Arthur-Tsai commited on
Commit
a7e19e7
·
verified ·
1 Parent(s): cfae2bf

End of training

Browse files
README.md ADDED
@@ -0,0 +1,283 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: transformers
3
+ tags:
4
+ - generated_from_trainer
5
+ metrics:
6
+ - accuracy
7
+ model-index:
8
+ - name: finbertv4_ftis_noPretrain
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
+ # finbertv4_ftis_noPretrain
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: 140.6824
20
+ - Accuracy: 0.9460
21
+ - Macro F1: 0.8637
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
+ | 45.549 | 0.0010 | 134 | 37.7000 | 0.1454 | 0.0430 |
54
+ | 12.1687 | 1.0010 | 268 | 120.4397 | 0.3653 | 0.0979 |
55
+ | 6.8804 | 2.0010 | 402 | 190.1079 | 0.5425 | 0.1458 |
56
+ | 6.0876 | 3.0010 | 536 | 177.8521 | 0.5840 | 0.1758 |
57
+ | 5.3127 | 4.0010 | 670 | 181.0252 | 0.6249 | 0.2063 |
58
+ | 4.4624 | 5.0010 | 804 | 165.3632 | 0.6468 | 0.2158 |
59
+ | 3.8216 | 6.0010 | 938 | 106.9821 | 0.6504 | 0.2401 |
60
+ | 3.0405 | 7.0009 | 1072 | 71.6789 | 0.6904 | 0.2770 |
61
+ | 2.3408 | 8.0009 | 1206 | 45.3098 | 0.6912 | 0.2993 |
62
+ | 2.0837 | 9.0009 | 1340 | 28.4964 | 0.7263 | 0.3498 |
63
+ | 1.7971 | 10.0009 | 1474 | 17.5005 | 0.7597 | 0.3933 |
64
+ | 1.5485 | 11.0009 | 1608 | 10.0478 | 0.7551 | 0.4004 |
65
+ | 1.4729 | 12.0009 | 1742 | 7.6028 | 0.7842 | 0.4397 |
66
+ | 1.3164 | 13.0009 | 1876 | 7.1881 | 0.8088 | 0.4893 |
67
+ | 1.1254 | 14.0009 | 2010 | 4.9870 | 0.8136 | 0.5220 |
68
+ | 1.0691 | 15.0009 | 2144 | 4.3065 | 0.8070 | 0.5180 |
69
+ | 1.1624 | 16.0009 | 2278 | 3.5147 | 0.8304 | 0.5520 |
70
+ | 0.9048 | 17.0009 | 2412 | 3.7801 | 0.8320 | 0.5597 |
71
+ | 0.9057 | 18.0009 | 2546 | 2.9275 | 0.8361 | 0.5762 |
72
+ | 0.903 | 19.0009 | 2680 | 2.5883 | 0.8463 | 0.6073 |
73
+ | 0.7304 | 20.0008 | 2814 | 2.6785 | 0.8540 | 0.6196 |
74
+ | 0.6946 | 21.0008 | 2948 | 2.5038 | 0.8464 | 0.6104 |
75
+ | 0.6078 | 22.0008 | 3082 | 2.3498 | 0.8606 | 0.6291 |
76
+ | 0.6088 | 23.0008 | 3216 | 2.4271 | 0.8530 | 0.6207 |
77
+ | 0.4886 | 24.0008 | 3350 | 2.4903 | 0.8647 | 0.6428 |
78
+ | 0.4934 | 25.0008 | 3484 | 2.5023 | 0.8676 | 0.6451 |
79
+ | 0.4467 | 26.0008 | 3618 | 3.1005 | 0.8743 | 0.6647 |
80
+ | 0.4272 | 27.0008 | 3752 | 2.8655 | 0.8730 | 0.6611 |
81
+ | 0.3755 | 28.0008 | 3886 | 3.4087 | 0.8734 | 0.6698 |
82
+ | 0.3419 | 29.0008 | 4020 | 3.0434 | 0.8803 | 0.6908 |
83
+ | 0.3178 | 30.0008 | 4154 | 4.0369 | 0.8847 | 0.6970 |
84
+ | 0.2935 | 31.0008 | 4288 | 4.9078 | 0.8787 | 0.6848 |
85
+ | 0.2843 | 32.0008 | 4422 | 5.1140 | 0.8852 | 0.6986 |
