pig4431 commited on
Commit
a2bab52
1 Parent(s): d5e1747

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +448 -0
README.md ADDED
@@ -0,0 +1,448 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: mit
3
+ tags:
4
+ - generated_from_trainer
5
+ datasets:
6
+ - amazon_polarity
7
+ metrics:
8
+ - accuracy
9
+ model-index:
10
+ - name: amazonPolarity_XLNET_5E
11
+ results:
12
+ - task:
13
+ name: Text Classification
14
+ type: text-classification
15
+ dataset:
16
+ name: amazon_polarity
17
+ type: amazon_polarity
18
+ config: amazon_polarity
19
+ split: train
20
+ args: amazon_polarity
21
+ metrics:
22
+ - name: Accuracy
23
+ type: accuracy
24
+ value: 0.9266666666666666
25
+ ---
26
+
27
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
28
+ should probably proofread and complete it, then remove this comment. -->
29
+
30
+ # amazonPolarity_XLNET_5E
31
+
32
+ This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on the amazon_polarity dataset.
33
+ It achieves the following results on the evaluation set:
34
+ - Loss: 0.4490
35
+ - Accuracy: 0.9267
36
+
37
+ ## Model description
38
+
39
+ More information needed
40
+
41
+ ## Intended uses & limitations
42
+
43
+ More information needed
44
+
45
+ ## Training and evaluation data
46
+
47
+ More information needed
48
+
49
+ ## Training procedure
50
+
51
+ ### Training hyperparameters
52
+
53
+ The following hyperparameters were used during training:
54
+ - learning_rate: 3e-05
55
+ - train_batch_size: 8
56
+ - eval_batch_size: 8
57
+ - seed: 42
58
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
59
+ - lr_scheduler_type: linear
60
+ - num_epochs: 5
61
+
62
+ ### Training results
63
+
64
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
65
+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|
66
+ | 0.6238 | 0.01 | 50 | 0.3703 | 0.86 |
67
+ | 0.3149 | 0.03 | 100 | 0.3715 | 0.9 |
68
+ | 0.3849 | 0.04 | 150 | 0.4125 | 0.8867 |
69
+ | 0.4051 | 0.05 | 200 | 0.4958 | 0.8933 |
70
+ | 0.3345 | 0.07 | 250 | 0.4258 | 0.9067 |
71
+ | 0.439 | 0.08 | 300 | 0.2650 | 0.9067 |
72
+ | 0.2248 | 0.09 | 350 | 0.3314 | 0.9267 |
73
+ | 0.2849 | 0.11 | 400 | 0.3097 | 0.8933 |
74
+ | 0.3468 | 0.12 | 450 | 0.3060 | 0.9067 |
75
+ | 0.3216 | 0.13 | 500 | 0.3826 | 0.9067 |
76
+ | 0.3462 | 0.15 | 550 | 0.2207 | 0.94 |
77
+ | 0.3632 | 0.16 | 600 | 0.1864 | 0.94 |
78
+ | 0.2483 | 0.17 | 650 | 0.3069 | 0.9267 |
79
+ | 0.3709 | 0.19 | 700 | 0.2859 | 0.9333 |
80
+ | 0.2953 | 0.2 | 750 | 0.3010 | 0.9333 |
81
+ | 0.3222 | 0.21 | 800 | 0.2668 | 0.9133 |
