss": 0.9591,
|
294 |
+
"step": 33000
|
295 |
+
},
|
296 |
+
{
|
297 |
+
"epoch": 1.9341259457307014,
|
298 |
+
"grad_norm": 0.8019358515739441,
|
299 |
+
"learning_rate": 0.0004905398486830878,
|
300 |
+
"loss": 0.9513,
|
301 |
+
"step": 34000
|
302 |
+
},
|
303 |
+
{
|
304 |
+
"epoch": 1.9910120029580751,
|
305 |
+
"grad_norm": 0.9495121240615845,
|
306 |
+
"learning_rate": 0.00048143807952670797,
|
307 |
+
"loss": 0.9511,
|
308 |
+
"step": 35000
|
309 |
+
},
|
310 |
+
{
|
311 |
+
"epoch": 1.9910120029580751,
|
312 |
+
"eval_accuracy": 0.755448,
|
313 |
+
"eval_loss": 0.9558805227279663,
|
314 |
+
"eval_runtime": 127.8711,
|
315 |
+
"eval_samples_per_second": 1955.094,
|
316 |
+
"eval_steps_per_second": 7.641,
|
317 |
+
"step": 35000
|
318 |
+
},
|
319 |
+
{
|
320 |
+
"epoch": 2.0478980601854486,
|
321 |
+
"grad_norm": 0.8410281538963318,
|
322 |
+
"learning_rate": 0.00047233631037032825,
|
323 |
+
"loss": 0.9081,
|
324 |
+
"step": 36000
|
325 |
+
},
|
326 |
+
{
|
327 |
+
"epoch": 2.104784117412822,
|
328 |
+
"grad_norm": 0.8246123194694519,
|
329 |
+
"learning_rate": 0.00046323454121394847,
|
330 |
+
"loss": 0.8964,
|
331 |
+
"step": 37000
|
332 |
+
},
|
333 |
+
{
|
334 |
+
"epoch": 2.1616701746401956,
|
335 |
+
"grad_norm": 0.9567108154296875,
|
336 |
+
"learning_rate": 0.0004541327720575687,
|
337 |
+
"loss": 0.8952,
|
338 |
+
"step": 38000
|
339 |
+
},
|
340 |
+
{
|
341 |
+
"epoch": 2.218556231867569,
|
342 |
+
"grad_norm": 0.8104901313781738,
|
343 |
+
"learning_rate": 0.0004450310029011889,
|
344 |
+
"loss": 0.8925,
|
345 |
+
"step": 39000
|
346 |
+
},
|
347 |
+
{
|
348 |
+
"epoch": 2.2754422890949426,
|
349 |
+
"grad_norm": 0.9034276008605957,
|
350 |
+
"learning_rate": 0.0004359292337448092,
|
351 |
+
"loss": 0.8998,
|
352 |
+
"step": 40000
|
353 |
+
},
|
354 |
+
{
|
355 |
+
"epoch": 2.2754422890949426,
|
356 |
+
"eval_accuracy": 0.755948,
|
357 |
+
"eval_loss": 0.9492226839065552,
|
358 |
+
"eval_runtime": 127.8812,
|
359 |
+
"eval_samples_per_second": 1954.94,
|
360 |
+
"eval_steps_per_second": 7.64,
|
361 |
+
"step": 40000
|
362 |
+
},
|
363 |
+
{
|
364 |
+
"epoch": 2.3323283463223166,
|
365 |
+
"grad_norm": 1.3229442834854126,
|
366 |
+
"learning_rate": 0.00042682746458842937,
|
367 |
+
"loss": 0.8962,
|
368 |
+
"step": 41000
|
369 |
+
},
|
370 |
+
{
|
371 |
+
"epoch": 2.38921440354969,
|
372 |
+
"grad_norm": 0.8582925200462341,
|
373 |
+
"learning_rate": 0.00041772569543204965,
|
374 |
+
"loss": 0.8976,
|
375 |
+
"step": 42000
|
376 |
+
},
|
377 |
+
{
|
378 |
+
