EroshkinIvan commited on
Commit
b79725a
·
1 Parent(s): 4e2eda6

End of training

Browse files
Files changed (3) hide show
  1. README.md +402 -102
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -15,7 +15,7 @@ should probably proofread and complete it, then remove this comment. -->
15
 
16
  This model is a fine-tuned version of [facebook/detr-resnet-50](https://huggingface.co/facebook/detr-resnet-50) on an unknown dataset.
17
  It achieves the following results on the evaluation set:
18
- - Loss: 2.8856
19
 
20
  ## Model description
21
 
@@ -40,113 +40,413 @@ The following hyperparameters were used during training:
40
  - seed: 42
41
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
42
  - lr_scheduler_type: linear
43
- - num_epochs: 100
44
  - mixed_precision_training: Native AMP
45
 
46
  ### Training results
47
 
48
  | Training Loss | Epoch | Step | Validation Loss |
49
  |:-------------:|:-----:|:-----:|:---------------:|
50
- | 3.1837 | 1.0 | 125 | 3.5659 |
51
- | 2.6907 | 2.0 | 250 | 3.2286 |
52
- | 2.4581 | 3.0 | 375 | 3.2118 |
53
- | 2.1997 | 4.0 | 500 | 3.1780 |
54
- | 2.0847 | 5.0 | 625 | 3.1968 |
55
- | 2.0268 | 6.0 | 750 | 3.1370 |
56
- | 1.9542 | 7.0 | 875 | 3.1588 |
57
- | 1.9343 | 8.0 | 1000 | 3.0960 |
58
- | 1.8819 | 9.0 | 1125 | 3.0811 |
59
- | 1.7656 | 10.0 | 1250 | 3.0102 |
60
- | 1.7109 | 11.0 | 1375 | 2.9754 |
61
- | 1.6785 | 12.0 | 1500 | 3.0246 |
62
- | 1.6194 | 13.0 | 1625 | 3.0076 |
63
- | 1.5821 | 14.0 | 1750 | 3.0798 |
64
- | 1.622 | 15.0 | 1875 | 3.0285 |
65
- | 1.629 | 16.0 | 2000 | 2.9987 |
66
- | 1.544 | 17.0 | 2125 | 3.0359 |
67
- | 1.5406 | 18.0 | 2250 | 3.0030 |
68
- | 1.5633 | 19.0 | 2375 | 2.9325 |
69
- | 1.5259 | 20.0 | 2500 | 2.9074 |
70
- | 1.4708 | 21.0 | 2625 | 2.9328 |
71
- | 1.4383 | 22.0 | 2750 | 2.9443 |
72
- | 1.4479 | 23.0 | 2875 | 2.9437 |
73
- | 1.3943 | 24.0 | 3000 | 2.8937 |
74
- | 1.3788 | 25.0 | 3125 | 2.9420 |
75
- | 1.3633 | 26.0 | 3250 | 2.9428 |
76
- | 1.3611 | 27.0 | 3375 | 2.9732 |
77
- | 1.3113 | 28.0 | 3500 | 2.9272 |
78
- | 1.2516 | 29.0 | 3625 | 2.9821 |
79
- | 1.2725 | 30.0 | 3750 | 2.9464 |
80
- | 1.2805 | 31.0 | 3875 | 2.9489 |
81
- | 1.2488 | 32.0 | 4000 | 2.9561 |
82
- | 1.2867 | 33.0 | 4125 | 2.9559 |
83
- | 1.2178 | 34.0 | 4250 | 2.9204 |
84
- | 1.2704 | 35.0 | 4375 | 2.8930 |
85
- | 1.2575 | 36.0 | 4500 | 2.9010 |
86
- | 1.2164 | 37.0 | 4625 | 2.9040 |
87
- | 1.1689 | 38.0 | 4750 | 2.8662 |
88
- | 1.1529 | 39.0 | 4875 | 2.8886 |
89
- | 1.2028 | 40.0 | 5000 | 2.8742 |
