Arthur-Tsai commited on
Commit
59754e6
·
verified ·
1 Parent(s): e5da469

End of training

Browse files
README.md ADDED
@@ -0,0 +1,299 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: transformers
3
+ tags:
4
+ - generated_from_trainer
5
+ metrics:
6
+ - accuracy
7
+ model-index:
8
+ - name: ht-stmini-cls-v5_ftis_noPretrain_tdso-smlo
9
+ results: []
10
+ ---
11
+
12
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
13
+ should probably proofread and complete it, then remove this comment. -->
14
+
15
+ # ht-stmini-cls-v5_ftis_noPretrain_tdso-smlo
16
+
17
+ This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
18
+ It achieves the following results on the evaluation set:
19
+ - Loss: 1.1151
20
+ - Accuracy: 0.9320
21
+ - Macro F1: 0.8258
22
+
23
+ ## Model description
24
+
25
+ More information needed
26
+
27
+ ## Intended uses & limitations
28
+
29
+ More information needed
30
+
31
+ ## Training and evaluation data
32
+
33
+ More information needed
34
+
35
+ ## Training procedure
36
+
37
+ ### Training hyperparameters
38
+
39
+ The following hyperparameters were used during training:
40
+ - learning_rate: 0.0001
41
+ - train_batch_size: 8
42
+ - eval_batch_size: 4
43
+ - seed: 42
44
+ - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
45
+ - lr_scheduler_type: linear
46
+ - lr_scheduler_warmup_steps: 6731
47
+ - training_steps: 134625
48
+
49
+ ### Training results
50
+
51
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 |
52
+ |:-------------:|:--------:|:-----:|:---------------:|:--------:|:--------:|
53
+ | 53.4294 | 0.0010 | 134 | 34.6494 | 0.0667 | 0.0319 |
54
+ | 27.1497 | 1.0010 | 268 | 14.9694 | 0.1124 | 0.0435 |
55
+ | 11.4988 | 2.0010 | 402 | 8.7507 | 0.3848 | 0.1041 |
56
+ | 8.2304 | 3.0010 | 536 | 7.7151 | 0.5117 | 0.1290 |
57
+ | 6.9053 | 4.0010 | 670 | 6.3015 | 0.5500 | 0.1401 |
58
+ | 5.9401 | 5.0010 | 804 | 5.5511 | 0.5709 | 0.1448 |
59
+ | 5.8426 | 6.0010 | 938 | 5.1179 | 0.5805 | 0.1487 |
60
+ | 4.9057 | 7.0009 | 1072 | 4.6319 | 0.6034 | 0.1605 |
61
+ | 4.3755 | 8.0009 | 1206 | 4.2476 | 0.6094 | 0.1684 |
62
+ | 4.0038 | 9.0009 | 1340 | 3.4130 | 0.6088 | 0.1569 |
63
+ | 3.4542 | 10.0009 | 1474 | 3.0477 | 0.6195 | 0.1664 |
64
+ | 3.1845 | 11.0009 | 1608 | 2.8463 | 0.6278 | 0.1863 |
65
+ | 2.9389 | 12.0009 | 1742 | 2.6226 | 0.6307 | 0.1944 |
66
+ | 2.9131 | 13.0009 | 1876 | 2.4606 | 0.6396 | 0.1897 |
67
+ | 2.7358 | 14.0009 | 2010 | 2.4721 | 0.6218 | 0.2053 |