82
+ | 0.3142 | 0.23 | 850 | 0.3545 | 0.8667 |
83
+ | 0.2637 | 0.24 | 900 | 0.1922 | 0.9467 |
84
+ | 0.3929 | 0.25 | 950 | 0.2712 | 0.92 |
85
+ | 0.2918 | 0.27 | 1000 | 0.2516 | 0.9333 |
86
+ | 0.2269 | 0.28 | 1050 | 0.4227 | 0.8933 |
87
+ | 0.239 | 0.29 | 1100 | 0.3639 | 0.9133 |
88
+ | 0.2439 | 0.31 | 1150 | 0.3430 | 0.9133 |
89
+ | 0.2417 | 0.32 | 1200 | 0.2920 | 0.94 |
90
+ | 0.3223 | 0.33 | 1250 | 0.3426 | 0.9067 |
91
+ | 0.2775 | 0.35 | 1300 | 0.3752 | 0.8867 |
92
+ | 0.2733 | 0.36 | 1350 | 0.3015 | 0.9333 |
93
+ | 0.3737 | 0.37 | 1400 | 0.2875 | 0.9267 |
94
+ | 0.2907 | 0.39 | 1450 | 0.4926 | 0.8933 |
95
+ | 0.316 | 0.4 | 1500 | 0.2948 | 0.9333 |
96
+ | 0.2472 | 0.41 | 1550 | 0.4003 | 0.8933 |
97
+ | 0.2607 | 0.43 | 1600 | 0.3608 | 0.92 |
98
+ | 0.2848 | 0.44 | 1650 | 0.3332 | 0.9133 |
99
+ | 0.2708 | 0.45 | 1700 | 0.3424 | 0.92 |
100
+ | 0.3721 | 0.47 | 1750 | 0.2384 | 0.9267 |
101
+ | 0.2925 | 0.48 | 1800 | 0.4472 | 0.88 |
102
+ | 0.3619 | 0.49 | 1850 | 0.3824 | 0.9 |
103
+ | 0.1994 | 0.51 | 1900 | 0.4160 | 0.9133 |
104
+ | 0.3586 | 0.52 | 1950 | 0.3198 | 0.8867 |
105
+ | 0.2455 | 0.53 | 2000 | 0.3119 | 0.92 |
106
+ | 0.2683 | 0.55 | 2050 | 0.4262 | 0.8867 |
107
+ | 0.2983 | 0.56 | 2100 | 0.3552 | 0.9067 |
108
+ | 0.2973 | 0.57 | 2150 | 0.2966 | 0.8933 |
109
+ | 0.2299 | 0.59 | 2200 | 0.2972 | 0.92 |
110
+ | 0.295 | 0.6 | 2250 | 0.3122 | 0.9067 |
111
+ | 0.2716 | 0.61 | 2300 | 0.2556 | 0.9267 |
112
+ | 0.2842 | 0.63 | 2350 | 0.3317 | 0.92 |
113
+ | 0.2723 | 0.64 | 2400 | 0.4409 | 0.8933 |
114
+ | 0.2492 | 0.65 | 2450 | 0.3871 | 0.88 |
115
+ | 0.2297 | 0.67 | 2500 | 0.3526 | 0.9133 |
116
+ | 0.2125 | 0.68 | 2550 | 0.4597 | 0.9067 |
117
+ | 0.3003 | 0.69 | 2600 | 0.3374 | 0.8933 |
118
+ | 0.2622 | 0.71 | 2650 | 0.3492 | 0.9267 |
119
+ | 0.2436 | 0.72 | 2700 | 0.3438 | 0.9267 |
120
+ | 0.2599 | 0.73 | 2750 | 0.3725 | 0.9133 |
121
+ | 0.2759 | 0.75 | 2800 | 0.3260 | 0.9333 |
122
+ | 0.1841 | 0.76 | 2850 | 0.4218 | 0.9067 |
123
+ | 0.252 | 0.77 | 2900 | 0.2730 | 0.92 |
124
+ | 0.248 | 0.79 | 2950 | 0.3628 | 0.92 |
125
+ | 0.2356 | 0.8 | 3000 | 0.4012 | 0.9067 |
126
+ | 0.191 | 0.81 | 3050 | 0.3500 | 0.9267 |
127
+ | 0.2351 | 0.83 | 3100 | 0.4038 | 0.9133 |
128
+ | 0.2758 | 0.84 | 3150 | 0.3361 | 0.9067 |
129
+ | 0.2952 | 0.85 | 3200 | 0.2301 | 0.9267 |
130
+ | 0.2137 | 0.87 | 3250 | 0.3837 | 0.9133 |
131
+ | 0.2386 | 0.88 | 3300 | 0.2739 | 0.94 |
132
+ | 0.2786 | 0.89 | 3350 | 0.2820 | 0.9333 |
133
+ | 0.2284 | 0.91 | 3400 | 0.2557 | 0.9333 |
134