90
- | 1.2133 | 41.0 | 5125 | 2.8920 |
91
- | 1.1297 | 42.0 | 5250 | 2.8889 |
92
- | 1.1679 | 43.0 | 5375 | 2.9592 |
93
- | 1.0868 | 44.0 | 5500 | 2.8861 |
94
- | 1.1039 | 45.0 | 5625 | 2.9462 |
95
- | 1.119 | 46.0 | 5750 | 2.9233 |
96
- | 1.1135 | 47.0 | 5875 | 2.9549 |
97
- | 1.0221 | 48.0 | 6000 | 2.9286 |
98
- | 1.0611 | 49.0 | 6125 | 2.9610 |
99
- | 1.0633 | 50.0 | 6250 | 2.9661 |
100
- | 1.0987 | 51.0 | 6375 | 2.9199 |
101
- | 1.0614 | 52.0 | 6500 | 2.9442 |
102
- | 1.0793 | 53.0 | 6625 | 2.8938 |
103
- | 1.0398 | 54.0 | 6750 | 2.9432 |
104
- | 1.0588 | 55.0 | 6875 | 2.8661 |
105
- | 0.9711 | 56.0 | 7000 | 2.9022 |
106
- | 1.0196 | 57.0 | 7125 | 2.9047 |
107
- | 1.0035 | 58.0 | 7250 | 2.8363 |
108
- | 1.0336 | 59.0 | 7375 | 2.8761 |
109
- | 0.9187 | 60.0 | 7500 | 2.8821 |
110
- | 0.9668 | 61.0 | 7625 | 2.8887 |
111
- | 1.0482 | 62.0 | 7750 | 2.9095 |
112
- | 1.0299 | 63.0 | 7875 | 2.8874 |
113
- | 0.9541 | 64.0 | 8000 | 2.8279 |
114
- | 0.9583 | 65.0 | 8125 | 2.8762 |
115
- | 0.9362 | 66.0 | 8250 | 2.8949 |
116
- | 0.9399 | 67.0 | 8375 | 2.8968 |
117
- | 0.9962 | 68.0 | 8500 | 2.9131 |
118
- | 0.9535 | 69.0 | 8625 | 2.8942 |
119
- | 0.91 | 70.0 | 8750 | 2.8740 |
120
- | 0.9345 | 71.0 | 8875 | 2.8686 |
121
- | 0.9695 | 72.0 | 9000 | 2.8287 |
122
- | 0.9645 | 73.0 | 9125 | 2.8337 |
123
- | 0.9433 | 74.0 | 9250 | 2.8606 |
124
- | 0.8786 | 75.0 | 9375 | 2.8629 |
125
- | 0.9213 | 76.0 | 9500 | 2.8518 |
126
- | 0.9078 | 77.0 | 9625 | 2.8582 |
127
- | 0.9115 | 78.0 | 9750 | 2.8374 |
128
- | 0.9425 | 79.0 | 9875 | 2.8753 |
129
- | 0.9144 | 80.0 | 10000 | 2.8480 |
130
- | 0.9168 | 81.0 | 10125 | 2.8754 |
131
- | 0.8959 | 82.0 | 10250 | 2.8765 |
132
- | 0.9031 | 83.0 | 10375 | 2.8996 |
133
- | 0.9328 | 84.0 | 10500 | 2.8937 |
134
- | 0.8159 | 85.0 | 10625 | 2.9085 |
135
- | 0.8857 | 86.0 | 10750 | 2.8733 |
136
- | 0.8684 | 87.0 | 10875 | 2.8559 |
137
- | 0.8514 | 88.0 | 11000 | 2.8945 |
138
- | 0.8557 | 89.0 | 11125 | 2.9170 |
139
- | 0.9147 | 90.0 | 11250 | 2.8985 |
140
- | 0.9022 | 91.0 | 11375 | 2.8808 |
141
- | 0.9027 | 92.0 | 11500 | 2.8827 |
142
- | 0.8562 | 93.0 | 11625 | 2.8811 |
143
- | 0.8032 | 94.0 | 11750 | 2.8769 |
144
- | 0.8689 | 95.0 | 11875 | 2.8719 |
145
- | 0.8718 | 96.0 | 12000 | 2.8891 |
146
- | 0.8729 | 97.0 | 12125 | 2.8699 |
147
- | 0.8137 | 98.0 | 12250 | 2.8693 |
148
- | 0.8434 | 99.0 | 12375 | 2.8892 |
149
- | 0.8836 | 100.0 | 12500 | 2.8856 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
150
 