86
+ | 0.2528 | 33.0008 | 4556 | 5.2650 | 0.8851 | 0.6992 |
87
+ | 0.2419 | 34.0007 | 4690 | 5.6761 | 0.8939 | 0.7100 |
88
+ | 0.2291 | 35.0007 | 4824 | 5.0780 | 0.8919 | 0.7164 |
89
+ | 0.2123 | 36.0007 | 4958 | 6.7257 | 0.8803 | 0.7084 |
90
+ | 0.2129 | 37.0007 | 5092 | 6.6463 | 0.8879 | 0.7106 |
91
+ | 0.1909 | 38.0007 | 5226 | 7.0005 | 0.8976 | 0.7224 |
92
+ | 0.1811 | 39.0007 | 5360 | 7.3596 | 0.8996 | 0.7331 |
93
+ | 0.156 | 40.0007 | 5494 | 8.9054 | 0.9002 | 0.7356 |
94
+ | 0.1412 | 41.0007 | 5628 | 8.4261 | 0.9034 | 0.7396 |
95
+ | 0.1408 | 42.0007 | 5762 | 10.1692 | 0.9005 | 0.7437 |
96
+ | 0.1365 | 43.0007 | 5896 | 10.4511 | 0.9036 | 0.7492 |
97
+ | 0.1302 | 44.0007 | 6030 | 8.5259 | 0.9028 | 0.7474 |
98
+ | 0.115 | 45.0007 | 6164 | 8.8409 | 0.9020 | 0.7486 |
99
+ | 0.1145 | 46.0007 | 6298 | 12.7269 | 0.9079 | 0.7511 |
100
+ | 0.1086 | 47.0006 | 6432 | 11.0894 | 0.9079 | 0.7558 |
101
+ | 0.1066 | 48.0006 | 6566 | 9.6379 | 0.9109 | 0.7645 |
102
+ | 0.0865 | 49.0006 | 6700 | 12.0341 | 0.9088 | 0.7590 |
103
+ | 0.0902 | 50.0006 | 6834 | 11.4583 | 0.9131 | 0.7690 |
104
+ | 0.0857 | 51.0006 | 6968 | 8.3967 | 0.9123 | 0.7709 |
105
+ | 0.075 | 52.0006 | 7102 | 12.6557 | 0.9151 | 0.7722 |
106
+ | 0.0814 | 53.0006 | 7236 | 13.2238 | 0.9165 | 0.7808 |
107
+ | 0.077 | 54.0006 | 7370 | 10.6487 | 0.9161 | 0.7797 |
108
+ | 0.0639 | 55.0006 | 7504 | 11.9067 | 0.9181 | 0.7828 |
109
+ | 0.0648 | 56.0006 | 7638 | 11.7533 | 0.9161 | 0.7821 |
110
+ | 0.0602 | 57.0006 | 7772 | 10.3832 | 0.9206 | 0.7910 |
111
+ | 0.0538 | 58.0006 | 7906 | 12.8221 | 0.9213 | 0.7850 |
112
+ | 0.0586 | 59.0006 | 8040 | 11.5703 | 0.9208 | 0.7906 |
113
+ | 0.0414 | 60.0005 | 8174 | 11.2536 | 0.9214 | 0.7923 |
114
+ | 0.0395 | 61.0005 | 8308 | 13.5535 | 0.9246 | 0.7960 |
115
+ | 0.0518 | 62.0005 | 8442 | 13.5787 | 0.9223 | 0.7922 |
116
+ | 0.0441 | 63.0005 | 8576 | 11.8294 | 0.9198 | 0.7890 |
117
+ | 0.0464 | 64.0005 | 8710 | 12.4562 | 0.9192 | 0.7936 |
118
+ | 0.0423 | 65.0005 | 8844 | 8.8058 | 0.9243 | 0.8010 |
119
+ | 0.0455 | 66.0005 | 8978 | 12.6342 | 0.9232 | 0.7962 |
120
+ | 0.0372 | 67.0005 | 9112 | 13.5254 | 0.9261 | 0.8008 |
121
+ | 0.0386 | 68.0005 | 9246 | 12.5933 | 0.9269 | 0.8044 |
122
+ | 0.0351 | 69.0005 | 9380 | 16.2459 | 0.9235 | 0.8031 |
123
+ | 0.0337 | 70.0005 | 9514 | 10.9077 | 0.9246 | 0.8031 |
124
+ | 0.0362 | 71.0005 | 9648 | 11.3444 | 0.9279 | 0.8057 |
125
+ | 0.0289 | 72.0005 | 9782 | 12.8704 | 0.9276 | 0.8114 |
126
+ | 0.0277 | 73.0005 | 9916 | 12.9896 | 0.9232 | 0.8039 |
127