"epoch": 2.4461004607770636,
|
379 |
+
"grad_norm": 0.8881712555885315,
|
380 |
+
"learning_rate": 0.0004086239262756698,
|
381 |
+
"loss": 0.8898,
|
382 |
+
"step": 43000
|
383 |
+
},
|
384 |
+
{
|
385 |
+
"epoch": 2.502986518004437,
|
386 |
+
"grad_norm": 0.8713961839675903,
|
387 |
+
"learning_rate": 0.00039952215711929005,
|
388 |
+
"loss": 0.8927,
|
389 |
+
"step": 44000
|
390 |
+
},
|
391 |
+
{
|
392 |
+
"epoch": 2.5598725752318106,
|
393 |
+
"grad_norm": 0.7883007526397705,
|
394 |
+
"learning_rate": 0.00039042038796291027,
|
395 |
+
"loss": 0.8967,
|
396 |
+
"step": 45000
|
397 |
+
},
|
398 |
+
{
|
399 |
+
"epoch": 2.5598725752318106,
|
400 |
+
"eval_accuracy": 0.760028,
|
401 |
+
"eval_loss": 0.937300980091095,
|
402 |
+
"eval_runtime": 130.0782,
|
403 |
+
"eval_samples_per_second": 1921.921,
|
404 |
+
"eval_steps_per_second": 7.511,
|
405 |
+
"step": 45000
|
406 |
+
},
|
407 |
+
{
|
408 |
+
"epoch": 2.6167586324591845,
|
409 |
+
"grad_norm": 0.8600155711174011,
|
410 |
+
"learning_rate": 0.00038131861880653055,
|
411 |
+
"loss": 0.8927,
|
412 |
+
"step": 46000
|
413 |
+
},
|
414 |
+
{
|
415 |
+
"epoch": 2.673644689686558,
|
416 |
+
"grad_norm": 0.8501909971237183,
|
417 |
+
"learning_rate": 0.0003722168496501508,
|
418 |
+
"loss": 0.8913,
|
419 |
+
"step": 47000
|
420 |
+
},
|
421 |
+
{
|
422 |
+
"epoch": 2.7305307469139315,
|
423 |
+
"grad_norm": 0.8116582632064819,
|
424 |
+
"learning_rate": 0.000363115080493771,
|
425 |
+
"loss": 0.8889,
|
426 |
+
"step": 48000
|
427 |
+
},
|
428 |
+
{
|
429 |
+
"epoch": 2.787416804141305,
|
430 |
+
"grad_norm": 0.8065186738967896,
|
431 |
+
"learning_rate": 0.0003540133113373912,
|
432 |
+
"loss": 0.8896,
|
433 |
+
"step": 49000
|
434 |
+
},
|
435 |
+
{
|
436 |
+
"epoch": 2.8443028613686785,
|
437 |
+
"grad_norm": 0.9248031973838806,
|
438 |
+
"learning_rate": 0.00034491154218101145,
|
439 |
+
"loss": 0.8837,
|
440 |
+
"step": 50000
|
441 |
+
},
|
442 |
+
{
|
443 |
+
"epoch": 2.8443028613686785,
|
444 |
+
"eval_accuracy": 0.762176,
|
445 |
+
"eval_loss": 0.9251159429550171,
|
446 |
+
"eval_runtime": 128.4439,
|
447 |
+
"eval_samples_per_second": 1946.376,
|
448 |
+
"eval_steps_per_second": 7.606,
|
449 |
+
"step": 50000
|
450 |
+
},
|
451 |
+
{
|
452 |
+
"epoch": 2.901188918596052,
|
453 |
+
"grad_norm": 0.8191467523574829,
|
454 |
+
"learning_rate": 0.0003358097730246317,
|
455 |
+
"loss": 0.878,
|
456 |
+
"step": 51000
|
457 |
+
},
|
458 |
+
{
|
459 |
+
"epoch": 2.9580749758234255,
|
460 |
+
"grad_norm": 0.7620063424110413,
|
461 |
+