151
 
152
  ### Framework versions
 
15
 
16
  This model is a fine-tuned version of [facebook/detr-resnet-50](https://huggingface.co/facebook/detr-resnet-50) on an unknown dataset.
17
  It achieves the following results on the evaluation set:
18
+ - Loss: 3.7727
19
 
20
  ## Model description
21
 
 
40
  - seed: 42
41
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
42
  - lr_scheduler_type: linear
43
+ - num_epochs: 400
44
  - mixed_precision_training: Native AMP
45
 
46
  ### Training results
47
 
48
  | Training Loss | Epoch | Step | Validation Loss |
49
  |:-------------:|:-----:|:-----:|:---------------:|
50
+ | 3.0989 | 1.0 | 125 | 3.4853 |
51
+ | 2.6414 | 2.0 | 250 | 3.4603 |
52
+ | 2.4811 | 3.0 | 375 | 3.1249 |
53
+ | 2.2018 | 4.0 | 500 | 2.9870 |
54
+ | 2.1618 | 5.0 | 625 | 3.2940 |
55
+ | 2.0608 | 6.0 | 750 | 3.1065 |
56
+ | 1.9556 | 7.0 | 875 | 3.0672 |
57
+ | 1.9142 | 8.0 | 1000 | 3.1347 |
58
+ | 1.8984 | 9.0 | 1125 | 3.0545 |
59
+ | 1.7799 | 10.0 | 1250 | 3.1041 |
60
+ | 1.7396 | 11.0 | 1375 | 2.9855 |
61
+ | 1.6741 | 12.0 | 1500 | 2.9899 |
62
+ | 1.6367 | 13.0 | 1625 | 3.0423 |
63
+ | 1.5807 | 14.0 | 1750 | 2.9943 |
64
+ | 1.6542 | 15.0 | 1875 | 3.0440 |
65
+ | 1.6268 | 16.0 | 2000 | 3.0157 |
66
+ | 1.5376 | 17.0 | 2125 | 3.0821 |
67
+ | 1.5396 | 18.0 | 2250 | 3.0359 |
68
+ | 1.5513 | 19.0 | 2375 | 3.0542 |
69
+ | 1.5038 | 20.0 | 2500 | 3.0153 |
70
+ | 1.4642 | 21.0 | 2625 | 3.0700 |
71
+ | 1.4331 | 22.0 | 2750 | 2.9970 |
72
+ | 1.4549 | 23.0 | 2875 | 3.0449 |
73
+ | 1.3796 | 24.0 | 3000 | 2.9348 |
74
+ | 1.3486 | 25.0 | 3125 | 3.0530 |
75
+ | 1.3557 | 26.0 | 3250 | 2.9036 |
76
+ | 1.3322 | 27.0 | 3375 | 2.8978 |
77
+ | 1.2866 | 28.0 | 3500 | 2.9449 |
78
+ | 1.2197 | 29.0 | 3625 | 2.9240 |
79
+ | 1.2596 | 30.0 | 3750 | 2.9422 |
80
+ | 1.2618 | 31.0 | 3875 | 2.8963 |
81
+ | 1.2298 | 32.0 | 4000 | 2.9116 |
82
+ | 1.2755 | 33.0 | 4125 | 2.8461 |
83
+ | 1.2062 | 34.0 | 4250 | 2.8651 |
84
+ | 1.2536 | 35.0 | 4375 | 2.8515 |
85
+ | 1.2543 | 36.0 | 4500 | 2.8212 |
86
+ | 1.2047 | 37.0 | 4625 | 2.8645 |
87
+ | 1.1618 | 38.0 | 4750 | 2.8755 |
88
+ | 1.1341 | 39.0 | 4875 | 2.9445 |
89
+ | 1.1881 | 40.0 | 5000 | 2.8731 |
90
+ | 1.2004 | 41.0 | 5125 | 2.8917 |
91
+ | 1.105 | 42.0 | 5250 | 2.9692 |
92
+ | 1.1408 | 43.0 | 5375 | 2.8619 |
93
+ | 1.0987 | 44.0 | 5500 | 2.8797 |
94
+ | 1.0857 | 45.0 | 5625 | 2.9032 |
95
+ | 1.0983 | 46.0 | 5750 | 2.7954 |
96
+ | 1.1254 | 47.0 | 5875 | 2.8693 |
97
+ | 0.9895 | 48.0 | 6000 | 2.9085 |
98
+ | 1.0401 | 49.0 | 6125 | 2.9256 |
99
+ | 1.0427 | 50.0 | 6250 | 2.9414 |
100
+ | 1.0813 | 51.0 | 6375 | 2.9730 |
101
+ | 1.043 | 52.0 | 6500 | 2.9698 |
102
+ | 1.0406 | 53.0 | 6625 | 2.9039 |
103
+ | 1.0178 | 54.0 | 6750 | 2.8910 |
104
+ | 1.0342 | 55.0 | 6875 | 2.8973 |
105
+ | 0.9433 | 56.0 | 7000 | 2.9515 |
106
+ | 1.0011 | 57.0 | 7125 | 2.8979 |
107
+ | 0.9683 | 58.0 | 7250 | 2.9770 |
108
+ | 0.9852 | 59.0 | 7375 | 2.9760 |
109
+ | 0.8886 | 60.0 | 7500 | 2.9978 |