+ | 0.2546 | 0.92 | 3450 | 0.2744 | 0.9267 |
135
+ | 0.2514 | 0.93 | 3500 | 0.2908 | 0.94 |
136
+ | 0.3052 | 0.95 | 3550 | 0.2362 | 0.9333 |
137
+ | 0.2366 | 0.96 | 3600 | 0.3047 | 0.9333 |
138
+ | 0.2147 | 0.97 | 3650 | 0.3375 | 0.9333 |
139
+ | 0.3347 | 0.99 | 3700 | 0.2669 | 0.9267 |
140
+ | 0.3076 | 1.0 | 3750 | 0.2453 | 0.94 |
141
+ | 0.1685 | 1.01 | 3800 | 0.4117 | 0.9133 |
142
+ | 0.1954 | 1.03 | 3850 | 0.3074 | 0.9333 |
143
+ | 0.2512 | 1.04 | 3900 | 0.3942 | 0.9133 |
144
+ | 0.1365 | 1.05 | 3950 | 0.3211 | 0.92 |
145
+ | 0.1985 | 1.07 | 4000 | 0.4188 | 0.9133 |
146
+ | 0.1585 | 1.08 | 4050 | 0.4177 | 0.9133 |
147
+ | 0.1798 | 1.09 | 4100 | 0.3298 | 0.9333 |
148
+ | 0.1458 | 1.11 | 4150 | 0.5283 | 0.9 |
149
+ | 0.1831 | 1.12 | 4200 | 0.3884 | 0.92 |
150
+ | 0.1452 | 1.13 | 4250 | 0.4130 | 0.9133 |
151
+ | 0.1679 | 1.15 | 4300 | 0.3678 | 0.9267 |
152
+ | 0.1688 | 1.16 | 4350 | 0.3268 | 0.9333 |
153
+ | 0.1175 | 1.17 | 4400 | 0.4722 | 0.92 |
154
+ | 0.1661 | 1.19 | 4450 | 0.3899 | 0.9133 |
155
+ | 0.1688 | 1.2 | 4500 | 0.4050 | 0.9133 |
156
+ | 0.228 | 1.21 | 4550 | 0.4608 | 0.9 |
157
+ | 0.1946 | 1.23 | 4600 | 0.5080 | 0.9 |
158
+ | 0.1849 | 1.24 | 4650 | 0.4340 | 0.9067 |
159
+ | 0.1365 | 1.25 | 4700 | 0.4592 | 0.9133 |
160
+ | 0.2432 | 1.27 | 4750 | 0.3683 | 0.92 |
161
+ | 0.1679 | 1.28 | 4800 | 0.4604 | 0.9 |
162
+ | 0.2107 | 1.29 | 4850 | 0.3952 | 0.9 |
163
+ | 0.1499 | 1.31 | 4900 | 0.4275 | 0.92 |
164
+ | 0.1504 | 1.32 | 4950 | 0.3370 | 0.9333 |
165
+ | 0.1013 | 1.33 | 5000 | 0.3723 | 0.92 |
166
+ | 0.1303 | 1.35 | 5050 | 0.2925 | 0.9333 |
167
+ | 0.1205 | 1.36 | 5100 | 0.3452 | 0.9267 |
168
+ | 0.1427 | 1.37 | 5150 | 0.3080 | 0.94 |
169
+ | 0.1518 | 1.39 | 5200 | 0.3190 | 0.94 |
170
+ | 0.1885 | 1.4 | 5250 | 0.2726 | 0.9467 |
171
+ | 0.1264 | 1.41 | 5300 | 0.3466 | 0.9333 |
172
+ | 0.1939 | 1.43 | 5350 | 0.3957 | 0.9133 |
173
+ | 0.1939 | 1.44 | 5400 | 0.4007 | 0.9 |
174
+ | 0.1239 | 1.45 | 5450 | 0.2924 | 0.9333 |
175
+ | 0.1588 | 1.47 | 5500 | 0.2687 | 0.9333 |
176
+ | 0.1516 | 1.48 | 5550 | 0.3668 | 0.92 |
177
+ | 0.1623 | 1.49 | 5600 | 0.3141 | 0.94 |
178
+ | 0.2632 | 1.51 | 5650 | 0.2714 | 0.9333 |
179
+ | 0.1674 | 1.52 | 5700 | 0.3188 | 0.94 |
180
+ | 0.1854 | 1.53 | 5750 | 0.2818 | 0.9267 |
181
+ | 0.1282 | 1.55 | 5800 | 0.2918 | 0.9333 |
182
+ | 0.228 | 1.56 | 5850 | 0.2802 | 0.9133 |
183
+ | 0.2349 | 1.57 | 5900 | 0.1803 | 0.9467 |
184
+ | 0.1608 | 1.59 | 5950 | 0.3112 | 0.92 |
185
+ | 0.1493 | 1.6 | 6000 | 0.3018 | 0.9267 |
186