68
+ | 2.7215 | 15.0009 | 2144 | 2.4285 | 0.6480 | 0.2185 |
69
+ | 2.4832 | 16.0009 | 2278 | 2.3308 | 0.6637 | 0.2434 |
70
+ | 2.4528 | 17.0009 | 2412 | 2.2547 | 0.6668 | 0.2532 |
71
+ | 2.3856 | 18.0009 | 2546 | 2.1757 | 0.6789 | 0.2821 |
72
+ | 2.2985 | 19.0009 | 2680 | 2.1081 | 0.6856 | 0.2947 |
73
+ | 2.2384 | 20.0008 | 2814 | 2.0189 | 0.6922 | 0.3071 |
74
+ | 2.1385 | 21.0008 | 2948 | 2.0347 | 0.6997 | 0.3131 |
75
+ | 2.0597 | 22.0008 | 3082 | 1.9363 | 0.7205 | 0.3373 |
76
+ | 1.9989 | 23.0008 | 3216 | 1.7928 | 0.7452 | 0.3727 |
77
+ | 1.8912 | 24.0008 | 3350 | 1.9196 | 0.7230 | 0.3659 |
78
+ | 1.8667 | 25.0008 | 3484 | 1.6743 | 0.7625 | 0.4069 |
79
+ | 1.7777 | 26.0008 | 3618 | 1.8150 | 0.7452 | 0.3782 |
80
+ | 1.6585 | 27.0008 | 3752 | 1.6782 | 0.7641 | 0.4010 |
81
+ | 1.5835 | 28.0008 | 3886 | 1.6307 | 0.7721 | 0.4364 |
82
+ | 1.5667 | 29.0008 | 4020 | 1.5599 | 0.7769 | 0.4518 |
83
+ | 1.5673 | 30.0008 | 4154 | 1.5360 | 0.7911 | 0.4755 |
84
+ | 1.4489 | 31.0008 | 4288 | 1.5137 | 0.7929 | 0.4647 |
85
+ | 1.4655 | 32.0008 | 4422 | 1.5320 | 0.7870 | 0.4747 |
86
+ | 1.3252 | 33.0008 | 4556 | 1.4500 | 0.8012 | 0.5054 |
87
+ | 1.3265 | 34.0007 | 4690 | 1.4675 | 0.8036 | 0.4968 |
88
+ | 1.2351 | 35.0007 | 4824 | 1.4150 | 0.8004 | 0.5250 |
89
+ | 1.2036 | 36.0007 | 4958 | 1.3264 | 0.8182 | 0.5174 |
90
+ | 1.1382 | 37.0007 | 5092 | 1.4109 | 0.8128 | 0.5266 |
91
+ | 1.1204 | 38.0007 | 5226 | 1.3105 | 0.8167 | 0.5397 |
92
+ | 1.1486 | 39.0007 | 5360 | 1.3909 | 0.8127 | 0.5405 |
93
+ | 1.0017 | 40.0007 | 5494 | 1.3912 | 0.8130 | 0.5574 |
94
+ | 1.051 | 41.0007 | 5628 | 1.3473 | 0.8193 | 0.5604 |
95
+ | 0.9848 | 42.0007 | 5762 | 1.3315 | 0.8302 | 0.5642 |
96
+ | 0.9754 | 43.0007 | 5896 | 1.2328 | 0.8360 | 0.5817 |
97
+ | 0.9222 | 44.0007 | 6030 | 1.2581 | 0.8337 | 0.5892 |
98
+ | 0.8774 | 45.0007 | 6164 | 1.3153 | 0.8289 | 0.5818 |
99
+ | 0.8709 | 46.0007 | 6298 | 1.2076 | 0.8448 | 0.6071 |
100
+ | 0.8298 | 47.0006 | 6432 | 1.2248 | 0.8441 | 0.5986 |
101
+ | 0.8274 | 48.0006 | 6566 | 1.2188 | 0.8481 | 0.6043 |
102
+ | 0.8153 | 49.0006 | 6700 | 1.1726 | 0.8516 | 0.6109 |
103
+ | 0.7686 | 50.0006 | 6834 | 1.1695 | 0.8537 | 0.6131 |
104
+ | 0.7466 | 51.0006 | 6968 | 1.1868 | 0.8513 | 0.6055 |
105
+ | 0.7249 | 52.0006 | 7102 | 1.1415 | 0.8540 | 0.6285 |
106
+ | 0.6858 | 53.0006 | 7236 | 1.1724 | 0.8597 | 0.6287 |
107
+ | 0.6782 | 54.0006 | 7370 | 1.1728 | 0.8551 | 0.6400 |
108