110
+ | 0.9192 | 61.0 | 7625 | 2.9287 |
111
+ | 1.0015 | 62.0 | 7750 | 3.0118 |
112
+ | 0.9786 | 63.0 | 7875 | 2.9599 |
113
+ | 0.9238 | 64.0 | 8000 | 2.9459 |
114
+ | 0.9055 | 65.0 | 8125 | 2.9782 |
115
+ | 0.8864 | 66.0 | 8250 | 2.9396 |
116
+ | 0.8986 | 67.0 | 8375 | 3.0249 |
117
+ | 0.9571 | 68.0 | 8500 | 3.0207 |
118
+ | 0.8921 | 69.0 | 8625 | 2.9716 |
119
+ | 0.847 | 70.0 | 8750 | 3.0404 |
120
+ | 0.881 | 71.0 | 8875 | 2.9912 |
121
+ | 0.8919 | 72.0 | 9000 | 2.8573 |
122
+ | 0.8949 | 73.0 | 9125 | 2.8769 |
123
+ | 0.8704 | 74.0 | 9250 | 2.8301 |
124
+ | 0.8159 | 75.0 | 9375 | 2.9823 |
125
+ | 0.8586 | 76.0 | 9500 | 2.9548 |
126
+ | 0.8398 | 77.0 | 9625 | 2.9726 |
127
+ | 0.8368 | 78.0 | 9750 | 2.9853 |
128
+ | 0.8597 | 79.0 | 9875 | 3.0549 |
129
+ | 0.8176 | 80.0 | 10000 | 3.0531 |
130
+ | 0.838 | 81.0 | 10125 | 2.9602 |
131
+ | 0.8059 | 82.0 | 10250 | 2.9129 |
132
+ | 0.8176 | 83.0 | 10375 | 2.9702 |
133
+ | 0.8318 | 84.0 | 10500 | 2.9154 |
134
+ | 0.7104 | 85.0 | 10625 | 2.9706 |
135
+ | 0.7804 | 86.0 | 10750 | 2.9344 |
136
+ | 0.7696 | 87.0 | 10875 | 3.0594 |
137
+ | 0.7478 | 88.0 | 11000 | 2.9454 |
138
+ | 0.7374 | 89.0 | 11125 | 2.9786 |
139
+ | 0.7977 | 90.0 | 11250 | 2.9514 |
140
+ | 0.7864 | 91.0 | 11375 | 2.9400 |
141
+ | 0.7665 | 92.0 | 11500 | 2.8717 |
142
+ | 0.7539 | 93.0 | 11625 | 3.0417 |
143
+ | 0.6882 | 94.0 | 11750 | 2.9567 |
144
+ | 0.7424 | 95.0 | 11875 | 2.9805 |
145
+ | 0.7238 | 96.0 | 12000 | 3.0428 |
146
+ | 0.7383 | 97.0 | 12125 | 2.9852 |
147
+ | 0.6602 | 98.0 | 12250 | 3.0132 |
148
+ | 0.6971 | 99.0 | 12375 | 2.9537 |
149
+ | 0.7379 | 100.0 | 12500 | 2.9592 |
150
+ | 0.7207 | 101.0 | 12625 | 2.9905 |
151
+ | 0.7012 | 102.0 | 12750 | 3.0638 |
152
+ | 0.6768 | 103.0 | 12875 | 3.0401 |
153
+ | 0.6777 | 104.0 | 13000 | 3.0396 |
154
+ | 0.6913 | 105.0 | 13125 | 2.9501 |
155
+ | 0.6654 | 106.0 | 13250 | 3.1079 |
156
+ | 0.6393 | 107.0 | 13375 | 3.0405 |
157
+ | 0.6465 | 108.0 | 13500 | 3.1579 |
158
+ | 0.6379 | 109.0 | 13625 | 3.1174 |
159
+ | 0.6662 | 110.0 | 13750 | 3.0548 |
160
+ | 0.657 | 111.0 | 13875 | 3.0542 |
161
+ | 0.6193 | 112.0 | 14000 | 3.0411 |
162
+ | 0.5961 | 113.0 | 14125 | 3.0915 |
163
+ | 0.6438 | 114.0 | 14250 | 3.0924 |
164
+ | 0.5815 | 115.0 | 14375 | 3.0309 |
165
+ | 0.6113 | 116.0 | 14500 | 3.0300 |
166
+ | 0.635 | 117.0 | 14625 | 2.9968 |
167
+ | 0.5875 | 118.0 | 14750 | 2.9821 |
168
+ | 0.6447 | 119.0 | 14875 | 3.0285 |
169
+ | 0.5632 | 120.0 | 15000 | 3.0684 |
170
+ | 0.6206 | 121.0 | 15125 | 3.0065 |
171
+ | 0.5929 | 122.0 | 15250 | 3.0490 |
172
+ | 0.5509 | 123.0 | 15375 | 3.0520 |
173
+ | 0.6068 | 124.0 | 15500 | 3.0957 |
174
+ | 0.5747 | 125.0 | 15625 | 2.9621 |
175
+ | 0.5844 | 126.0 | 15750 | 3.0194 |
176
+ | 0.5684 | 127.0 | 15875 | 3.1037 |
177
+ | 0.6356 | 128.0 | 16000 | 3.0752 |
178
+ | 0.5644 | 129.0 | 16125 | 3.0063 |
179
+ | 0.6303 | 130.0 | 16250 | 3.0204 |
180
+ | 0.5432 | 131.0 | 16375 | 3.0809 |
181
+ | 0.6153 | 132.0 | 16500 | 3.1015 |