+ | 0.2182 | 1.61 | 6050 | 0.3419 | 0.9333 |
187
+ | 0.2408 | 1.63 | 6100 | 0.2887 | 0.9267 |
188
+ | 0.1872 | 1.64 | 6150 | 0.2408 | 0.9267 |
189
+ | 0.1246 | 1.65 | 6200 | 0.3752 | 0.9 |
190
+ | 0.2098 | 1.67 | 6250 | 0.2622 | 0.9333 |
191
+ | 0.1916 | 1.68 | 6300 | 0.2245 | 0.9467 |
192
+ | 0.2069 | 1.69 | 6350 | 0.2151 | 0.9467 |
193
+ | 0.1446 | 1.71 | 6400 | 0.2186 | 0.9533 |
194
+ | 0.1528 | 1.72 | 6450 | 0.1863 | 0.9533 |
195
+ | 0.1352 | 1.73 | 6500 | 0.2660 | 0.9467 |
196
+ | 0.2398 | 1.75 | 6550 | 0.1912 | 0.9533 |
197
+ | 0.1485 | 1.76 | 6600 | 0.2492 | 0.9467 |
198
+ | 0.2006 | 1.77 | 6650 | 0.2495 | 0.9267 |
199
+ | 0.2036 | 1.79 | 6700 | 0.3885 | 0.9067 |
200
+ | 0.1725 | 1.8 | 6750 | 0.2359 | 0.9533 |
201
+ | 0.1864 | 1.81 | 6800 | 0.2271 | 0.9533 |
202
+ | 0.1465 | 1.83 | 6850 | 0.2669 | 0.9333 |
203
+ | 0.197 | 1.84 | 6900 | 0.2290 | 0.96 |
204
+ | 0.1382 | 1.85 | 6950 | 0.2322 | 0.9467 |
205
+ | 0.1206 | 1.87 | 7000 | 0.3117 | 0.9333 |
206
+ | 0.157 | 1.88 | 7050 | 0.2163 | 0.9533 |
207
+ | 0.1686 | 1.89 | 7100 | 0.2239 | 0.9533 |
208
+ | 0.1953 | 1.91 | 7150 | 0.3064 | 0.9333 |
209
+ | 0.1638 | 1.92 | 7200 | 0.2821 | 0.9533 |
210
+ | 0.1605 | 1.93 | 7250 | 0.2413 | 0.9467 |
211
+ | 0.1736 | 1.95 | 7300 | 0.2430 | 0.94 |
212
+ | 0.2372 | 1.96 | 7350 | 0.2306 | 0.94 |
213
+ | 0.1549 | 1.97 | 7400 | 0.2730 | 0.94 |
214
+ | 0.1824 | 1.99 | 7450 | 0.3443 | 0.94 |
215
+ | 0.2263 | 2.0 | 7500 | 0.2695 | 0.9267 |
216
+ | 0.088 | 2.01 | 7550 | 0.2305 | 0.96 |
217
+ | 0.0376 | 2.03 | 7600 | 0.3380 | 0.94 |
218
+ | 0.072 | 2.04 | 7650 | 0.3349 | 0.9467 |
219
+ | 0.0491 | 2.05 | 7700 | 0.3397 | 0.94 |
220
+ | 0.0509 | 2.07 | 7750 | 0.3496 | 0.9467 |
221
+ | 0.1033 | 2.08 | 7800 | 0.3364 | 0.94 |
222
+ | 0.0549 | 2.09 | 7850 | 0.3520 | 0.94 |
223
+ | 0.0627 | 2.11 | 7900 | 0.4510 | 0.9267 |
224
+ | 0.0283 | 2.12 | 7950 | 0.3733 | 0.94 |
225
+ | 0.1215 | 2.13 | 8000 | 0.3892 | 0.9267 |
226
+ | 0.0856 | 2.15 | 8050 | 0.3114 | 0.9533 |
227
+ | 0.0945 | 2.16 | 8100 | 0.3626 | 0.9333 |
228
+ | 0.0901 | 2.17 | 8150 | 0.3116 | 0.94 |
229
+ | 0.0688 | 2.19 | 8200 | 0.3515 | 0.9267 |
230
+ | 0.1286 | 2.2 | 8250 | 0.3255 | 0.9333 |
231
+ | 0.1043 | 2.21 | 8300 | 0.4395 | 0.9133 |
232
+ | 0.1199 | 2.23 | 8350 | 0.3307 | 0.94 |
233
+ | 0.0608 | 2.24 | 8400 | 0.2992 | 0.9533 |
234
+ | 0.0827 | 2.25 | 8450 | 0.3500 | 0.94 |
235
+ | 0.047 | 2.27 | 8500 | 0.3982 | 0.94 |
236
+ | 0.1154 | 2.28 | 8550 | 0.3851 | 0.94 |
237
+ | 0.1158 | 2.29 | 8600 | 0.3820 | 0.9133 |
238
+ | 0.1053 | 2.31 | 8650 | 0.4414 | 0.92 |