"learning_rate": 0.0003267080038682519,
|
462 |
+
"loss": 0.8832,
|
463 |
+
"step": 52000
|
464 |
+
},
|
465 |
+
{
|
466 |
+
"epoch": 3.0149610330507994,
|
467 |
+
"grad_norm": 0.8365482687950134,
|
468 |
+
"learning_rate": 0.0003176062347118721,
|
469 |
+
"loss": 0.8621,
|
470 |
+
"step": 53000
|
471 |
+
},
|
472 |
+
{
|
473 |
+
"epoch": 3.071847090278173,
|
474 |
+
"grad_norm": 0.9817807078361511,
|
475 |
+
"learning_rate": 0.00030850446555549235,
|
476 |
+
"loss": 0.8224,
|
477 |
+
"step": 54000
|
478 |
+
},
|
479 |
+
{
|
480 |
+
"epoch": 3.1287331475055464,
|
481 |
+
"grad_norm": 0.847806453704834,
|
482 |
+
"learning_rate": 0.00029940269639911263,
|
483 |
+
"loss": 0.8253,
|
484 |
+
"step": 55000
|
485 |
+
},
|
486 |
+
{
|
487 |
+
"epoch": 3.1287331475055464,
|
488 |
+
"eval_accuracy": 0.76438,
|
489 |
+
"eval_loss": 0.9235970973968506,
|
490 |
+
"eval_runtime": 126.2531,
|
491 |
+
"eval_samples_per_second": 1980.15,
|
492 |
+
"eval_steps_per_second": 7.738,
|
493 |
+
"step": 55000
|
494 |
+
},
|
495 |
+
{
|
496 |
+
"epoch": 3.18561920473292,
|
497 |
+
"grad_norm": 1.1729530096054077,
|
498 |
+
"learning_rate": 0.00029030092724273285,
|
499 |
+
"loss": 0.8225,
|
500 |
+
"step": 56000
|
501 |
+
},
|
502 |
+
{
|
503 |
+
"epoch": 3.2425052619602934,
|
504 |
+
"grad_norm": 1.0548408031463623,
|
505 |
+
"learning_rate": 0.0002811991580863531,
|
506 |
+
"loss": 0.821,
|
507 |
+
"step": 57000
|
508 |
+
},
|
509 |
+
{
|
510 |
+
"epoch": 3.299391319187667,
|
511 |
+
"grad_norm": 1.0199774503707886,
|
512 |
+
"learning_rate": 0.0002720973889299733,
|
513 |
+
"loss": 0.8213,
|
514 |
+
"step": 58000
|
515 |
+
},
|
516 |
+
{
|
517 |
+
"epoch": 3.356277376415041,
|
518 |
+
"grad_norm": 0.9180177450180054,
|
519 |
+
"learning_rate": 0.00026299561977359353,
|
520 |
+
"loss": 0.8274,
|
521 |
+
"step": 59000
|
522 |
+
},
|
523 |
+
{
|
524 |
+
"epoch": 3.4131634336424144,
|
525 |
+
"grad_norm": 0.9745663404464722,
|
526 |
+
"learning_rate": 0.0002538938506172137,
|
527 |
+
"loss": 0.8229,
|
528 |
+
"step": 60000
|
529 |
+
},
|
530 |
+
{
|
531 |
+
"epoch": 3.4131634336424144,
|
532 |
+
"eval_accuracy": 0.766832,
|
533 |
+
"eval_loss": 0.9138370156288147,
|
534 |
+
"eval_runtime": 129.2727,
|
535 |
+
"eval_samples_per_second": 1933.897,
|
536 |
+
"eval_steps_per_second": 7.558,
|
537 |
+
"step": 60000
|
538 |
+
},
|
539 |
+
{
|
540 |
+
"epoch": 3.470049490869788,
|
541 |
+
"grad_norm": 0.8708947896957397,
|
542 |
+
"learning_rate": 0.0002447920814608339,
|
543 |
+
"loss": 0.8256,
|
544 |
+
"step": 61000
|
545 |