+ | 0.6867 | 55.0006 | 7504 | 1.1532 | 0.8634 | 0.6561 |
109
+ | 0.6371 | 56.0006 | 7638 | 1.1081 | 0.8695 | 0.6541 |
110
+ | 0.6353 | 57.0006 | 7772 | 1.1107 | 0.8736 | 0.6568 |
111
+ | 0.6087 | 58.0006 | 7906 | 1.0870 | 0.8722 | 0.6631 |
112
+ | 0.5978 | 59.0006 | 8040 | 1.1551 | 0.8722 | 0.6536 |
113
+ | 0.5868 | 60.0005 | 8174 | 1.0833 | 0.8788 | 0.6698 |
114
+ | 0.5694 | 61.0005 | 8308 | 1.1657 | 0.8765 | 0.6782 |
115
+ | 0.5486 | 62.0005 | 8442 | 1.1373 | 0.8759 | 0.6629 |
116
+ | 0.5428 | 63.0005 | 8576 | 1.0265 | 0.8849 | 0.6842 |
117
+ | 0.5216 | 64.0005 | 8710 | 1.0735 | 0.8845 | 0.6859 |
118
+ | 0.5228 | 65.0005 | 8844 | 1.0677 | 0.8861 | 0.6935 |
119
+ | 0.5154 | 66.0005 | 8978 | 1.1307 | 0.8845 | 0.6884 |
120
+ | 0.4861 | 67.0005 | 9112 | 1.0339 | 0.8826 | 0.6980 |
121
+ | 0.5013 | 68.0005 | 9246 | 0.9976 | 0.8901 | 0.7070 |
122
+ | 0.4786 | 69.0005 | 9380 | 1.0301 | 0.8863 | 0.6976 |
123
+ | 0.4642 | 70.0005 | 9514 | 1.0534 | 0.8921 | 0.7095 |
124
+ | 0.4686 | 71.0005 | 9648 | 1.1015 | 0.8927 | 0.7112 |
125
+ | 0.446 | 72.0005 | 9782 | 1.0751 | 0.8891 | 0.7059 |
126
+ | 0.4467 | 73.0005 | 9916 | 1.0255 | 0.8926 | 0.7140 |
127
+ | 0.4475 | 74.0004 | 10050 | 1.0032 | 0.8954 | 0.7105 |
128
+ | 0.4263 | 75.0004 | 10184 | 0.9607 | 0.8905 | 0.7185 |
129
+ | 0.4207 | 76.0004 | 10318 | 1.0544 | 0.8948 | 0.7179 |
130
+ | 0.4164 | 77.0004 | 10452 | 1.1040 | 0.8976 | 0.7241 |
131
+ | 0.4075 | 78.0004 | 10586 | 1.0797 | 0.8966 | 0.7258 |
132
+ | 0.3991 | 79.0004 | 10720 | 1.0864 | 0.8974 | 0.7195 |
133
+ | 0.3897 | 80.0004 | 10854 | 1.0940 | 0.8983 | 0.7303 |
134
+ | 0.398 | 81.0004 | 10988 | 1.0326 | 0.8981 | 0.7299 |
135
+ | 0.3807 | 82.0004 | 11122 | 1.1258 | 0.8980 | 0.7175 |
136
+ | 0.3804 | 83.0004 | 11256 | 1.0126 | 0.9011 | 0.7295 |
137
+ | 0.3888 | 84.0004 | 11390 | 0.9941 | 0.9011 | 0.7402 |
138
+ | 0.3746 | 85.0004 | 11524 | 1.0302 | 0.9035 | 0.7452 |
139
+ | 0.3667 | 86.0004 | 11658 | 1.0306 | 0.9061 | 0.7419 |
140
+ | 0.3749 | 87.0003 | 11792 | 1.0660 | 0.9052 | 0.7409 |
141
+ | 0.3658 | 88.0003 | 11926 | 0.9591 | 0.9078 | 0.7439 |
142
+ | 0.3515 | 89.0003 | 12060 | 0.9417 | 0.9089 | 0.7451 |
143
+ | 0.3501 | 90.0003 | 12194 | 1.0079 | 0.9060 | 0.7475 |
144
+ | 0.3525 | 91.0003 | 12328 | 1.0466 | 0.9083 | 0.7492 |
145
+ | 0.3464 | 92.0003 | 12462 | 1.0299 | 0.9081 | 0.7462 |
146
+ | 0.3413 | 93.0003 | 12596 | 0.9978 | 0.9110 | 0.7556 |
147