239
+ | 0.1336 | 2.32 | 8700 | 0.3680 | 0.92 |
240
+ | 0.0853 | 2.33 | 8750 | 0.3732 | 0.9333 |
241
+ | 0.0496 | 2.35 | 8800 | 0.3450 | 0.94 |
242
+ | 0.0552 | 2.36 | 8850 | 0.4310 | 0.9267 |
243
+ | 0.1054 | 2.37 | 8900 | 0.4174 | 0.92 |
244
+ | 0.0951 | 2.39 | 8950 | 0.3815 | 0.9333 |
245
+ | 0.1235 | 2.4 | 9000 | 0.4119 | 0.9267 |
246
+ | 0.1094 | 2.41 | 9050 | 0.4282 | 0.9133 |
247
+ | 0.0897 | 2.43 | 9100 | 0.4766 | 0.9133 |
248
+ | 0.0925 | 2.44 | 9150 | 0.3303 | 0.94 |
249
+ | 0.1487 | 2.45 | 9200 | 0.2948 | 0.94 |
250
+ | 0.0963 | 2.47 | 9250 | 0.2911 | 0.94 |
251
+ | 0.0836 | 2.48 | 9300 | 0.3379 | 0.94 |
252
+ | 0.1594 | 2.49 | 9350 | 0.3841 | 0.9267 |
253
+ | 0.0846 | 2.51 | 9400 | 0.4128 | 0.9267 |
254
+ | 0.0984 | 2.52 | 9450 | 0.4131 | 0.9333 |
255
+ | 0.1042 | 2.53 | 9500 | 0.4048 | 0.9267 |
256
+ | 0.0633 | 2.55 | 9550 | 0.3776 | 0.94 |
257
+ | 0.1266 | 2.56 | 9600 | 0.3247 | 0.9333 |
258
+ | 0.1084 | 2.57 | 9650 | 0.3174 | 0.9467 |
259
+ | 0.0714 | 2.59 | 9700 | 0.3597 | 0.94 |
260
+ | 0.0826 | 2.6 | 9750 | 0.3261 | 0.9467 |
261
+ | 0.1527 | 2.61 | 9800 | 0.2531 | 0.9533 |
262
+ | 0.0506 | 2.63 | 9850 | 0.2994 | 0.9533 |
263
+ | 0.1043 | 2.64 | 9900 | 0.3345 | 0.9467 |
264
+ | 0.0229 | 2.65 | 9950 | 0.4318 | 0.9333 |
265
+ | 0.1247 | 2.67 | 10000 | 0.2951 | 0.9533 |
266
+ | 0.1285 | 2.68 | 10050 | 0.3036 | 0.9533 |
267
+ | 0.081 | 2.69 | 10100 | 0.3541 | 0.94 |
268
+ | 0.0829 | 2.71 | 10150 | 0.3757 | 0.9467 |
269
+ | 0.0702 | 2.72 | 10200 | 0.3307 | 0.9533 |
270
+ | 0.07 | 2.73 | 10250 | 0.3638 | 0.94 |
271
+ | 0.1563 | 2.75 | 10300 | 0.3283 | 0.94 |
272
+ | 0.1223 | 2.76 | 10350 | 0.3441 | 0.92 |
273
+ | 0.0954 | 2.77 | 10400 | 0.3049 | 0.94 |
274
+ | 0.0438 | 2.79 | 10450 | 0.3675 | 0.9467 |
275
+ | 0.0796 | 2.8 | 10500 | 0.3364 | 0.94 |
276
+ | 0.0803 | 2.81 | 10550 | 0.2970 | 0.94 |
277
+ | 0.0324 | 2.83 | 10600 | 0.3941 | 0.9267 |
278
+ | 0.083 | 2.84 | 10650 | 0.3439 | 0.94 |
279
+ | 0.1263 | 2.85 | 10700 | 0.3759 | 0.9267 |
280
+ | 0.1044 | 2.87 | 10750 | 1.0700 | 0.58 |
281
+ | 0.1182 | 2.88 | 10800 | 0.4409 | 0.9333 |
282
+ | 0.126 | 2.89 | 10850 | 0.6467 | 0.5933 |
283
+ | 0.094 | 2.91 | 10900 | 0.3741 | 0.9333 |
284
+ | 0.1405 | 2.92 | 10950 | 0.3458 | 0.9267 |
285
+ | 0.1024 | 2.93 | 11000 | 0.2946 | 0.9333 |
286
+ | 0.0812 | 2.95 | 11050 | 0.2850 | 0.9333 |
287
+ | 0.1132 | 2.96 | 11100 | 0.3093 | 0.9267 |
288
+ | 0.0775 | 2.97 | 11150 | 0.3938 | 0.9067 |
289
+ | 0.1179 | 2.99 | 11200 | 0.3528 | 0.9267 |
290