+
},
|
546 |
+
{
|
547 |
+
"epoch": 3.5269355480971614,
|
548 |
+
"grad_norm": 0.9808185696601868,
|
549 |
+
"learning_rate": 0.00023569031230445418,
|
550 |
+
"loss": 0.8298,
|
551 |
+
"step": 62000
|
552 |
+
},
|
553 |
+
{
|
554 |
+
"epoch": 3.583821605324535,
|
555 |
+
"grad_norm": 0.8228833079338074,
|
556 |
+
"learning_rate": 0.0002265885431480744,
|
557 |
+
"loss": 0.827,
|
558 |
+
"step": 63000
|
559 |
+
},
|
560 |
+
{
|
561 |
+
"epoch": 3.6407076625519084,
|
562 |
+
"grad_norm": 0.9581019878387451,
|
563 |
+
"learning_rate": 0.00021748677399169463,
|
564 |
+
"loss": 0.8275,
|
565 |
+
"step": 64000
|
566 |
+
},
|
567 |
+
{
|
568 |
+
"epoch": 3.697593719779282,
|
569 |
+
"grad_norm": 0.8560314178466797,
|
570 |
+
"learning_rate": 0.00020838500483531488,
|
571 |
+
"loss": 0.8145,
|
572 |
+
"step": 65000
|
573 |
+
},
|
574 |
+
{
|
575 |
+
"epoch": 3.697593719779282,
|
576 |
+
"eval_accuracy": 0.769172,
|
577 |
+
"eval_loss": 0.9042648673057556,
|
578 |
+
"eval_runtime": 129.2138,
|
579 |
+
"eval_samples_per_second": 1934.778,
|
580 |
+
"eval_steps_per_second": 7.561,
|
581 |
+
"step": 65000
|
582 |
+
},
|
583 |
+
{
|
584 |
+
"epoch": 3.754479777006656,
|
585 |
+
"grad_norm": 0.8918451070785522,
|
586 |
+
"learning_rate": 0.0001992832356789351,
|
587 |
+
"loss": 0.819,
|
588 |
+
"step": 66000
|
589 |
+
},
|
590 |
+
{
|
591 |
+
"epoch": 3.8113658342340293,
|
592 |
+
"grad_norm": 1.0977294445037842,
|
593 |
+
"learning_rate": 0.00019018146652255533,
|
594 |
+
"loss": 0.8122,
|
595 |
+
"step": 67000
|
596 |
+
},
|
597 |
+
{
|
598 |
+
"epoch": 3.868251891461403,
|
599 |
+
"grad_norm": 0.7856444716453552,
|
600 |
+
"learning_rate": 0.00018107969736617555,
|
601 |
+
"loss": 0.8225,
|
602 |
+
"step": 68000
|
603 |
+
},
|
604 |
+
{
|
605 |
+
"epoch": 3.9251379486887763,
|
606 |
+
"grad_norm": 0.9270259141921997,
|
607 |
+
"learning_rate": 0.00017197792820979578,
|
608 |
+
"loss": 0.8158,
|
609 |
+
"step": 69000
|
610 |
+
},
|
611 |
+
{
|
612 |
+
"epoch": 3.98202400591615,
|
613 |
+
"grad_norm": 1.082774043083191,
|
614 |
+
"learning_rate": 0.00016287615905341603,
|
615 |
+
"loss": 0.8156,
|
616 |
+
"step": 70000
|
617 |
+
},
|
618 |
+
{
|
619 |
+
"epoch": 3.98202400591615,
|
620 |
+
"eval_accuracy": 0.770764,
|
621 |
+
"eval_loss": 0.8961142301559448,
|
622 |
+
"eval_runtime": 138.0555,
|
623 |
+
"eval_samples_per_second": 1810.866,
|
624 |
+
"eval_steps_per_second": 7.077,
|
625 |
+
"step": 70000
|
626 |
+
},
|
627 |
+
{
|
628 |
+
"epoch": 4.038910063143524,
|
629 |
+
"grad_norm": 0.909858226776123,