+ | 0.3494 | 94.0003 | 12730 | 1.1079 | 0.9081 | 0.7590 |
148
+ | 0.3432 | 95.0003 | 12864 | 0.9787 | 0.9106 | 0.7544 |
149
+ | 0.3399 | 96.0003 | 12998 | 1.0458 | 0.9060 | 0.7514 |
150
+ | 0.3397 | 97.0003 | 13132 | 1.0186 | 0.9076 | 0.7519 |
151
+ | 0.3398 | 98.0003 | 13266 | 1.0323 | 0.9111 | 0.7595 |
152
+ | 0.3296 | 99.0003 | 13400 | 1.0332 | 0.9109 | 0.7660 |
153
+ | 0.3266 | 100.0003 | 13534 | 1.0575 | 0.9105 | 0.7615 |
154
+ | 0.3451 | 101.0002 | 13668 | 1.0218 | 0.9085 | 0.7623 |
155
+ | 0.3187 | 102.0002 | 13802 | 1.0354 | 0.9135 | 0.7672 |
156
+ | 0.3257 | 103.0002 | 13936 | 0.9968 | 0.9150 | 0.7679 |
157
+ | 0.3154 | 104.0002 | 14070 | 1.0238 | 0.9144 | 0.7640 |
158
+ | 0.3176 | 105.0002 | 14204 | 1.0824 | 0.9141 | 0.7705 |
159
+ | 0.3172 | 106.0002 | 14338 | 1.0311 | 0.9155 | 0.7713 |
160
+ | 0.3121 | 107.0002 | 14472 | 1.0403 | 0.9150 | 0.7717 |
161
+ | 0.3185 | 108.0002 | 14606 | 1.0869 | 0.9180 | 0.7728 |
162
+ | 0.3076 | 109.0002 | 14740 | 1.0839 | 0.9168 | 0.7729 |
163
+ | 0.3147 | 110.0002 | 14874 | 1.0488 | 0.9177 | 0.7754 |
164
+ | 0.3109 | 111.0002 | 15008 | 1.0400 | 0.9171 | 0.7785 |
165
+ | 0.3179 | 112.0002 | 15142 | 1.0723 | 0.9159 | 0.7746 |
166
+ | 0.3061 | 113.0002 | 15276 | 1.0431 | 0.9134 | 0.7723 |
167
+ | 0.3152 | 114.0001 | 15410 | 1.0751 | 0.9140 | 0.7725 |
168
+ | 0.3093 | 115.0001 | 15544 | 0.9621 | 0.9198 | 0.7848 |
169
+ | 0.3025 | 116.0001 | 15678 | 1.0381 | 0.9183 | 0.7811 |
170
+ | 0.3 | 117.0001 | 15812 | 1.0633 | 0.9156 | 0.7735 |
171
+ | 0.3002 | 118.0001 | 15946 | 1.0692 | 0.9205 | 0.7816 |
172
+ | 0.3013 | 119.0001 | 16080 | 0.9795 | 0.9185 | 0.7809 |
173
+ | 0.2972 | 120.0001 | 16214 | 1.0215 | 0.9197 | 0.7789 |
174
+ | 0.2977 | 121.0001 | 16348 | 1.1028 | 0.9163 | 0.7784 |
175
+ | 0.2938 | 122.0001 | 16482 | 1.0413 | 0.9181 | 0.7809 |
176
+ | 0.2915 | 123.0001 | 16616 | 1.0661 | 0.9221 | 0.7856 |
177
+ | 0.291 | 124.0001 | 16750 | 0.9958 | 0.9204 | 0.7880 |
178
+ | 0.2904 | 125.0001 | 16884 | 1.0781 | 0.9185 | 0.7780 |
179
+ | 0.291 | 126.0001 | 17018 | 1.0248 | 0.9216 | 0.7892 |
180
+ | 0.2923 | 127.0001 | 17152 | 1.0341 | 0.9211 | 0.7850 |
181
+ | 0.2905 | 128.0000 | 17286 | 0.9978 | 0.9198 | 0.7882 |
182
+ | 0.2831 | 129.0000 | 17420 | 1.0524 | 0.9192 | 0.7883 |
183
+ | 0.2861 | 130.0000 | 17554 | 1.0516 | 0.9182 | 0.7891 |
184
+ | 0.2835 | 131.0000 | 17688 | 1.0511 | 0.9208 | 0.7898 |
185
+ | 0.2845 | 132.0000 | 17822 | 1.0037 | 0.9222 | 0.7926 |
186