+ | 0.1413 | 3.0 | 11250 | 0.2984 | 0.9333 |
291
+ | 0.0528 | 3.01 | 11300 | 0.3387 | 0.9333 |
292
+ | 0.0214 | 3.03 | 11350 | 0.4108 | 0.92 |
293
+ | 0.0408 | 3.04 | 11400 | 0.4174 | 0.9267 |
294
+ | 0.0808 | 3.05 | 11450 | 0.4283 | 0.9267 |
295
+ | 0.0535 | 3.07 | 11500 | 0.3719 | 0.9333 |
296
+ | 0.0344 | 3.08 | 11550 | 0.4382 | 0.9333 |
297
+ | 0.0364 | 3.09 | 11600 | 0.4195 | 0.9333 |
298
+ | 0.0524 | 3.11 | 11650 | 0.4607 | 0.92 |
299
+ | 0.0682 | 3.12 | 11700 | 0.4503 | 0.92 |
300
+ | 0.0554 | 3.13 | 11750 | 0.4563 | 0.92 |
301
+ | 0.0401 | 3.15 | 11800 | 0.4668 | 0.9133 |
302
+ | 0.0782 | 3.16 | 11850 | 0.4468 | 0.9133 |
303
+ | 0.0605 | 3.17 | 11900 | 0.4239 | 0.92 |
304
+ | 0.0599 | 3.19 | 11950 | 0.4019 | 0.92 |
305
+ | 0.0364 | 3.2 | 12000 | 0.3988 | 0.9267 |
306
+ | 0.0357 | 3.21 | 12050 | 0.4168 | 0.9267 |
307
+ | 0.072 | 3.23 | 12100 | 0.3889 | 0.9333 |
308
+ | 0.0931 | 3.24 | 12150 | 0.3368 | 0.9333 |
309
+ | 0.0724 | 3.25 | 12200 | 0.3209 | 0.9333 |
310
+ | 0.0653 | 3.27 | 12250 | 0.3615 | 0.9333 |
311
+ | 0.0173 | 3.28 | 12300 | 0.3946 | 0.9333 |
312
+ | 0.0537 | 3.29 | 12350 | 0.3876 | 0.9333 |
313
+ | 0.0373 | 3.31 | 12400 | 0.4079 | 0.9267 |
314
+ | 0.0322 | 3.32 | 12450 | 0.3553 | 0.94 |
315
+ | 0.0585 | 3.33 | 12500 | 0.4276 | 0.92 |
316
+ | 0.0315 | 3.35 | 12550 | 0.4092 | 0.9267 |
317
+ | 0.0317 | 3.36 | 12600 | 0.4107 | 0.9267 |
318
+ | 0.082 | 3.37 | 12650 | 0.4170 | 0.9267 |
319
+ | 0.1101 | 3.39 | 12700 | 0.3801 | 0.9333 |
320
+ | 0.0392 | 3.4 | 12750 | 0.3802 | 0.9333 |
321
+ | 0.0382 | 3.41 | 12800 | 0.4194 | 0.9267 |
322
+ | 0.048 | 3.43 | 12850 | 0.3794 | 0.9333 |
323
+ | 0.0896 | 3.44 | 12900 | 0.3961 | 0.9267 |
324
+ | 0.0966 | 3.45 | 12950 | 0.3982 | 0.92 |
325
+ | 0.0165 | 3.47 | 13000 | 0.3819 | 0.92 |
326
+ | 0.0701 | 3.48 | 13050 | 0.3440 | 0.94 |
327
+ | 0.0104 | 3.49 | 13100 | 0.4132 | 0.9267 |
328
+ | 0.0991 | 3.51 | 13150 | 0.3477 | 0.9333 |
329
+ | 0.0554 | 3.52 | 13200 | 0.3255 | 0.94 |
330
+ | 0.0476 | 3.53 | 13250 | 0.4343 | 0.92 |
331
+ | 0.0213 | 3.55 | 13300 | 0.4601 | 0.92 |
332
+ | 0.0465 | 3.56 | 13350 | 0.4141 | 0.9267 |
333
+ | 0.1246 | 3.57 | 13400 | 0.3473 | 0.94 |
334
+ | 0.1112 | 3.59 | 13450 | 0.3679 | 0.92 |
335
+ | 0.0323 | 3.6 | 13500 | 0.3508 | 0.9267 |
336
+ | 0.0423 | 3.61 | 13550 | 0.3475 | 0.94 |
337
+ | 0.0498 | 3.63 | 13600 | 0.4095 | 0.92 |
338
+ | 0.0531 | 3.64 | 13650 | 0.3544 | 0.9333 |
339
+ | 0.0365 | 3.65 | 13700 | 0.4403 | 0.9133 |
340
+ | 0.058 | 3.67 | 13750 | 0.4284 | 0.9133 |
341
