Hugging Face's logo

Onutoa
/
1_6e-3_10_0.1

Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Inference Endpoints
Model card Files Community
Onutoa commited on
Commit
d84e150
•
1 Parent(s): e3821ed

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +160 -0
README.md ADDED
@@ -0,0 +1,160 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ tags:
4
+ - generated_from_trainer
5
+ datasets:
6
+ - super_glue
7
+ metrics:
8
+ - accuracy
9
+ model-index:
10
+ - name: 1_6e-3_10_0.1
11
+ results: []
12
+ ---
13
+
14
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
15
+ should probably proofread and complete it, then remove this comment. -->
16
+
17
+ # 1_6e-3_10_0.1
18
+
19
+ This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the super_glue dataset.
20
+ It achieves the following results on the evaluation set:
21
+ - Loss: 0.9853
22
+ - Accuracy: 0.7416
23
+
24
+ ## Model description
25
+
26
+ More information needed
27
+
28
+ ## Intended uses & limitations
29
+
30
+ More information needed
31
+
32
+ ## Training and evaluation data
33
+
34
+ More information needed
35
+
36
+ ## Training procedure
37
+
38
+ ### Training hyperparameters
39
+
40
+ The following hyperparameters were used during training:
41
+ - learning_rate: 0.006
42
+ - train_batch_size: 16
43
+ - eval_batch_size: 8
44
+ - seed: 11
45
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
46
+ - lr_scheduler_type: linear
47
+ - num_epochs: 100.0
48
+
49
+ ### Training results
50
+
51
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
52
+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|
53
+ | 1.4161 | 1.0 | 590 | 1.9327 | 0.6217 |
54
+ | 1.4964 | 2.0 | 1180 | 1.4733 | 0.6217 |
55
+ | 1.4294 | 3.0 | 1770 | 1.3770 | 0.6217 |
56
+ | 1.3196 | 4.0 | 2360 | 1.1956 | 0.4070 |
57
+ | 1.1661 | 5.0 | 2950 | 0.9866 | 0.6333 |
58
+ | 1.1565 | 6.0 | 3540 | 0.9164 | 0.6453 |
59
+ | 1.0435 | 7.0 | 4130 | 1.0146 | 0.5786 |
60
+ | 1.0861 | 8.0 | 4720 | 0.8707 | 0.6541 |
61
+ | 1.0246 | 9.0 | 5310 | 0.9747 | 0.6728 |
62
+ | 0.9761 | 10.0 | 5900 | 1.0055 | 0.6560 |
63
+ | 0.9672 | 11.0 | 6490 | 0.7808 | 0.6869 |
64
+ | 0.8746 | 12.0 | 7080 | 0.8158 | 0.6768 |
65
+ | 0.8883 | 13.0 | 7670 | 0.7982 | 0.6917 |
66
+ | 0.8257 | 14.0 | 8260 | 0.9875 | 0.6869 |
67
+ | 0.8053 | 15.0 | 8850 | 0.9210 | 0.7171 |
68
+ | 0.7995 | 16.0 | 9440 | 0.7910 | 0.7168 |
69
+ | 0.7376 | 17.0 | 10030 | 0.8382 | 0.7122 |
70
+ | 0.6743 | 18.0 | 10620 | 1.0620 | 0.6141 |
71
+ | 0.6343 | 19.0 | 11210 | 0.7421 | 0.7245 |
72
+ | 0.6499 | 20.0 | 11800 | 0.7841 | 0.7187 |
73
+ | 0.5897 | 21.0 | 12390 | 0.9551 | 0.6713 |
74
+ | 0.6163 | 22.0 | 12980 | 1.0281 | 0.7135 |
75
+ | 0.5617 | 23.0 | 13570 | 0.9252 | 0.7245 |
76
+ | 0.5282 | 24.0 | 14160 | 0.8599 | 0.7080 |
77
+ | 0.5402 | 25.0 | 14750 | 0.8381 | 0.7254 |
78
+ | 0.493 | 26.0 | 15340 | 1.0387 | 0.6657 |
79
+ | 0.474 | 27.0 | 15930 | 0.7978 | 0.7266 |
80
+ | 0.4658 | 28.0 | 16520 | 0.8697 | 0.7306 |
81
+ | 0.4624 | 29.0 | 17110 | 0.8746 | 0.7287 |
82
+ | 0.4333 | 30.0 | 17700 | 0.9256 | 0.7254 |
83
+ | 0.4324 | 31.0 | 18290 | 0.8635 | 0.7336 |
84
+ | 0.4352 | 32.0 | 18880 | 1.0482 | 0.7232 |
85
+ | 0.4144 | 33.0 | 19470 | 1.2383 | 0.6872 |
86
+ | 0.3822 | 34.0 | 20060 | 0.9361 | 0.7324 |
87
+ | 0.3549 | 35.0 | 20650 | 0.9758 | 0.7180 |
88
+ | 0.3597 | 36.0 | 21240 | 1.1784 | 0.7239 |
89
