tinutmap commited on
Commit
b88c796
·
verified ·
1 Parent(s): 8636a7a

End of training

Browse files
Files changed (2) hide show
  1. README.md +102 -102
  2. model.safetensors +1 -1
README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
17
 
18
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
19
  It achieves the following results on the evaluation set:
20
- - Loss: 0.5024
21
- - Accuracy: 0.8778
22
 
23
  ## Model description
24
 
@@ -49,106 +49,106 @@ The following hyperparameters were used during training:
49
 
50
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
51
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
52
- | No log | 1.0 | 13 | 2.3799 | 0.4556 |
53
- | No log | 2.0 | 26 | 2.0506 | 0.6889 |
54
- | No log | 3.0 | 39 | 1.7473 | 0.7778 |
55
- | No log | 4.0 | 52 | 1.4873 | 0.7889 |
56
- | No log | 5.0 | 65 | 1.2484 | 0.7778 |
57
- | No log | 6.0 | 78 | 1.0468 | 0.8444 |
58
- | No log | 7.0 | 91 | 0.9031 | 0.8444 |
59
- | No log | 8.0 | 104 | 0.7793 | 0.8556 |
60
- | No log | 9.0 | 117 | 0.7284 | 0.8444 |
61
- | No log | 10.0 | 130 | 0.6379 | 0.8333 |
62
- | No log | 11.0 | 143 | 0.5547 | 0.8556 |
63
- | No log | 12.0 | 156 | 0.5551 | 0.8556 |
64
- | No log | 13.0 | 169 | 0.4907 | 0.8556 |
65
- | No log | 14.0 | 182 | 0.5155 | 0.8556 |
66
- | No log | 15.0 | 195 | 0.4732 | 0.8667 |
67
- | No log | 16.0 | 208 | 0.4599 | 0.8667 |
68
- | No log | 17.0 | 221 | 0.4919 | 0.8556 |
69
- | No log | 18.0 | 234 | 0.4649 | 0.8667 |
70
- | No log | 19.0 | 247 | 0.4718 | 0.8778 |
71
- | No log | 20.0 | 260 | 0.4769 | 0.8667 |
72
- | No log | 21.0 | 273 | 0.4732 | 0.8556 |
73
- | No log | 22.0 | 286 | 0.4587 | 0.8556 |
74
- | No log | 23.0 | 299 | 0.4615 | 0.8667 |
75
- | No log | 24.0 | 312 | 0.4694 | 0.8667 |
76
- | No log | 25.0 | 325 | 0.4666 | 0.8667 |
77
- | No log | 26.0 | 338 | 0.4916 | 0.8556 |
78
- | No log | 27.0 | 351 | 0.4907 | 0.8556 |
79
- | No log | 28.0 | 364 | 0.4886 | 0.8667 |
80
- | No log | 29.0 | 377 | 0.4891 | 0.8667 |
81
- | No log | 30.0 | 390 | 0.4811 | 0.8667 |
82
- | No log | 31.0 | 403 | 0.4628 | 0.8667 |
83
- | No log | 32.0 | 416 | 0.4755 | 0.8667 |
84
- | No log | 33.0 | 429 | 0.4687 | 0.8667 |
85
- | No log | 34.0 | 442 | 0.4633 | 0.8667 |
86
- | No log | 35.0 | 455 | 0.4734 | 0.8667 |
87
- | No log | 36.0 | 468 | 0.4750 | 0.8556 |
88
- | No log | 37.0 | 481 | 0.4763 | 0.8667 |
89
- | No log | 38.0 | 494 | 0.4648 | 0.8667 |
90
- | 0.4152 | 39.0 | 507 | 0.4881 | 0.8556 |
91
- | 0.4152 | 40.0 | 520 | 0.4587 | 0.8778 |
92
- | 0.4152 | 41.0 | 533 | 0.4781 | 0.8556 |
93
- | 0.4152 | 42.0 | 546 | 0.4622 | 0.8778 |
94
- | 0.4152 | 43.0 | 559 | 0.4885 | 0.8667 |
95
- | 0.4152 | 44.0 | 572 | 0.4898 | 0.8667 |
96
- | 0.4152 | 45.0 | 585 | 0.4959 | 0.8667 |
97
- | 0.4152 | 46.0 | 598 | 0.4911 | 0.8667 |
98