+ | 0.0191 | 3.68 | 13800 | 0.4466 | 0.92 |
342
+ | 0.0838 | 3.69 | 13850 | 0.5128 | 0.9067 |
343
+ | 0.1561 | 3.71 | 13900 | 0.3588 | 0.9267 |
344
+ | 0.0464 | 3.72 | 13950 | 0.3867 | 0.92 |
345
+ | 0.037 | 3.73 | 14000 | 0.3961 | 0.92 |
346
+ | 0.0288 | 3.75 | 14050 | 0.4274 | 0.92 |
347
+ | 0.0928 | 3.76 | 14100 | 0.3524 | 0.94 |
348
+ | 0.0696 | 3.77 | 14150 | 0.3555 | 0.9333 |
349
+ | 0.0318 | 3.79 | 14200 | 0.3457 | 0.9467 |
350
+ | 0.0417 | 3.8 | 14250 | 0.3412 | 0.94 |
351
+ | 0.0283 | 3.81 | 14300 | 0.3845 | 0.9333 |
352
+ | 0.058 | 3.83 | 14350 | 0.3765 | 0.9333 |
353
+ | 0.0589 | 3.84 | 14400 | 0.4085 | 0.9267 |
354
+ | 0.0432 | 3.85 | 14450 | 0.4103 | 0.9267 |
355
+ | 0.0365 | 3.87 | 14500 | 0.4000 | 0.9267 |
356
+ | 0.0858 | 3.88 | 14550 | 0.3905 | 0.9267 |
357
+ | 0.0494 | 3.89 | 14600 | 0.3739 | 0.9267 |
358
+ | 0.0503 | 3.91 | 14650 | 0.3203 | 0.94 |
359
+ | 0.0349 | 3.92 | 14700 | 0.3268 | 0.9467 |
360
+ | 0.0328 | 3.93 | 14750 | 0.3259 | 0.9467 |
361
+ | 0.0347 | 3.95 | 14800 | 0.3588 | 0.94 |
362
+ | 0.0233 | 3.96 | 14850 | 0.3456 | 0.9467 |
363
+ | 0.0602 | 3.97 | 14900 | 0.3819 | 0.94 |
364
+ | 0.0766 | 3.99 | 14950 | 0.3813 | 0.9333 |
365
+ | 0.0562 | 4.0 | 15000 | 0.3669 | 0.9333 |
366
+ | 0.0163 | 4.01 | 15050 | 0.4176 | 0.92 |
367
+ | 0.007 | 4.03 | 15100 | 0.3694 | 0.9333 |
368
+ | 0.0005 | 4.04 | 15150 | 0.3915 | 0.9333 |
369
+ | 0.021 | 4.05 | 15200 | 0.4334 | 0.9333 |
370
+ | 0.0823 | 4.07 | 15250 | 0.4155 | 0.9333 |
371
+ | 0.0509 | 4.08 | 15300 | 0.4056 | 0.9333 |
372
+ | 0.0381 | 4.09 | 15350 | 0.3729 | 0.94 |
373
+ | 0.045 | 4.11 | 15400 | 0.3940 | 0.9333 |
374
+ | 0.0379 | 4.12 | 15450 | 0.4276 | 0.9267 |
375
+ | 0.0661 | 4.13 | 15500 | 0.3797 | 0.94 |
376
+ | 0.0522 | 4.15 | 15550 | 0.4029 | 0.9333 |
377
+ | 0.0189 | 4.16 | 15600 | 0.4424 | 0.9267 |
378
+ | 0.0191 | 4.17 | 15650 | 0.4711 | 0.92 |
379
+ | 0.031 | 4.19 | 15700 | 0.4344 | 0.9333 |
380
+ | 0.0837 | 4.2 | 15750 | 0.3703 | 0.94 |
381
+ | 0.0397 | 4.21 | 15800 | 0.3976 | 0.9333 |
382
+ | 0.034 | 4.23 | 15850 | 0.4021 | 0.9333 |
383
+ | 0.0199 | 4.24 | 15900 | 0.4015 | 0.9333 |
384
+ | 0.0315 | 4.25 | 15950 | 0.3652 | 0.94 |
385
+ | 0.076 | 4.27 | 16000 | 0.3421 | 0.94 |
386
+ | 0.0478 | 4.28 | 16050 | 0.3122 | 0.9533 |
387
+ | 0.0203 | 4.29 | 16100 | 0.3436 | 0.9467 |
388
+ | 0.0706 | 4.31 | 16150 | 0.3544 | 0.94 |
389
+ | 0.0086 | 4.32 | 16200 | 0.3730 | 0.94 |
390
+ | 0.05 | 4.33 | 16250 | 0.3761 | 0.94 |
391
+ | 0.048 | 4.35 | 16300 | 0.3583 | 0.94 |
392
+ | 0.0715 | 4.36 | 16350 | 0.3459 | 0.94 |