+ | 0.0337 | 74.0004 | 10050 | 14.7879 | 0.9243 | 0.8070 |
128
+ | 0.038 | 75.0004 | 10184 | 13.4084 | 0.9221 | 0.7950 |
129
+ | 0.0389 | 76.0004 | 10318 | 15.4665 | 0.9208 | 0.7877 |
130
+ | 0.0331 | 77.0004 | 10452 | 13.3072 | 0.9252 | 0.8066 |
131
+ | 0.0309 | 78.0004 | 10586 | 12.6113 | 0.9238 | 0.8079 |
132
+ | 0.0234 | 79.0004 | 10720 | 14.3185 | 0.9298 | 0.8135 |
133
+ | 0.0224 | 80.0004 | 10854 | 18.7701 | 0.9309 | 0.8149 |
134
+ | 0.0249 | 81.0004 | 10988 | 14.7982 | 0.9268 | 0.8159 |
135
+ | 0.0293 | 82.0004 | 11122 | 16.2099 | 0.9252 | 0.8096 |
136
+ | 0.0375 | 83.0004 | 11256 | 13.1446 | 0.9222 | 0.8083 |
137
+ | 0.0398 | 84.0004 | 11390 | 12.2897 | 0.9270 | 0.8069 |
138
+ | 0.0329 | 85.0004 | 11524 | 9.9588 | 0.9277 | 0.8101 |
139
+ | 0.0264 | 86.0004 | 11658 | 15.5504 | 0.9309 | 0.8207 |
140
+ | 0.0212 | 87.0003 | 11792 | 16.3288 | 0.9319 | 0.8223 |
141
+ | 0.0201 | 88.0003 | 11926 | 16.9663 | 0.9327 | 0.8222 |
142
+ | 0.0197 | 89.0003 | 12060 | 23.1126 | 0.9328 | 0.8241 |
143
+ | 0.0195 | 90.0003 | 12194 | 20.7772 | 0.9316 | 0.8216 |
144
+ | 0.0217 | 91.0003 | 12328 | 20.8325 | 0.9297 | 0.8180 |
145
+ | 0.0228 | 92.0003 | 12462 | 20.2237 | 0.9286 | 0.8192 |
146
+ | 0.0229 | 93.0003 | 12596 | 19.9432 | 0.9331 | 0.8228 |
147
+ | 0.0257 | 94.0003 | 12730 | 20.8237 | 0.9319 | 0.8147 |
148
+ | 0.0164 | 95.0003 | 12864 | 24.2862 | 0.9347 | 0.8267 |
149
+ | 0.0174 | 96.0003 | 12998 | 26.0493 | 0.9363 | 0.8256 |
150
+ | 0.0276 | 97.0003 | 13132 | 19.0496 | 0.9289 | 0.8211 |
151
+ | 0.0252 | 98.0003 | 13266 | 11.8151 | 0.9322 | 0.8221 |
152
+ | 0.0239 | 99.0003 | 13400 | 26.1875 | 0.9295 | 0.8220 |
153
+ | 0.032 | 100.0003 | 13534 | 21.7392 | 0.9347 | 0.8245 |
154
+ | 0.0725 | 101.0002 | 13668 | 17.1267 | 0.9274 | 0.8222 |
155
+ | 0.0326 | 102.0002 | 13802 | 16.2185 | 0.9338 | 0.8279 |
156
+ | 0.0311 | 103.0002 | 13936 | 16.9710 | 0.9314 | 0.8216 |
157
+ | 0.0226 | 104.0002 | 14070 | 25.8568 | 0.9327 | 0.8270 |
158
+ | 0.0166 | 105.0002 | 14204 | 22.9278 | 0.9368 | 0.8334 |
159
+ | 0.0124 | 106.0002 | 14338 | 25.7349 | 0.9392 | 0.8366 |
160
+ | 0.0107 | 107.0002 | 14472 | 32.1370 | 0.9384 | 0.8322 |
161
+ | 0.0104 | 108.0002 | 14606 | 33.9868 | 0.9382 | 0.8338 |
162
+ | 0.0245 | 109.0002 | 14740 | 19.0870 | 0.9359 | 0.8335 |
163
+ | 0.0148 | 110.0002 | 14874 | 27.1582 | 0.9343 | 0.8213 |
164
+ | 0.0123 | 111.0002 | 15008 | 21.2497 | 0.9382 | 0.8322 |
165
+ | 0.0121 | 112.0002 | 15142 | 21.2890 | 0.9396 | 0.8364 |
166
+ | 0.0098 | 113.0002 | 15276 | 33.8945 | 0.9322 | 0.8336 |
167