+ | 0.2802 | 133.0000 | 17956 | 1.0668 | 0.9208 | 0.7933 |
187
+ | 0.2832 | 133.0010 | 18090 | 0.9618 | 0.9247 | 0.7983 |
188
+ | 0.2797 | 134.0010 | 18224 | 1.0268 | 0.9213 | 0.7893 |
189
+ | 0.2835 | 135.0010 | 18358 | 1.0142 | 0.9247 | 0.7927 |
190
+ | 0.2763 | 136.0010 | 18492 | 1.0004 | 0.9219 | 0.7940 |
191
+ | 0.2828 | 137.0010 | 18626 | 1.0009 | 0.9226 | 0.7948 |
192
+ | 0.2797 | 138.0010 | 18760 | 1.0596 | 0.9189 | 0.7928 |
193
+ | 0.2777 | 139.0010 | 18894 | 1.0930 | 0.9193 | 0.7907 |
194
+ | 0.277 | 140.0010 | 19028 | 1.0537 | 0.9215 | 0.7912 |
195
+ | 0.2711 | 141.0009 | 19162 | 1.0998 | 0.9205 | 0.7921 |
196
+ | 0.2727 | 142.0009 | 19296 | 0.9981 | 0.9251 | 0.8002 |
197
+ | 0.2735 | 143.0009 | 19430 | 1.0946 | 0.9244 | 0.7980 |
198
+ | 0.2773 | 144.0009 | 19564 | 1.0148 | 0.9214 | 0.7896 |
199
+ | 0.2755 | 145.0009 | 19698 | 1.0633 | 0.9204 | 0.7959 |
200
+ | 0.2741 | 146.0009 | 19832 | 1.0738 | 0.9225 | 0.7931 |
201
+ | 0.274 | 147.0009 | 19966 | 1.0521 | 0.9247 | 0.7982 |
202
+ | 0.2713 | 148.0009 | 20100 | 1.0310 | 0.9245 | 0.7997 |
203
+ | 0.2675 | 149.0009 | 20234 | 1.0098 | 0.9240 | 0.7978 |
204
+ | 0.2675 | 150.0009 | 20368 | 1.0380 | 0.9223 | 0.7922 |
205
+ | 0.2705 | 151.0009 | 20502 | 1.0536 | 0.9217 | 0.7931 |
206
+ | 0.2716 | 152.0009 | 20636 | 0.9678 | 0.9236 | 0.8040 |
207
+ | 0.2702 | 153.0009 | 20770 | 1.0847 | 0.9226 | 0.8039 |
208
+ | 0.2694 | 154.0008 | 20904 | 0.9990 | 0.9261 | 0.8047 |
209
+ | 0.2683 | 155.0008 | 21038 | 0.9972 | 0.9271 | 0.8057 |
210
+ | 0.2663 | 156.0008 | 21172 | 1.0734 | 0.9256 | 0.8045 |
211
+ | 0.2697 | 157.0008 | 21306 | 1.0862 | 0.9256 | 0.8029 |
212
+ | 0.2644 | 158.0008 | 21440 | 1.1121 | 0.9262 | 0.8039 |
213
+ | 0.2681 | 159.0008 | 21574 | 1.0425 | 0.9251 | 0.8029 |
214
+ | 0.2647 | 160.0008 | 21708 | 1.0396 | 0.9261 | 0.8020 |
215
+ | 0.2658 | 161.0008 | 21842 | 1.0132 | 0.9233 | 0.8022 |
216
+ | 0.262 | 162.0008 | 21976 | 1.0660 | 0.9273 | 0.8035 |
217
+ | 0.2593 | 163.0008 | 22110 | 1.0056 | 0.9282 | 0.8101 |
218
+ | 0.2685 | 164.0008 | 22244 | 1.0320 | 0.9288 | 0.8080 |
219
+ | 0.2649 | 165.0008 | 22378 | 1.0231 | 0.9285 | 0.8100 |
220
+ | 0.2623 | 166.0008 | 22512 | 1.0400 | 0.9279 | 0.8067 |
221
+ | 0.2613 | 167.0008 | 22646 | 1.0634 | 0.9224 | 0.8066 |
222
+ | 0.2589 | 168.0007 | 22780 | 1.0589 | 0.9257 | 0.8044 |
223
+ | 0.2599 | 169.0007 | 22914 | 1.0476 | 0.9268 | 0.8082 |
224
+ | 0.2599 | 170.0007 | 23048 | 1.0405 | 0.9281 | 0.8081 |