393
+ | 0.0316 | 4.37 | 16400 | 0.3355 | 0.94 |
394
+ | 0.0356 | 4.39 | 16450 | 0.3278 | 0.9467 |
395
+ | 0.0176 | 4.4 | 16500 | 0.3177 | 0.9467 |
396
+ | 0.0817 | 4.41 | 16550 | 0.3705 | 0.9333 |
397
+ | 0.0414 | 4.43 | 16600 | 0.3919 | 0.9333 |
398
+ | 0.0198 | 4.44 | 16650 | 0.3435 | 0.9467 |
399
+ | 0.0203 | 4.45 | 16700 | 0.3708 | 0.94 |
400
+ | 0.0391 | 4.47 | 16750 | 0.3615 | 0.94 |
401
+ | 0.0132 | 4.48 | 16800 | 0.3827 | 0.94 |
402
+ | 0.0385 | 4.49 | 16850 | 0.3837 | 0.94 |
403
+ | 0.0366 | 4.51 | 16900 | 0.3633 | 0.94 |
404
+ | 0.0779 | 4.52 | 16950 | 0.3403 | 0.9467 |
405
+ | 0.0168 | 4.53 | 17000 | 0.4592 | 0.92 |
406
+ | 0.0517 | 4.55 | 17050 | 0.4063 | 0.9333 |
407
+ | 0.0138 | 4.56 | 17100 | 0.4335 | 0.9267 |
408
+ | 0.0123 | 4.57 | 17150 | 0.3777 | 0.9333 |
409
+ | 0.0324 | 4.59 | 17200 | 0.4657 | 0.92 |
410
+ | 0.0202 | 4.6 | 17250 | 0.4791 | 0.92 |
411
+ | 0.001 | 4.61 | 17300 | 0.4761 | 0.92 |
412
+ | 0.0364 | 4.63 | 17350 | 0.4663 | 0.92 |
413
+ | 0.0154 | 4.64 | 17400 | 0.4611 | 0.92 |
414
+ | 0.0184 | 4.65 | 17450 | 0.4616 | 0.92 |
415
+ | 0.0004 | 4.67 | 17500 | 0.4650 | 0.92 |
416
+ | 0.0192 | 4.68 | 17550 | 0.4649 | 0.92 |
417
+ | 0.0185 | 4.69 | 17600 | 0.4654 | 0.92 |
418
+ | 0.0196 | 4.71 | 17650 | 0.4643 | 0.92 |
419
+ | 0.0386 | 4.72 | 17700 | 0.4660 | 0.92 |
420
+ | 0.0236 | 4.73 | 17750 | 0.4499 | 0.9267 |
421
+ | 0.0383 | 4.75 | 17800 | 0.4479 | 0.9267 |
422
+ | 0.0398 | 4.76 | 17850 | 0.4483 | 0.9267 |
423
+ | 0.0004 | 4.77 | 17900 | 0.4541 | 0.9267 |
424
+ | 0.023 | 4.79 | 17950 | 0.4387 | 0.9267 |
425
+ | 0.0361 | 4.8 | 18000 | 0.4409 | 0.9267 |
426
+ | 0.0409 | 4.81 | 18050 | 0.4384 | 0.9267 |
427
+ | 0.0004 | 4.83 | 18100 | 0.4376 | 0.9267 |
428
+ | 0.0171 | 4.84 | 18150 | 0.4421 | 0.9267 |
429
+ | 0.0589 | 4.85 | 18200 | 0.4373 | 0.9267 |
430
+ | 0.0004 | 4.87 | 18250 | 0.4492 | 0.9267 |
431
+ | 0.0142 | 4.88 | 18300 | 0.4585 | 0.9267 |
432
+ | 0.0561 | 4.89 | 18350 | 0.4681 | 0.9267 |
433
+ | 0.0204 | 4.91 | 18400 | 0.4608 | 0.9267 |
434
+ | 0.0248 | 4.92 | 18450 | 0.4641 | 0.9267 |
435
+ | 0.0404 | 4.93 | 18500 | 0.4567 | 0.9267 |
436
+ | 0.0608 | 4.95 | 18550 | 0.4518 | 0.9267 |
437
+ | 0.0412 | 4.96 | 18600 | 0.4510 | 0.9267 |
438
+ | 0.0183 | 4.97 | 18650 | 0.4522 | 0.9267 |
439
+ | 0.0567 | 4.99 | 18700 | 0.4492 | 0.9267 |
440
+ | 0.0173 | 5.0 | 18750 | 0.4490 | 0.9267 |
441
+
442
+
443
+ ### Framework versions
444
+
445
+ - Transformers 4.24.0
446
+ - Pytorch 1.13.0
447
+ - Datasets 2.6.1
448
+ - Tokenizers 0.13.1