182
+ | 0.5662 | 133.0 | 16625 | 3.0639 |
183
+ | 0.5704 | 134.0 | 16750 | 3.1974 |
184
+ | 0.603 | 135.0 | 16875 | 3.1371 |
185
+ | 0.526 | 136.0 | 17000 | 3.1381 |
186
+ | 0.5767 | 137.0 | 17125 | 3.1614 |
187
+ | 0.5591 | 138.0 | 17250 | 3.2744 |
188
+ | 0.5609 | 139.0 | 17375 | 3.0405 |
189
+ | 0.5229 | 140.0 | 17500 | 3.0773 |
190
+ | 0.5367 | 141.0 | 17625 | 3.1367 |
191
+ | 0.5719 | 142.0 | 17750 | 3.1770 |
192
+ | 0.5172 | 143.0 | 17875 | 3.0953 |
193
+ | 0.5592 | 144.0 | 18000 | 3.2524 |
194
+ | 0.5422 | 145.0 | 18125 | 3.1534 |
195
+ | 0.5007 | 146.0 | 18250 | 3.1571 |
196
+ | 0.5348 | 147.0 | 18375 | 3.0949 |
197
+ | 0.5123 | 148.0 | 18500 | 3.1381 |
198
+ | 0.4839 | 149.0 | 18625 | 3.1624 |
199
+ | 0.5207 | 150.0 | 18750 | 3.0585 |
200
+ | 0.5236 | 151.0 | 18875 | 3.0886 |
201
+ | 0.5144 | 152.0 | 19000 | 3.1348 |
202
+ | 0.4882 | 153.0 | 19125 | 3.1027 |
203
+ | 0.4618 | 154.0 | 19250 | 3.1335 |
204
+ | 0.4573 | 155.0 | 19375 | 3.1687 |
205
+ | 0.4956 | 156.0 | 19500 | 3.2155 |
206
+ | 0.5073 | 157.0 | 19625 | 3.2512 |
207
+ | 0.5334 | 158.0 | 19750 | 3.2262 |
208
+ | 0.5014 | 159.0 | 19875 | 3.2350 |
209
+ | 0.4519 | 160.0 | 20000 | 3.2416 |
210
+ | 0.5042 | 161.0 | 20125 | 3.1955 |
211
+ | 0.4624 | 162.0 | 20250 | 3.2036 |
212
+ | 0.4577 | 163.0 | 20375 | 3.2498 |
213
+ | 0.5032 | 164.0 | 20500 | 3.1687 |
214
+ | 0.4894 | 165.0 | 20625 | 3.1920 |
215
+ | 0.4621 | 166.0 | 20750 | 3.2275 |
216
+ | 0.4896 | 167.0 | 20875 | 3.1416 |
217
+ | 0.4998 | 168.0 | 21000 | 3.1483 |
218
+ | 0.4941 | 169.0 | 21125 | 3.1408 |
219
+ | 0.4307 | 170.0 | 21250 | 3.2056 |
220
+ | 0.4284 | 171.0 | 21375 | 3.2112 |
221
+ | 0.4431 | 172.0 | 21500 | 3.1926 |
222
+ | 0.4429 | 173.0 | 21625 | 3.0972 |
223
+ | 0.4832 | 174.0 | 21750 | 3.2309 |
224
+ | 0.4417 | 175.0 | 21875 | 3.2027 |
225
+ | 0.4022 | 176.0 | 22000 | 3.2380 |
226
+ | 0.4777 | 177.0 | 22125 | 3.3315 |
227
+ | 0.462 | 178.0 | 22250 | 3.1854 |
228
+ | 0.4209 | 179.0 | 22375 | 3.1563 |
229
+ | 0.4271 | 180.0 | 22500 | 3.3036 |
230
+ | 0.4359 | 181.0 | 22625 | 3.3058 |
231
+ | 0.4324 | 182.0 | 22750 | 3.3639 |
232
+ | 0.4252 | 183.0 | 22875 | 3.2810 |
233
+ | 0.4382 | 184.0 | 23000 | 3.4633 |
234
+ | 0.4344 | 185.0 | 23125 | 3.2875 |
235
+ | 0.4639 | 186.0 | 23250 | 3.2771 |
236
+ | 0.4104 | 187.0 | 23375 | 3.2768 |
237
+ | 0.437 | 188.0 | 23500 | 3.3128 |
238
+ | 0.4469 | 189.0 | 23625 | 3.2389 |
239
+ | 0.4084 | 190.0 | 23750 | 3.4082 |
240
+ | 0.4333 | 191.0 | 23875 | 3.3177 |
241
+ | 0.4337 | 192.0 | 24000 | 3.3474 |
242
+ | 0.4173 | 193.0 | 24125 | 3.3495 |
243
+ | 0.386 | 194.0 | 24250 | 3.3413 |
244
+ | 0.4279 | 195.0 | 24375 | 3.3327 |
245
+ | 0.4046 | 196.0 | 24500 | 3.3383 |
246
+ | 0.4163 | 197.0 | 24625 | 3.3235 |
247
+ | 0.4032 | 198.0 | 24750 | 3.3549 |
248
+ | 0.381 | 199.0 | 24875 | 3.2899 |
249
+ | 0.3858 | 200.0 | 25000 | 3.3752 |
250
+ | 0.4085 | 201.0 | 25125 | 3.2569 |
251
+ | 0.3643 | 202.0 | 25250 | 3.3265 |
252