225
+ | 0.2609 | 171.0007 | 23182 | 1.1016 | 0.9274 | 0.8111 |
226
+ | 0.2553 | 172.0007 | 23316 | 1.0562 | 0.9283 | 0.8128 |
227
+ | 0.2539 | 173.0007 | 23450 | 1.0041 | 0.9295 | 0.8153 |
228
+ | 0.2574 | 174.0007 | 23584 | 0.9900 | 0.9311 | 0.8164 |
229
+ | 0.2559 | 175.0007 | 23718 | 1.1037 | 0.9283 | 0.8134 |
230
+ | 0.2569 | 176.0007 | 23852 | 0.9777 | 0.9305 | 0.8124 |
231
+ | 0.2558 | 177.0007 | 23986 | 1.0454 | 0.9309 | 0.8132 |
232
+ | 0.2593 | 178.0007 | 24120 | 1.0291 | 0.9283 | 0.8109 |
233
+ | 0.2545 | 179.0007 | 24254 | 1.0082 | 0.9295 | 0.8118 |
234
+ | 0.2604 | 180.0007 | 24388 | 0.9476 | 0.9302 | 0.8111 |
235
+ | 0.2516 | 181.0006 | 24522 | 1.0872 | 0.9249 | 0.8037 |
236
+ | 0.2517 | 182.0006 | 24656 | 1.0817 | 0.9289 | 0.8142 |
237
+ | 0.2559 | 183.0006 | 24790 | 0.9947 | 0.9316 | 0.8122 |
238
+ | 0.2506 | 184.0006 | 24924 | 1.0754 | 0.9280 | 0.8143 |
239
+ | 0.2487 | 185.0006 | 25058 | 1.0662 | 0.9309 | 0.8204 |
240
+ | 0.2539 | 186.0006 | 25192 | 0.9953 | 0.9276 | 0.8102 |
241
+ | 0.253 | 187.0006 | 25326 | 1.0346 | 0.9274 | 0.8165 |
242
+ | 0.2514 | 188.0006 | 25460 | 1.0474 | 0.9327 | 0.8177 |
243
+ | 0.2518 | 189.0006 | 25594 | 0.9955 | 0.9293 | 0.8137 |
244
+ | 0.249 | 190.0006 | 25728 | 1.0742 | 0.9281 | 0.8092 |
245
+ | 0.256 | 191.0006 | 25862 | 1.0483 | 0.9253 | 0.8137 |
246
+ | 0.2528 | 192.0006 | 25996 | 1.0245 | 0.9301 | 0.8149 |
247
+ | 0.2514 | 193.0006 | 26130 | 1.1073 | 0.9250 | 0.8115 |
248
+ | 0.2514 | 194.0005 | 26264 | 1.0164 | 0.9286 | 0.8129 |
249
+ | 0.2502 | 195.0005 | 26398 | 1.0373 | 0.9293 | 0.8136 |
250
+ | 0.2506 | 196.0005 | 26532 | 0.9956 | 0.9288 | 0.8146 |
251
+ | 0.25 | 197.0005 | 26666 | 1.0266 | 0.9319 | 0.8206 |
252
+ | 0.2473 | 198.0005 | 26800 | 1.0130 | 0.9341 | 0.8222 |
253
+ | 0.2507 | 199.0005 | 26934 | 1.0242 | 0.9313 | 0.8205 |
254
+ | 0.2496 | 200.0005 | 27068 | 1.0685 | 0.9320 | 0.8195 |
255
+ | 0.2504 | 201.0005 | 27202 | 1.0466 | 0.9309 | 0.8185 |
256
+ | 0.2469 | 202.0005 | 27336 | 0.9906 | 0.9329 | 0.8192 |
257
+ | 0.2503 | 203.0005 | 27470 | 0.9668 | 0.9331 | 0.8185 |
258
+ | 0.2445 | 204.0005 | 27604 | 1.0083 | 0.9347 | 0.8200 |
259
+ | 0.2484 | 205.0005 | 27738 | 1.0224 | 0.9330 | 0.8195 |
260
+ | 0.2453 | 206.0005 | 27872 | 0.9509 | 0.9309 | 0.8181 |
261
+ | 0.2456 | 207.0005 | 28006 | 1.0999 | 0.9318 | 0.8182 |
262
+ | 0.2434 | 208.0004 | 28140 | 1.0461 | 0.9314 | 0.8172 |
263