+ | 0.3598 | 37.0 | 21830 | 0.9757 | 0.7336 |
90
+ | 0.3421 | 38.0 | 22420 | 1.3951 | 0.7245 |
91
+ | 0.3309 | 39.0 | 23010 | 1.1202 | 0.7401 |
92
+ | 0.3209 | 40.0 | 23600 | 0.9882 | 0.7358 |
93
+ | 0.3214 | 41.0 | 24190 | 0.9997 | 0.7343 |
94
+ | 0.3101 | 42.0 | 24780 | 0.8871 | 0.7376 |
95
+ | 0.2913 | 43.0 | 25370 | 1.0116 | 0.7401 |
96
+ | 0.2884 | 44.0 | 25960 | 1.1248 | 0.7291 |
97
+ | 0.2761 | 45.0 | 26550 | 0.8363 | 0.7291 |
98
+ | 0.2761 | 46.0 | 27140 | 1.0666 | 0.7202 |
99
+ | 0.2674 | 47.0 | 27730 | 1.0285 | 0.7416 |
100
+ | 0.2647 | 48.0 | 28320 | 0.9575 | 0.7300 |
101
+ | 0.2662 | 49.0 | 28910 | 0.9258 | 0.7373 |
102
+ | 0.2726 | 50.0 | 29500 | 1.0936 | 0.7346 |
103
+ | 0.2461 | 51.0 | 30090 | 1.0192 | 0.7196 |
104
+ | 0.2485 | 52.0 | 30680 | 1.0543 | 0.7382 |
105
+ | 0.245 | 53.0 | 31270 | 0.9507 | 0.7336 |
106
+ | 0.2377 | 54.0 | 31860 | 0.8907 | 0.7361 |
107
+ | 0.2379 | 55.0 | 32450 | 0.9788 | 0.7327 |
108
+ | 0.2335 | 56.0 | 33040 | 1.0168 | 0.7413 |
109
+ | 0.2251 | 57.0 | 33630 | 1.0117 | 0.7346 |
110
+ | 0.2293 | 58.0 | 34220 | 0.9280 | 0.7336 |
111
+ | 0.2211 | 59.0 | 34810 | 0.9735 | 0.7401 |
112
+ | 0.2236 | 60.0 | 35400 | 0.9822 | 0.7404 |
113
+ | 0.2123 | 61.0 | 35990 | 1.0189 | 0.7346 |
114
+ | 0.207 | 62.0 | 36580 | 1.0436 | 0.7401 |
115
+ | 0.2059 | 63.0 | 37170 | 0.9571 | 0.7410 |
116
+ | 0.2052 | 64.0 | 37760 | 1.0027 | 0.7419 |
117
+ | 0.193 | 65.0 | 38350 | 0.9395 | 0.7413 |
118
+ | 0.2099 | 66.0 | 38940 | 1.0325 | 0.7358 |
119
+ | 0.1968 | 67.0 | 39530 | 1.0441 | 0.7398 |
120
+ | 0.1887 | 68.0 | 40120 | 1.1337 | 0.7413 |
121
+ | 0.1911 | 69.0 | 40710 | 1.0438 | 0.7382 |
122
+ | 0.1955 | 70.0 | 41300 | 1.0361 | 0.7394 |
123
+ | 0.1998 | 71.0 | 41890 | 1.0202 | 0.7349 |
124
+ | 0.1944 | 72.0 | 42480 | 1.0261 | 0.7407 |
125
+ | 0.1755 | 73.0 | 43070 | 1.0091 | 0.7422 |
126
+ | 0.1836 | 74.0 | 43660 | 0.9986 | 0.7425 |
127
+ | 0.1856 | 75.0 | 44250 | 0.9461 | 0.7404 |
128
+ | 0.187 | 76.0 | 44840 | 0.9383 | 0.7385 |
129
+ | 0.1873 | 77.0 | 45430 | 1.0445 | 0.7416 |
130
+ | 0.1763 | 78.0 | 46020 | 1.0263 | 0.7410 |
131
+ | 0.1749 | 79.0 | 46610 | 0.9650 | 0.7370 |
132
+ | 0.1728 | 80.0 | 47200 | 0.9903 | 0.7343 |
133
+ | 0.1668 | 81.0 | 47790 | 1.0391 | 0.7382 |
134
+ | 0.1693 | 82.0 | 48380 | 0.9794 | 0.7346 |
135
+ | 0.1665 | 83.0 | 48970 | 1.0463 | 0.7355 |
136
+ | 0.1609 | 84.0 | 49560 | 0.9976 | 0.7373 |
137
+ | 0.165 | 85.0 | 50150 | 1.0040 | 0.7404 |
138
+ | 0.1622 | 86.0 | 50740 | 1.0184 | 0.7419 |
139
+ | 0.1615 | 87.0 | 51330 | 0.9825 | 0.7336 |
140
+ | 0.1624 | 88.0 | 51920 | 0.9889 | 0.7394 |
141
+ | 0.1557 | 89.0 | 52510 | 0.9938 | 0.7370 |
142
+ | 0.1515 | 90.0 | 53100 | 1.0207 | 0.7385 |
143
+ | 0.1565 | 91.0 | 53690 | 1.0081 | 0.7401 |
144
+ | 0.1582 | 92.0 | 54280 | 0.9308 | 0.7364 |
145
+ | 0.1513 | 93.0 | 54870 | 0.9795 | 0.7398 |
146
+ | 0.1572 | 94.0 | 55460 | 0.9688 | 0.7382 |
147
+ | 0.1514 | 95.0 | 56050 | 1.0002 | 0.7410 |
148
+ | 0.1546 | 96.0 | 56640 | 0.9869 | 0.7401 |
149
+ | 0.1534 | 97.0 | 57230 | 0.9694 | 0.7370 |
150
+ | 0.1405 | 98.0 | 57820 | 0.9705 | 0.7404 |
151
+ | 0.149 | 99.0 | 58410 | 0.9859 | 0.7413 |
152
+ | 0.1456 | 100.0 | 59000 | 0.9853 | 0.7416 |
153
+
154
+
155
+ ### Framework versions
156
+
157
+ - Transformers 4.30.0
158
+ - Pytorch 2.0.1+cu117
159
+ - Datasets 2.14.4
160
+ - Tokenizers 0.13.3