+ | 0.3621 | 203.0 | 25375 | 3.3730 |
253
+ | 0.4749 | 204.0 | 25500 | 3.3738 |
254
+ | 0.3969 | 205.0 | 25625 | 3.3619 |
255
+ | 0.3677 | 206.0 | 25750 | 3.4378 |
256
+ | 0.3838 | 207.0 | 25875 | 3.3412 |
257
+ | 0.4063 | 208.0 | 26000 | 3.3268 |
258
+ | 0.3719 | 209.0 | 26125 | 3.4574 |
259
+ | 0.3803 | 210.0 | 26250 | 3.3598 |
260
+ | 0.4093 | 211.0 | 26375 | 3.3738 |
261
+ | 0.38 | 212.0 | 26500 | 3.2644 |
262
+ | 0.3757 | 213.0 | 26625 | 3.3872 |
263
+ | 0.4116 | 214.0 | 26750 | 3.4318 |
264
+ | 0.3741 | 215.0 | 26875 | 3.2945 |
265
+ | 0.3809 | 216.0 | 27000 | 3.4419 |
266
+ | 0.3625 | 217.0 | 27125 | 3.4126 |
267
+ | 0.3772 | 218.0 | 27250 | 3.3693 |
268
+ | 0.3494 | 219.0 | 27375 | 3.3014 |
269
+ | 0.3521 | 220.0 | 27500 | 3.4202 |
270
+ | 0.3498 | 221.0 | 27625 | 3.2887 |
271
+ | 0.3716 | 222.0 | 27750 | 3.5634 |
272
+ | 0.346 | 223.0 | 27875 | 3.3463 |
273
+ | 0.388 | 224.0 | 28000 | 3.4088 |
274
+ | 0.3708 | 225.0 | 28125 | 3.3841 |
275
+ | 0.3964 | 226.0 | 28250 | 3.3839 |
276
+ | 0.3897 | 227.0 | 28375 | 3.4874 |
277
+ | 0.3272 | 228.0 | 28500 | 3.5225 |
278
+ | 0.3582 | 229.0 | 28625 | 3.4964 |
279
+ | 0.3656 | 230.0 | 28750 | 3.3781 |
280
+ | 0.3497 | 231.0 | 28875 | 3.4067 |
281
+ | 0.3318 | 232.0 | 29000 | 3.4918 |
282
+ | 0.3565 | 233.0 | 29125 | 3.5039 |
283
+ | 0.3865 | 234.0 | 29250 | 3.5416 |
284
+ | 0.3583 | 235.0 | 29375 | 3.4231 |
285
+ | 0.3464 | 236.0 | 29500 | 3.4524 |
286
+ | 0.3465 | 237.0 | 29625 | 3.4779 |
287
+ | 0.3428 | 238.0 | 29750 | 3.4889 |
288
+ | 0.3847 | 239.0 | 29875 | 3.5142 |
289
+ | 0.3505 | 240.0 | 30000 | 3.5132 |
290
+ | 0.344 | 241.0 | 30125 | 3.5439 |
291
+ | 0.3741 | 242.0 | 30250 | 3.4861 |
292
+ | 0.3045 | 243.0 | 30375 | 3.4534 |
293
+ | 0.3443 | 244.0 | 30500 | 3.4675 |
294
+ | 0.3719 | 245.0 | 30625 | 3.4354 |
295
+ | 0.3534 | 246.0 | 30750 | 3.4817 |
296
+ | 0.3644 | 247.0 | 30875 | 3.5027 |
297
+ | 0.3157 | 248.0 | 31000 | 3.5055 |
298
+ | 0.3393 | 249.0 | 31125 | 3.3962 |
299
+ | 0.3054 | 250.0 | 31250 | 3.4470 |
300
+ | 0.3434 | 251.0 | 31375 | 3.5036 |
301
+ | 0.3141 | 252.0 | 31500 | 3.5428 |
302
+ | 0.3227 | 253.0 | 31625 | 3.5025 |
303
+ | 0.3199 | 254.0 | 31750 | 3.5110 |
304
+ | 0.3667 | 255.0 | 31875 | 3.5168 |
305
+ | 0.3442 | 256.0 | 32000 | 3.5739 |
306
+ | 0.366 | 257.0 | 32125 | 3.5094 |
307
+ | 0.3053 | 258.0 | 32250 | 3.4360 |
308
+ | 0.3595 | 259.0 | 32375 | 3.5895 |
309
+ | 0.3329 | 260.0 | 32500 | 3.5869 |
310
+ | 0.3139 | 261.0 | 32625 | 3.5317 |
311
+ | 0.299 | 262.0 | 32750 | 3.6398 |
312
+ | 0.3131 | 263.0 | 32875 | 3.5696 |
313
+ | 0.3218 | 264.0 | 33000 | 3.5519 |
314
+ | 0.3677 | 265.0 | 33125 | 3.6712 |
315
+ | 0.3447 | 266.0 | 33250 | 3.5278 |
316
+ | 0.3094 | 267.0 | 33375 | 3.5613 |
317
+ | 0.3031 | 268.0 | 33500 | 3.4634 |
318
+ | 0.3234 | 269.0 | 33625 | 3.5966 |
319
+ | 0.3489 | 270.0 | 33750 | 3.5239 |
320
+ | 0.3168 | 271.0 | 33875 | 3.6847 |
321
+ | 0.3151 | 272.0 | 34000 | 3.5559 |
322
+ | 0.2843 | 273.0 | 34125 | 3.5995 |