- | 0.4152 | 47.0 | 611 | 0.4795 | 0.8667 |
99
- | 0.4152 | 48.0 | 624 | 0.4869 | 0.8667 |
100
- | 0.4152 | 49.0 | 637 | 0.4937 | 0.8667 |
101
- | 0.4152 | 50.0 | 650 | 0.4954 | 0.8667 |
102
- | 0.4152 | 51.0 | 663 | 0.4992 | 0.8667 |
103
- | 0.4152 | 52.0 | 676 | 0.5022 | 0.8667 |
104
- | 0.4152 | 53.0 | 689 | 0.4891 | 0.8778 |
105
- | 0.4152 | 54.0 | 702 | 0.5037 | 0.8667 |
106
- | 0.4152 | 55.0 | 715 | 0.5084 | 0.8667 |
107
- | 0.4152 | 56.0 | 728 | 0.5007 | 0.8667 |
108
- | 0.4152 | 57.0 | 741 | 0.4938 | 0.8778 |
109
- | 0.4152 | 58.0 | 754 | 0.4899 | 0.8778 |
110
- | 0.4152 | 59.0 | 767 | 0.4952 | 0.8667 |
111
- | 0.4152 | 60.0 | 780 | 0.4916 | 0.8778 |
112
- | 0.4152 | 61.0 | 793 | 0.4947 | 0.8778 |
113
- | 0.4152 | 62.0 | 806 | 0.4890 | 0.8778 |
114
- | 0.4152 | 63.0 | 819 | 0.4863 | 0.8778 |
115
- | 0.4152 | 64.0 | 832 | 0.4887 | 0.8778 |
116
- | 0.4152 | 65.0 | 845 | 0.4946 | 0.8778 |
117
- | 0.4152 | 66.0 | 858 | 0.4961 | 0.8778 |
118
- | 0.4152 | 67.0 | 871 | 0.4947 | 0.8778 |
119
- | 0.4152 | 68.0 | 884 | 0.4940 | 0.8778 |
120
- | 0.4152 | 69.0 | 897 | 0.4927 | 0.8778 |
121
- | 0.4152 | 70.0 | 910 | 0.4930 | 0.8667 |
122
- | 0.4152 | 71.0 | 923 | 0.4998 | 0.8778 |
123
- | 0.4152 | 72.0 | 936 | 0.5011 | 0.8778 |
124
- | 0.4152 | 73.0 | 949 | 0.5031 | 0.8778 |
125
- | 0.4152 | 74.0 | 962 | 0.5045 | 0.8778 |
126
- | 0.4152 | 75.0 | 975 | 0.5020 | 0.8778 |
127
- | 0.4152 | 76.0 | 988 | 0.5015 | 0.8778 |
128
- | 0.0244 | 77.0 | 1001 | 0.5006 | 0.8778 |
129
- | 0.0244 | 78.0 | 1014 | 0.5018 | 0.8778 |
130
- | 0.0244 | 79.0 | 1027 | 0.5059 | 0.8778 |
131
- | 0.0244 | 80.0 | 1040 | 0.5056 | 0.8778 |
132
- | 0.0244 | 81.0 | 1053 | 0.5033 | 0.8778 |
133
- | 0.0244 | 82.0 | 1066 | 0.5048 | 0.8778 |
134
- | 0.0244 | 83.0 | 1079 | 0.5036 | 0.8778 |
135
- | 0.0244 | 84.0 | 1092 | 0.5043 | 0.8778 |
136
- | 0.0244 | 85.0 | 1105 | 0.5069 | 0.8778 |
137
- | 0.0244 | 86.0 | 1118 | 0.5073 | 0.8778 |
138
- | 0.0244 | 87.0 | 1131 | 0.5049 | 0.8778 |
139
- | 0.0244 | 88.0 | 1144 | 0.5026 | 0.8778 |
140
- | 0.0244 | 89.0 | 1157 | 0.5027 | 0.8778 |
141
- | 0.0244 | 90.0 | 1170 | 0.5040 | 0.8778 |
142
- | 0.0244 | 91.0 | 1183 | 0.5041 | 0.8778 |
143
- | 0.0244 | 92.0 | 1196 | 0.5029 | 0.8778 |
144
- | 0.0244 | 93.0 | 1209 | 0.5027 | 0.8778 |
145
- | 0.0244 | 94.0 | 1222 | 0.5023 | 0.8778 |
146
- | 0.0244 | 95.0 | 1235 | 0.5023 | 0.8778 |
147
- | 0.0244 | 96.0 | 1248 | 0.5024 | 0.8778 |
148
- | 0.0244 | 97.0 | 1261 | 0.5028 | 0.8778 |
149
- | 0.0244 | 98.0 | 1274 | 0.5027 | 0.8778 |
150
- | 0.0244 | 99.0 | 1287 | 0.5025 | 0.8778 |
151
- | 0.0244 | 100.0 | 1300 | 0.5024 | 0.8778 |
152
 
153
 
154
  ### Framework versions
 
17
 
18
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
19
  It achieves the following results on the evaluation set:
20
+ - Loss: 0.6307
21
+ - Accuracy: 0.8901
22
 