+ | 0.2424 | 209.0004 | 28274 | 1.0378 | 0.9340 | 0.8189 |
264
+ | 0.2421 | 210.0004 | 28408 | 1.0437 | 0.9324 | 0.8199 |
265
+ | 0.2462 | 211.0004 | 28542 | 1.1065 | 0.9302 | 0.8158 |
266
+ | 0.2445 | 212.0004 | 28676 | 1.1000 | 0.9297 | 0.8138 |
267
+ | 0.2459 | 213.0004 | 28810 | 0.9650 | 0.9322 | 0.8193 |
268
+ | 0.2479 | 214.0004 | 28944 | 1.0826 | 0.9305 | 0.8207 |
269
+ | 0.2467 | 215.0004 | 29078 | 1.0177 | 0.9296 | 0.8172 |
270
+ | 0.2414 | 216.0004 | 29212 | 1.1070 | 0.9323 | 0.8203 |
271
+ | 0.241 | 217.0004 | 29346 | 0.9799 | 0.9342 | 0.8269 |
272
+ | 0.239 | 218.0004 | 29480 | 1.0150 | 0.9338 | 0.8234 |
273
+ | 0.2398 | 219.0004 | 29614 | 1.0282 | 0.9341 | 0.8247 |
274
+ | 0.24 | 220.0004 | 29748 | 1.1072 | 0.9338 | 0.8242 |
275
+ | 0.242 | 221.0003 | 29882 | 1.1370 | 0.9330 | 0.8227 |
276
+ | 0.2387 | 222.0003 | 30016 | 1.0361 | 0.9344 | 0.8234 |
277
+ | 0.2391 | 223.0003 | 30150 | 1.0160 | 0.9340 | 0.8243 |
278
+ | 0.238 | 224.0003 | 30284 | 1.1120 | 0.9303 | 0.8197 |
279
+ | 0.24 | 225.0003 | 30418 | 1.0258 | 0.9341 | 0.8222 |
280
+ | 0.2404 | 226.0003 | 30552 | 1.0780 | 0.9324 | 0.8229 |
281
+ | 0.2398 | 227.0003 | 30686 | 1.0820 | 0.9300 | 0.8218 |
282
+ | 0.2402 | 228.0003 | 30820 | 1.1298 | 0.9298 | 0.8165 |
283
+ | 0.2384 | 229.0003 | 30954 | 1.1296 | 0.9298 | 0.8202 |
284
+ | 0.2388 | 230.0003 | 31088 | 1.0049 | 0.9335 | 0.8233 |
285
+ | 0.2427 | 231.0003 | 31222 | 1.0497 | 0.9327 | 0.8223 |
286
+ | 0.2394 | 232.0003 | 31356 | 1.1404 | 0.9309 | 0.8207 |
287
+ | 0.2374 | 233.0003 | 31490 | 1.0844 | 0.9321 | 0.8196 |
288
+ | 0.242 | 234.0003 | 31624 | 1.0799 | 0.9332 | 0.8262 |
289
+ | 0.2402 | 235.0002 | 31758 | 0.9813 | 0.9359 | 0.8252 |
290
+ | 0.2356 | 236.0002 | 31892 | 1.0763 | 0.9332 | 0.8225 |
291
+ | 0.2381 | 237.0002 | 32026 | 1.0975 | 0.9347 | 0.8254 |
292
+
293
+
294
+ ### Framework versions
295
+
296
+ - Transformers 4.46.0
297
+ - Pytorch 2.3.1+cu121
298
+ - Datasets 2.20.0
299
+ - Tokenizers 0.20.1
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:10385b6f6f6fe6dbe236e0135892c8ee3d638c49c1ccd2f775d4bd5968d60dcf
3
  size 127238056
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:abc6a820da7c5feb377d7eb88d838b0e34ce97dff4b1128780c7ef6e816e1469
3
  size 127238056
runs/0-sample_rate=0.2/events.out.tfevents.1743039828.luna.609863.1 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f20512dbc22568146437bb7e17b894d1055d38b717c530841049fab8a45f54e0
3
+ size 470