|
630 |
+
"learning_rate": 0.00015377438989703626,
|
631 |
+
"loss": 0.7785,
|
632 |
+
"step": 71000
|
633 |
+
},
|
634 |
+
{
|
635 |
+
"epoch": 4.095796120370897,
|
636 |
+
"grad_norm": 0.931280791759491,
|
637 |
+
"learning_rate": 0.00014467262074065645,
|
638 |
+
"loss": 0.7637,
|
639 |
+
"step": 72000
|
640 |
+
},
|
641 |
+
{
|
642 |
+
"epoch": 4.152682177598271,
|
643 |
+
"grad_norm": 0.94422847032547,
|
644 |
+
"learning_rate": 0.0001355708515842767,
|
645 |
+
"loss": 0.7612,
|
646 |
+
"step": 73000
|
647 |
+
},
|
648 |
+
{
|
649 |
+
"epoch": 4.209568234825644,
|
650 |
+
"grad_norm": 0.9250127077102661,
|
651 |
+
"learning_rate": 0.00012646908242789693,
|
652 |
+
"loss": 0.7616,
|
653 |
+
"step": 74000
|
654 |
+
},
|
655 |
+
{
|
656 |
+
"epoch": 4.266454292053018,
|
657 |
+
"grad_norm": 0.8467296957969666,
|
658 |
+
"learning_rate": 0.00011736731327151716,
|
659 |
+
"loss": 0.7557,
|
660 |
+
"step": 75000
|
661 |
+
},
|
662 |
+
{
|
663 |
+
"epoch": 4.266454292053018,
|
664 |
+
"eval_accuracy": 0.77204,
|
665 |
+
"eval_loss": 0.9022773504257202,
|
666 |
+
"eval_runtime": 144.5432,
|
667 |
+
"eval_samples_per_second": 1729.587,
|
668 |
+
"eval_steps_per_second": 6.759,
|
669 |
+
"step": 75000
|
670 |
+
},
|
671 |
+
{
|
672 |
+
"epoch": 4.323340349280391,
|
673 |
+
"grad_norm": 0.8985564708709717,
|
674 |
+
"learning_rate": 0.00010826554411513738,
|
675 |
+
"loss": 0.7604,
|
676 |
+
"step": 76000
|
677 |
+
},
|
678 |
+
{
|
679 |
+
"epoch": 4.380226406507765,
|
680 |
+
"grad_norm": 0.8618564605712891,
|
681 |
+
"learning_rate": 9.916377495875762e-05,
|
682 |
+
"loss": 0.7632,
|
683 |
+
"step": 77000
|
684 |
+
},
|
685 |
+
{
|
686 |
+
"epoch": 4.437112463735138,
|
687 |
+
"grad_norm": 0.9467126727104187,
|
688 |
+
"learning_rate": 9.006200580237784e-05,
|
689 |
+
"loss": 0.7614,
|
690 |
+
"step": 78000
|
691 |
+
},
|
692 |
+
{
|
693 |
+
"epoch": 4.493998520962512,
|
694 |
+
"grad_norm": 1.0163730382919312,
|
695 |
+
"learning_rate": 8.096023664599807e-05,
|
696 |
+
"loss": 0.7575,
|
697 |
+
"step": 79000
|
698 |
+
},
|
699 |
+
{
|
700 |
+
"epoch": 4.550884578189885,
|
701 |
+
"grad_norm": 1.1194038391113281,
|
702 |
+
"learning_rate": 7.18584674896183e-05,
|
703 |
+
"loss": 0.7595,
|
704 |
+
"step": 80000
|
705 |
+
},
|
706 |
+
{
|
707 |
+
"epoch": 4.550884578189885,
|
708 |
+
"eval_accuracy": 0.772256,
|
709 |
+
"eval_loss": 0.897346019744873,
|
710 |
+
"eval_runtime": 136.9434,
|
711 |
+
"eval_samples_per_second": 1825.571,
|
712 |
+
"eval_steps_per_second": 7.134,
|