323
+ | 0.3003 | 274.0 | 34250 | 3.6388 |
324
+ | 0.3154 | 275.0 | 34375 | 3.6759 |
325
+ | 0.3178 | 276.0 | 34500 | 3.5199 |
326
+ | 0.3436 | 277.0 | 34625 | 3.5651 |
327
+ | 0.3136 | 278.0 | 34750 | 3.5722 |
328
+ | 0.3252 | 279.0 | 34875 | 3.4851 |
329
+ | 0.3404 | 280.0 | 35000 | 3.6847 |
330
+ | 0.304 | 281.0 | 35125 | 3.5653 |
331
+ | 0.3395 | 282.0 | 35250 | 3.6775 |
332
+ | 0.3431 | 283.0 | 35375 | 3.5556 |
333
+ | 0.2861 | 284.0 | 35500 | 3.6451 |
334
+ | 0.3066 | 285.0 | 35625 | 3.6052 |
335
+ | 0.3151 | 286.0 | 35750 | 3.6406 |
336
+ | 0.3143 | 287.0 | 35875 | 3.6744 |
337
+ | 0.2873 | 288.0 | 36000 | 3.6218 |
338
+ | 0.3296 | 289.0 | 36125 | 3.4993 |
339
+ | 0.3024 | 290.0 | 36250 | 3.5596 |
340
+ | 0.3138 | 291.0 | 36375 | 3.5875 |
341
+ | 0.2964 | 292.0 | 36500 | 3.5953 |
342
+ | 0.2935 | 293.0 | 36625 | 3.5550 |
343
+ | 0.2856 | 294.0 | 36750 | 3.5805 |
344
+ | 0.2998 | 295.0 | 36875 | 3.6153 |
345
+ | 0.2809 | 296.0 | 37000 | 3.6440 |
346
+ | 0.3197 | 297.0 | 37125 | 3.6127 |
347
+ | 0.2863 | 298.0 | 37250 | 3.6362 |
348
+ | 0.3355 | 299.0 | 37375 | 3.7291 |
349
+ | 0.2942 | 300.0 | 37500 | 3.6750 |
350
+ | 0.3187 | 301.0 | 37625 | 3.6617 |
351
+ | 0.3191 | 302.0 | 37750 | 3.6898 |
352
+ | 0.2716 | 303.0 | 37875 | 3.6238 |
353
+ | 0.2911 | 304.0 | 38000 | 3.6409 |
354
+ | 0.3231 | 305.0 | 38125 | 3.6807 |
355
+ | 0.2723 | 306.0 | 38250 | 3.7038 |
356
+ | 0.2812 | 307.0 | 38375 | 3.6565 |
357
+ | 0.3225 | 308.0 | 38500 | 3.6680 |
358
+ | 0.2803 | 309.0 | 38625 | 3.7389 |
359
+ | 0.2852 | 310.0 | 38750 | 3.7257 |
360
+ | 0.2958 | 311.0 | 38875 | 3.7873 |
361
+ | 0.3191 | 312.0 | 39000 | 3.8238 |
362
+ | 0.2815 | 313.0 | 39125 | 3.7388 |
363
+ | 0.2681 | 314.0 | 39250 | 3.7543 |
364
+ | 0.3259 | 315.0 | 39375 | 3.8022 |
365
+ | 0.2804 | 316.0 | 39500 | 3.7106 |
366
+ | 0.3214 | 317.0 | 39625 | 3.6244 |
367
+ | 0.2732 | 318.0 | 39750 | 3.7712 |
368
+ | 0.3054 | 319.0 | 39875 | 3.6776 |
369
+ | 0.263 | 320.0 | 40000 | 3.6850 |
370
+ | 0.2644 | 321.0 | 40125 | 3.7169 |
371
+ | 0.2796 | 322.0 | 40250 | 3.7958 |
372
+ | 0.2928 | 323.0 | 40375 | 3.7770 |
373
+ | 0.2774 | 324.0 | 40500 | 3.7142 |
374
+ | 0.3048 | 325.0 | 40625 | 3.7942 |
375
+ | 0.2637 | 326.0 | 40750 | 3.7499 |
376
+ | 0.2549 | 327.0 | 40875 | 3.7323 |
377
+ | 0.2681 | 328.0 | 41000 | 3.8373 |
378
+ | 0.2735 | 329.0 | 41125 | 3.7600 |
379
+ | 0.291 | 330.0 | 41250 | 3.6715 |
380
+ | 0.278 | 331.0 | 41375 | 3.6660 |
381
+ | 0.2785 | 332.0 | 41500 | 3.7076 |
382
+ | 0.2632 | 333.0 | 41625 | 3.7408 |
383
+ | 0.2994 | 334.0 | 41750 | 3.7214 |
384
+ | 0.2563 | 335.0 | 41875 | 3.7326 |
385
+ | 0.2755 | 336.0 | 42000 | 3.7088 |
386
+ | 0.287 | 337.0 | 42125 | 3.7493 |
387
+ | 0.3144 | 338.0 | 42250 | 3.7180 |
388
+ | 0.2816 | 339.0 | 42375 | 3.7289 |
389
+ | 0.2515 | 340.0 | 42500 | 3.6592 |
390
+ | 0.2647 | 341.0 | 42625 | 3.6483 |
391
+ | 0.2833 | 342.0 | 42750 | 3.7359 |
392
+ | 0.2678 | 343.0 | 42875 | 3.7351 |
393