+ | 0.0127 | 114.0001 | 15410 | 23.7403 | 0.9354 | 0.8340 |
168
+ | 0.016 | 115.0001 | 15544 | 36.1000 | 0.9346 | 0.8317 |
169
+ | 0.0159 | 116.0001 | 15678 | 34.1377 | 0.9352 | 0.8306 |
170
+ | 0.0238 | 117.0001 | 15812 | 29.9560 | 0.9336 | 0.8289 |
171
+ | 0.0215 | 118.0001 | 15946 | 23.3953 | 0.9352 | 0.8337 |
172
+ | 0.0196 | 119.0001 | 16080 | 21.2258 | 0.9328 | 0.8361 |
173
+ | 0.016 | 120.0001 | 16214 | 17.8038 | 0.9359 | 0.8368 |
174
+ | 0.0317 | 121.0001 | 16348 | 19.2920 | 0.9325 | 0.8351 |
175
+ | 0.0144 | 122.0001 | 16482 | 29.3245 | 0.9377 | 0.8390 |
176
+ | 0.0142 | 123.0001 | 16616 | 29.8097 | 0.9377 | 0.8402 |
177
+ | 0.011 | 124.0001 | 16750 | 35.3951 | 0.9388 | 0.8432 |
178
+ | 0.0094 | 125.0001 | 16884 | 26.2506 | 0.9370 | 0.8426 |
179
+ | 0.0116 | 126.0001 | 17018 | 31.6060 | 0.9262 | 0.8371 |
180
+ | 0.0102 | 127.0001 | 17152 | 31.9086 | 0.9345 | 0.8435 |
181
+ | 0.0146 | 128.0000 | 17286 | 30.6725 | 0.9363 | 0.8391 |
182
+ | 0.0126 | 129.0000 | 17420 | 22.8775 | 0.9370 | 0.8364 |
183
+ | 0.0108 | 130.0000 | 17554 | 27.2359 | 0.9397 | 0.8434 |
184
+ | 0.0097 | 131.0000 | 17688 | 25.9838 | 0.9393 | 0.8417 |
185
+ | 0.008 | 132.0000 | 17822 | 38.6480 | 0.9406 | 0.8445 |
186
+ | 0.0067 | 133.0000 | 17956 | 49.8206 | 0.9410 | 0.8463 |
187
+ | 0.0058 | 133.0010 | 18090 | 49.0981 | 0.9399 | 0.8446 |
188
+ | 0.0065 | 134.0010 | 18224 | 37.6428 | 0.9398 | 0.8425 |
189
+ | 0.0062 | 135.0010 | 18358 | 46.4948 | 0.9381 | 0.8376 |
190
+ | 0.0065 | 136.0010 | 18492 | 33.9389 | 0.9409 | 0.8474 |
191
+ | 0.0344 | 137.0010 | 18626 | 17.4156 | 0.9336 | 0.8368 |
192
+ | 0.0194 | 138.0010 | 18760 | 20.2359 | 0.9378 | 0.8407 |
193
+ | 0.0205 | 139.0010 | 18894 | 24.1386 | 0.9416 | 0.8477 |
194
+ | 0.0091 | 140.0010 | 19028 | 38.4560 | 0.9403 | 0.8431 |
195
+ | 0.008 | 141.0009 | 19162 | 46.6457 | 0.9430 | 0.8494 |
196
+ | 0.0076 | 142.0009 | 19296 | 67.7721 | 0.9415 | 0.8450 |
197
+ | 0.006 | 143.0009 | 19430 | 53.1972 | 0.9438 | 0.8506 |
198
+ | 0.006 | 144.0009 | 19564 | 55.7990 | 0.9435 | 0.8510 |
199
+ | 0.0063 | 145.0009 | 19698 | 63.8235 | 0.9430 | 0.8528 |
200
+ | 0.0046 | 146.0009 | 19832 | 60.1267 | 0.9433 | 0.8506 |
201
+ | 0.0043 | 147.0009 | 19966 | 51.8146 | 0.9423 | 0.8491 |
202
+ | 0.0036 | 148.0009 | 20100 | 53.4295 | 0.9433 | 0.8526 |
203
+ | 0.0052 | 149.0009 | 20234 | 73.8274 | 0.9428 | 0.8525 |
204
+ | 0.0066 | 150.0009 | 20368 | 50.7785 | 0.9402 | 0.8476 |
205
+ | 0.0467 | 151.0009 | 20502 | 12.7505 | 0.9272 | 0.8218 |
206
+ | 0.0183 | 152.0009 | 20636 | 16.3303 | 0.9334 | 0.8400 |