23
  ## Model description
24
 
 
49
 
50
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
51
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
52
+ | No log | 1.0 | 14 | 2.4323 | 0.4615 |
53
+ | No log | 2.0 | 28 | 2.0883 | 0.5495 |
54
+ | No log | 3.0 | 42 | 1.7465 | 0.7033 |
55
+ | No log | 4.0 | 56 | 1.4428 | 0.7363 |
56
+ | No log | 5.0 | 70 | 1.1838 | 0.8242 |
57
+ | No log | 6.0 | 84 | 0.9881 | 0.8132 |
58
+ | No log | 7.0 | 98 | 0.8446 | 0.8571 |
59
+ | No log | 8.0 | 112 | 0.7304 | 0.8791 |
60
+ | No log | 9.0 | 126 | 0.6456 | 0.8681 |
61
+ | No log | 10.0 | 140 | 0.6267 | 0.8352 |
62
+ | No log | 11.0 | 154 | 0.5656 | 0.8791 |
63
+ | No log | 12.0 | 168 | 0.5412 | 0.8901 |
64
+ | No log | 13.0 | 182 | 0.5301 | 0.8901 |
65
+ | No log | 14.0 | 196 | 0.5190 | 0.8791 |
66
+ | No log | 15.0 | 210 | 0.5175 | 0.8901 |
67
+ | No log | 16.0 | 224 | 0.5295 | 0.8681 |
68
+ | No log | 17.0 | 238 | 0.5147 | 0.8901 |
69
+ | No log | 18.0 | 252 | 0.5094 | 0.8901 |
70
+ | No log | 19.0 | 266 | 0.5130 | 0.8791 |
71
+ | No log | 20.0 | 280 | 0.5212 | 0.8901 |
72
+ | No log | 21.0 | 294 | 0.5421 | 0.8791 |
73
+ | No log | 22.0 | 308 | 0.5439 | 0.8791 |
74
+ | No log | 23.0 | 322 | 0.5516 | 0.8791 |
75
+ | No log | 24.0 | 336 | 0.5544 | 0.8791 |
76
+ | No log | 25.0 | 350 | 0.5441 | 0.8901 |
77
+ | No log | 26.0 | 364 | 0.5497 | 0.8901 |
78
+ | No log | 27.0 | 378 | 0.5502 | 0.8791 |
79
+ | No log | 28.0 | 392 | 0.5345 | 0.8901 |
80
+ | No log | 29.0 | 406 | 0.5444 | 0.8901 |
81
+ | No log | 30.0 | 420 | 0.5489 | 0.8901 |
82
+ | No log | 31.0 | 434 | 0.5838 | 0.8681 |
83
+ | No log | 32.0 | 448 | 0.5444 | 0.9011 |
84
+ | No log | 33.0 | 462 | 0.6005 | 0.8681 |
85
+ | No log | 34.0 | 476 | 0.5633 | 0.8901 |
86
+ | No log | 35.0 | 490 | 0.5701 | 0.8791 |
87
+ | 0.4178 | 36.0 | 504 | 0.5805 | 0.8901 |
88
+ | 0.4178 | 37.0 | 518 | 0.5919 | 0.8791 |
89
+ | 0.4178 | 38.0 | 532 | 0.5729 | 0.8901 |
90
+ | 0.4178 | 39.0 | 546 | 0.5805 | 0.8901 |
91
+ | 0.4178 | 40.0 | 560 | 0.5940 | 0.8901 |
92
+ | 0.4178 | 41.0 | 574 | 0.5816 | 0.8901 |
93
+ | 0.4178 | 42.0 | 588 | 0.5754 | 0.8901 |
94
+ | 0.4178 | 43.0 | 602 | 0.5838 | 0.8901 |
95
+ | 0.4178 | 44.0 | 616 | 0.5901 | 0.8901 |
96
+ | 0.4178 | 45.0 | 630 | 0.5942 | 0.8901 |
97
+ | 0.4178 | 46.0 | 644 | 0.5922 | 0.8901 |
98
+ | 0.4178 | 47.0 | 658 | 0.5908 | 0.8901 |
99
+ | 0.4178 | 48.0 | 672 | 0.5921 | 0.8901 |
100
+ | 0.4178 | 49.0 | 686 | 0.5916 | 0.8901 |
101
+ | 0.4178 | 50.0 | 700 | 0.6024 | 0.8901 |
102
+ | 0.4178 | 51.0 | 714 | 0.6012 | 0.8901 |
103
+ | 0.4178 | 52.0 | 728 | 0.5998 | 0.8901 |
104
+ | 0.4178 | 53.0 | 742 | 0.6031 | 0.8901 |