713 |
+
"step": 80000
|
714 |
+
},
|
715 |
+
{
|
716 |
+
"epoch": 4.607770635417259,
|
717 |
+
"grad_norm": 1.0589629411697388,
|
718 |
+
"learning_rate": 6.275669833323853e-05,
|
719 |
+
"loss": 0.7548,
|
720 |
+
"step": 81000
|
721 |
+
},
|
722 |
+
{
|
723 |
+
"epoch": 4.664656692644633,
|
724 |
+
"grad_norm": 0.8540852665901184,
|
725 |
+
"learning_rate": 5.365492917685876e-05,
|
726 |
+
"loss": 0.7601,
|
727 |
+
"step": 82000
|
728 |
+
},
|
729 |
+
{
|
730 |
+
"epoch": 4.721542749872007,
|
731 |
+
"grad_norm": 1.127475380897522,
|
732 |
+
"learning_rate": 4.455316002047898e-05,
|
733 |
+
"loss": 0.7554,
|
734 |
+
"step": 83000
|
735 |
+
},
|
736 |
+
{
|
737 |
+
"epoch": 4.77842880709938,
|
738 |
+
"grad_norm": 0.9464063048362732,
|
739 |
+
"learning_rate": 3.545139086409921e-05,
|
740 |
+
"loss": 0.756,
|
741 |
+
"step": 84000
|
742 |
+
},
|
743 |
+
{
|
744 |
+
"epoch": 4.835314864326754,
|
745 |
+
"grad_norm": 0.9705914855003357,
|
746 |
+
"learning_rate": 2.634962170771944e-05,
|
747 |
+
"loss": 0.7581,
|
748 |
+
"step": 85000
|
749 |
+
},
|
750 |
+
{
|
751 |
+
"epoch": 4.835314864326754,
|
752 |
+
"eval_accuracy": 0.773724,
|
753 |
+
"eval_loss": 0.8925997018814087,
|
754 |
+
"eval_runtime": 138.7415,
|
755 |
+
"eval_samples_per_second": 1801.913,
|
756 |
+
"eval_steps_per_second": 7.042,
|
757 |
+
"step": 85000
|
758 |
+
},
|
759 |
+
{
|
760 |
+
"epoch": 4.892200921554127,
|
761 |
+
"grad_norm": 0.8879310488700867,
|
762 |
+
"learning_rate": 1.7247852551339668e-05,
|
763 |
+
"loss": 0.758,
|
764 |
+
"step": 86000
|
765 |
+
},
|
766 |
+
{
|
767 |
+
"epoch": 4.949086978781501,
|
768 |
+
"grad_norm": 1.2024400234222412,
|
769 |
+
"learning_rate": 8.146083394959896e-06,
|
770 |
+
"loss": 0.751,
|
771 |
+
"step": 87000
|
772 |
+
},
|
773 |
+
{
|
774 |
+
"epoch": 5.0,
|
775 |
+
"step": 87895,
|
776 |
+
"total_flos": 1.93274424e+18,
|
777 |
+
"train_loss": 0.9357909288237652,
|
778 |
+
"train_runtime": 45635.435,
|
779 |
+
"train_samples_per_second": 493.038,
|
780 |
+
"train_steps_per_second": 1.926
|
781 |
+
}
|
782 |
+
],
|
783 |
+
"logging_steps": 1000,
|
784 |
+
"max_steps": 87895,
|
785 |
+
"num_input_tokens_seen": 0,
|
786 |
+
"num_train_epochs": 5,
|
787 |
+
"save_steps": 5000,
|
788 |
+
"total_flos": 1.93274424e+18,
|
789 |
+
"train_batch_size": 256,
|
790 |
+
"trial_name": null,
|
791 |
+
"trial_params": null
|
792 |
+
}
|
training_args.bin
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:09269e0c37bdf9c229beefd43c807681f37512212896aa362181dedc28d01416
|
3 |
+
size 4984
|