207
+ | 0.017 | 153.0009 | 20770 | 32.9632 | 0.9407 | 0.8472 |
208
+ | 0.0054 | 154.0008 | 20904 | 45.1417 | 0.9422 | 0.8513 |
209
+ | 0.0046 | 155.0008 | 21038 | 58.7558 | 0.9427 | 0.8532 |
210
+ | 0.0037 | 156.0008 | 21172 | 71.0211 | 0.9435 | 0.8521 |
211
+ | 0.0036 | 157.0008 | 21306 | 78.0138 | 0.9436 | 0.8552 |
212
+ | 0.0035 | 158.0008 | 21440 | 70.2300 | 0.9429 | 0.8551 |
213
+ | 0.0032 | 159.0008 | 21574 | 84.0004 | 0.9429 | 0.8541 |
214
+ | 0.0031 | 160.0008 | 21708 | 76.8712 | 0.9437 | 0.8545 |
215
+ | 0.0034 | 161.0008 | 21842 | 63.4302 | 0.9436 | 0.8523 |
216
+ | 0.0069 | 162.0008 | 21976 | 36.4633 | 0.9415 | 0.8474 |
217
+ | 0.0135 | 163.0008 | 22110 | 15.8481 | 0.9342 | 0.8337 |
218
+ | 0.0183 | 164.0008 | 22244 | 19.2228 | 0.9341 | 0.8387 |
219
+ | 0.017 | 165.0008 | 22378 | 26.5695 | 0.9372 | 0.8459 |
220
+ | 0.0187 | 166.0008 | 22512 | 40.8066 | 0.9402 | 0.8527 |
221
+ | 0.0057 | 167.0008 | 22646 | 66.2340 | 0.9401 | 0.8451 |
222
+ | 0.0061 | 168.0007 | 22780 | 65.7938 | 0.9422 | 0.8555 |
223
+ | 0.0091 | 169.0007 | 22914 | 38.5296 | 0.9372 | 0.8454 |
224
+ | 0.0074 | 170.0007 | 23048 | 37.0112 | 0.9359 | 0.8422 |
225
+ | 0.0096 | 171.0007 | 23182 | 58.2084 | 0.9409 | 0.8490 |
226
+ | 0.0173 | 172.0007 | 23316 | 43.4838 | 0.9434 | 0.8525 |
227
+ | 0.0095 | 173.0007 | 23450 | 53.2788 | 0.9409 | 0.8555 |
228
+ | 0.0074 | 174.0007 | 23584 | 49.6918 | 0.9419 | 0.8589 |
229
+ | 0.0043 | 175.0007 | 23718 | 73.2480 | 0.9405 | 0.8538 |
230
+ | 0.0029 | 176.0007 | 23852 | 77.7240 | 0.9428 | 0.8590 |
231
+ | 0.0045 | 177.0007 | 23986 | 61.1120 | 0.9415 | 0.8508 |
232
+ | 0.0056 | 178.0007 | 24120 | 77.8616 | 0.9438 | 0.8572 |
233
+ | 0.0045 | 179.0007 | 24254 | 89.1427 | 0.9419 | 0.8544 |
234
+ | 0.0098 | 180.0007 | 24388 | 82.9110 | 0.9440 | 0.8579 |
235
+ | 0.0028 | 181.0006 | 24522 | 106.0760 | 0.9444 | 0.8607 |
236
+ | 0.003 | 182.0006 | 24656 | 112.8113 | 0.9445 | 0.8580 |
237
+ | 0.0028 | 183.0006 | 24790 | 87.1914 | 0.9437 | 0.8526 |
238
+ | 0.0037 | 184.0006 | 24924 | 100.4757 | 0.9445 | 0.8573 |
239
+ | 0.0028 | 185.0006 | 25058 | 125.8635 | 0.9443 | 0.8576 |
240
+ | 0.0028 | 186.0006 | 25192 | 122.9104 | 0.9452 | 0.8594 |
241
+ | 0.0029 | 187.0006 | 25326 | 137.2739 | 0.9422 | 0.8549 |
242
+ | 0.0074 | 188.0006 | 25460 | 76.9213 | 0.9421 | 0.8482 |
243
+ | 0.007 | 189.0006 | 25594 | 70.3398 | 0.9424 | 0.8543 |
244
+ | 0.0191 | 190.0006 | 25728 | 47.5316 | 0.9443 | 0.8576 |
245
+ | 0.0102 | 191.0006 | 25862 | 39.1774 | 0.9422 | 0.8566 |
246