105
+ | 0.4178 | 54.0 | 756 | 0.5967 | 0.8901 |
106
+ | 0.4178 | 55.0 | 770 | 0.5950 | 0.8901 |
107
+ | 0.4178 | 56.0 | 784 | 0.6018 | 0.8901 |
108
+ | 0.4178 | 57.0 | 798 | 0.5989 | 0.8901 |
109
+ | 0.4178 | 58.0 | 812 | 0.5945 | 0.8901 |
110
+ | 0.4178 | 59.0 | 826 | 0.5948 | 0.8901 |
111
+ | 0.4178 | 60.0 | 840 | 0.5930 | 0.8901 |
112
+ | 0.4178 | 61.0 | 854 | 0.5961 | 0.8901 |
113
+ | 0.4178 | 62.0 | 868 | 0.6010 | 0.8901 |
114
+ | 0.4178 | 63.0 | 882 | 0.5973 | 0.8901 |
115
+ | 0.4178 | 64.0 | 896 | 0.5997 | 0.8901 |
116
+ | 0.4178 | 65.0 | 910 | 0.6016 | 0.8901 |
117
+ | 0.4178 | 66.0 | 924 | 0.6069 | 0.8901 |
118
+ | 0.4178 | 67.0 | 938 | 0.6095 | 0.8901 |
119
+ | 0.4178 | 68.0 | 952 | 0.6117 | 0.8901 |
120
+ | 0.4178 | 69.0 | 966 | 0.6160 | 0.8901 |
121
+ | 0.4178 | 70.0 | 980 | 0.6166 | 0.8901 |
122
+ | 0.4178 | 71.0 | 994 | 0.6177 | 0.8901 |
123
+ | 0.0153 | 72.0 | 1008 | 0.6172 | 0.8901 |
124
+ | 0.0153 | 73.0 | 1022 | 0.6190 | 0.8901 |
125
+ | 0.0153 | 74.0 | 1036 | 0.6213 | 0.8901 |
126
+ | 0.0153 | 75.0 | 1050 | 0.6220 | 0.8901 |
127
+ | 0.0153 | 76.0 | 1064 | 0.6204 | 0.8901 |
128
+ | 0.0153 | 77.0 | 1078 | 0.6193 | 0.8901 |
129
+ | 0.0153 | 78.0 | 1092 | 0.6198 | 0.8901 |
130
+ | 0.0153 | 79.0 | 1106 | 0.6235 | 0.8901 |
131
+ | 0.0153 | 80.0 | 1120 | 0.6260 | 0.8901 |
132
+ | 0.0153 | 81.0 | 1134 | 0.6271 | 0.8901 |
133
+ | 0.0153 | 82.0 | 1148 | 0.6290 | 0.8901 |
134
+ | 0.0153 | 83.0 | 1162 | 0.6288 | 0.8901 |
135
+ | 0.0153 | 84.0 | 1176 | 0.6298 | 0.8901 |
136
+ | 0.0153 | 85.0 | 1190 | 0.6301 | 0.8901 |
137
+ | 0.0153 | 86.0 | 1204 | 0.6324 | 0.8901 |
138
+ | 0.0153 | 87.0 | 1218 | 0.6332 | 0.8901 |
139
+ | 0.0153 | 88.0 | 1232 | 0.6333 | 0.8901 |
140
+ | 0.0153 | 89.0 | 1246 | 0.6347 | 0.8901 |
141
+ | 0.0153 | 90.0 | 1260 | 0.6337 | 0.8901 |
142
+ | 0.0153 | 91.0 | 1274 | 0.6332 | 0.8901 |
143
+ | 0.0153 | 92.0 | 1288 | 0.6329 | 0.8901 |
144
+ | 0.0153 | 93.0 | 1302 | 0.6316 | 0.8901 |
145
+ | 0.0153 | 94.0 | 1316 | 0.6315 | 0.8901 |
146
+ | 0.0153 | 95.0 | 1330 | 0.6312 | 0.8901 |
147
+ | 0.0153 | 96.0 | 1344 | 0.6310 | 0.8901 |
148
+ | 0.0153 | 97.0 | 1358 | 0.6305 | 0.8901 |
149
+ | 0.0153 | 98.0 | 1372 | 0.6306 | 0.8901 |
150
+ | 0.0153 | 99.0 | 1386 | 0.6307 | 0.8901 |
151
+ | 0.0153 | 100.0 | 1400 | 0.6307 | 0.8901 |
152
 
153
 
154
  ### Framework versions
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:7855362bf3543bd5da2b231d918c475ba583c93e749b56a1ba32b3e7ab7a036f
3
  size 267872556
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6a0bc9bae848d97f2037ccc6890c4a224a43f1a2b975e5749a7ba980bc162fc1
3
  size 267872556