+ | 0.2929 | 344.0 | 43000 | 3.7129 |
394
+ | 0.2604 | 345.0 | 43125 | 3.7604 |
395
+ | 0.2406 | 346.0 | 43250 | 3.6867 |
396
+ | 0.2802 | 347.0 | 43375 | 3.6935 |
397
+ | 0.2702 | 348.0 | 43500 | 3.6744 |
398
+ | 0.2836 | 349.0 | 43625 | 3.7118 |
399
+ | 0.2454 | 350.0 | 43750 | 3.7354 |
400
+ | 0.238 | 351.0 | 43875 | 3.7200 |
401
+ | 0.2663 | 352.0 | 44000 | 3.7351 |
402
+ | 0.272 | 353.0 | 44125 | 3.7509 |
403
+ | 0.2422 | 354.0 | 44250 | 3.7413 |
404
+ | 0.3032 | 355.0 | 44375 | 3.6266 |
405
+ | 0.2617 | 356.0 | 44500 | 3.7229 |
406
+ | 0.2618 | 357.0 | 44625 | 3.7356 |
407
+ | 0.2619 | 358.0 | 44750 | 3.7178 |
408
+ | 0.2588 | 359.0 | 44875 | 3.7896 |
409
+ | 0.2508 | 360.0 | 45000 | 3.7686 |
410
+ | 0.2791 | 361.0 | 45125 | 3.7918 |
411
+ | 0.27 | 362.0 | 45250 | 3.7870 |
412
+ | 0.2841 | 363.0 | 45375 | 3.7675 |
413
+ | 0.2776 | 364.0 | 45500 | 3.7090 |
414
+ | 0.2752 | 365.0 | 45625 | 3.6754 |
415
+ | 0.2727 | 366.0 | 45750 | 3.6542 |
416
+ | 0.2423 | 367.0 | 45875 | 3.6399 |
417
+ | 0.263 | 368.0 | 46000 | 3.6337 |
418
+ | 0.2562 | 369.0 | 46125 | 3.7343 |
419
+ | 0.2704 | 370.0 | 46250 | 3.6502 |
420
+ | 0.2604 | 371.0 | 46375 | 3.7519 |
421
+ | 0.2312 | 372.0 | 46500 | 3.7563 |
422
+ | 0.2761 | 373.0 | 46625 | 3.6497 |
423
+ | 0.265 | 374.0 | 46750 | 3.7312 |
424
+ | 0.2545 | 375.0 | 46875 | 3.7273 |
425
+ | 0.2551 | 376.0 | 47000 | 3.8266 |
426
+ | 0.2604 | 377.0 | 47125 | 3.7659 |
427
+ | 0.252 | 378.0 | 47250 | 3.8003 |
428
+ | 0.2468 | 379.0 | 47375 | 3.7535 |
429
+ | 0.289 | 380.0 | 47500 | 3.7376 |
430
+ | 0.2449 | 381.0 | 47625 | 3.7216 |
431
+ | 0.2471 | 382.0 | 47750 | 3.7704 |
432
+ | 0.2627 | 383.0 | 47875 | 3.7510 |
433
+ | 0.2454 | 384.0 | 48000 | 3.8007 |
434
+ | 0.2391 | 385.0 | 48125 | 3.7535 |
435
+ | 0.2452 | 386.0 | 48250 | 3.7905 |
436
+ | 0.2608 | 387.0 | 48375 | 3.8170 |
437
+ | 0.2662 | 388.0 | 48500 | 3.7836 |
438
+ | 0.235 | 389.0 | 48625 | 3.7754 |
439
+ | 0.2425 | 390.0 | 48750 | 3.7201 |
440
+ | 0.2463 | 391.0 | 48875 | 3.8298 |
441
+ | 0.2507 | 392.0 | 49000 | 3.8252 |
442
+ | 0.2451 | 393.0 | 49125 | 3.7625 |
443
+ | 0.2418 | 394.0 | 49250 | 3.7482 |
444
+ | 0.2397 | 395.0 | 49375 | 3.7875 |
445
+ | 0.2773 | 396.0 | 49500 | 3.8159 |
446
+ | 0.256 | 397.0 | 49625 | 3.8322 |
447
+ | 0.2304 | 398.0 | 49750 | 3.8012 |
448
+ | 0.2363 | 399.0 | 49875 | 3.8033 |
449
+ | 0.2575 | 400.0 | 50000 | 3.7727 |
450
 
451
 
452
  ### Framework versions
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:5e76c520626216fa3a6b7910a669d61db7e2179821dac10f9c23c733dba3e9c1
3
  size 166498936
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9fc97db52994d4d294f68900d4ec14c515704e4440c03bb48fab9fff8a7bcf60
3
  size 166498936
training_args.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:e5609f69cb5d27d56f7f9fde3e0ef3f84df65ca3db94c27b05c90b1ea8e32b27
3
  size 4728
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:777449595f25b73418557bd8ff15d7c4fd101dc7cfab931cef077c1e768771a2
3
  size 4728