+ | 0.0123 | 192.0006 | 25996 | 46.5033 | 0.9423 | 0.8555 |
247
+ | 0.0134 | 193.0006 | 26130 | 44.7733 | 0.9423 | 0.8523 |
248
+ | 0.0343 | 194.0005 | 26264 | 58.8501 | 0.9384 | 0.8524 |
249
+ | 0.0046 | 195.0005 | 26398 | 100.5458 | 0.9397 | 0.8571 |
250
+ | 0.0036 | 196.0005 | 26532 | 95.4706 | 0.9462 | 0.8600 |
251
+ | 0.0025 | 197.0005 | 26666 | 118.5605 | 0.9457 | 0.8605 |
252
+ | 0.002 | 198.0005 | 26800 | 115.6680 | 0.9458 | 0.8614 |
253
+ | 0.0022 | 199.0005 | 26934 | 95.8778 | 0.9445 | 0.8612 |
254
+ | 0.0019 | 200.0005 | 27068 | 105.3724 | 0.9460 | 0.8634 |
255
+ | 0.0016 | 201.0005 | 27202 | 138.2059 | 0.9460 | 0.8637 |
256
+ | 0.0018 | 202.0005 | 27336 | 115.5890 | 0.9448 | 0.8606 |
257
+ | 0.0084 | 203.0005 | 27470 | 94.2083 | 0.9421 | 0.8561 |
258
+ | 0.0032 | 204.0005 | 27604 | 88.8184 | 0.9439 | 0.8618 |
259
+ | 0.006 | 205.0005 | 27738 | 97.2172 | 0.9425 | 0.8586 |
260
+ | 0.0032 | 206.0005 | 27872 | 89.8283 | 0.9407 | 0.8597 |
261
+ | 0.008 | 207.0005 | 28006 | 65.2748 | 0.9440 | 0.8575 |
262
+ | 0.0071 | 208.0004 | 28140 | 82.2443 | 0.9455 | 0.8592 |
263
+ | 0.0055 | 209.0004 | 28274 | 94.2593 | 0.9438 | 0.8558 |
264
+ | 0.0119 | 210.0004 | 28408 | 87.6687 | 0.9425 | 0.8502 |
265
+ | 0.0118 | 211.0004 | 28542 | 42.2785 | 0.9392 | 0.8534 |
266
+ | 0.0091 | 212.0004 | 28676 | 59.0222 | 0.9417 | 0.8568 |
267
+ | 0.007 | 213.0004 | 28810 | 79.9297 | 0.9403 | 0.8590 |
268
+ | 0.0056 | 214.0004 | 28944 | 109.2196 | 0.9391 | 0.8515 |
269
+ | 0.0068 | 215.0004 | 29078 | 90.4840 | 0.9422 | 0.8598 |
270
+ | 0.0043 | 216.0004 | 29212 | 86.8893 | 0.9425 | 0.8565 |
271
+ | 0.0056 | 217.0004 | 29346 | 99.9204 | 0.9427 | 0.8611 |
272
+ | 0.0038 | 218.0004 | 29480 | 98.2803 | 0.9396 | 0.8587 |
273
+ | 0.0025 | 219.0004 | 29614 | 125.4547 | 0.9442 | 0.8625 |
274
+ | 0.0016 | 220.0004 | 29748 | 126.0455 | 0.9447 | 0.8631 |
275
+ | 0.0015 | 221.0003 | 29882 | 147.4570 | 0.9441 | 0.8612 |
276
+
277
+
278
+ ### Framework versions
279
+
280
+ - Transformers 4.46.0
281
+ - Pytorch 2.3.1+cu121
282
+ - Datasets 2.20.0
283
+ - Tokenizers 0.20.1
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:ecaf9fa3a9f3074e50bcc245ad57c5cf3b0d3d3c3d0bbb824ea105e551620b29
3
  size 521223456
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c406bc723321f60660dc91d78ca562f72a916e2a69933906a11f85f44874e6b9
3
  size 521223456
runs/0-sample_rate=0.2/events.out.tfevents.1738905106.luna.352376.1 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:92b12372f18d0b7da9f497d0f23c6dacbd93abd6a842d166cd187b1facd308f8
3
+ size 470