Hugging Face's logo

gokuls
/
model_v1_complete_training_wt_init_48_mini

Fill-Mask
Transformers
PyTorch
TensorBoard
hybridbert
Generated from Trainer
Model card Files
xet
 Metrics Community
gokuls commited on
Commit
594d2fc
·
1 Parent(s): dce3efd

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +120 -0
README.md ADDED
@@ -0,0 +1,120 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ tags:
3
+ - generated_from_trainer
4
+ metrics:
5
+ - accuracy
6
+ model-index:
7
+ - name: model_v1_complete_training_wt_init_48_mini
8
+ results: []
9
+ ---
10
+
11
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
12
+ should probably proofread and complete it, then remove this comment. -->
13
+
14
+ # model_v1_complete_training_wt_init_48_mini
15
+
16
+ This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
17
+ It achieves the following results on the evaluation set:
18
+ - Loss: 2.7920
19
+ - Accuracy: 0.4992
20
+
21
+ ## Model description
22
+
23
+ More information needed
24
+
25
+ ## Intended uses & limitations
26
+
27
+ More information needed
28
+
29
+ ## Training and evaluation data
30
+
31
+ More information needed
32
+
33
+ ## Training procedure
34
+
35
+ ### Training hyperparameters
36
+
37
+ The following hyperparameters were used during training:
38
+ - learning_rate: 1e-05
39
+ - train_batch_size: 48
40
+ - eval_batch_size: 48
41
+ - seed: 10
42
+ - distributed_type: multi-GPU
43
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
44
+ - lr_scheduler_type: linear
45
+ - lr_scheduler_warmup_steps: 10000
46
+ - num_epochs: 25
47
+
48
+ ### Training results
49
+
50
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
51
+ |:-------------:|:-----:|:-------:|:---------------:|:--------:|
52
+ | 5.9411 | 0.25 | 30000 | 5.8833 | 0.1518 |
53
+ | 5.6408 | 0.49 | 60000 | 5.5265 | 0.1908 |
54
+ | 4.5385 | 0.74 | 90000 | 4.3133 | 0.3138 |
55
+ | 4.1015 | 0.98 | 120000 | 3.8996 | 0.3583 |
56
+ | 3.9119 | 1.23 | 150000 | 3.7199 | 0.3783 |
57
+ | 3.7832 | 1.47 | 180000 | 3.6039 | 0.3920 |
58
+ | 3.6686 | 1.72 | 210000 | 3.5057 | 0.4033 |
59
+ | 3.5793 | 1.97 | 240000 | 3.4227 | 0.4137 |
60
+ | 3.5128 | 2.21 | 270000 | 3.3645 | 0.4209 |
61
+ | 3.4597 | 2.46 | 300000 | 3.3219 | 0.4261 |
62
+ | 3.4263 | 2.7 | 330000 | 3.2841 | 0.4312 |
63
+ | 3.3909 | 2.95 | 360000 | 3.2547 | 0.4348 |
64
+ | 3.3635 | 3.2 | 390000 | 3.2284 | 0.4379 |
65
+ | 3.3488 | 3.44 | 420000 | 3.2060 | 0.4409 |
66
+ | 3.3239 | 3.69 | 450000 | 3.1872 | 0.4436 |
67
+ | 3.3062 | 3.93 | 480000 | 3.1660 | 0.4462 |
68
+ | 3.2841 | 4.18 | 510000 | 3.1493 | 0.4485 |
69
+ | 3.2663 | 4.42 | 540000 | 3.1355 | 0.4503 |
70
+ | 3.259 | 4.67 | 570000 | 3.1229 | 0.4519 |
71
+ | 3.2429 | 4.92 | 600000 | 3.1096 | 0.4535 |
72
+ | 3.2234 | 5.16 | 630000 | 3.0947 | 0.4554 |
73
+ | 3.2115 | 5.41 | 660000 | 3.0818 | 0.4573 |
74
+ | 3.2011 | 5.65 | 690000 | 3.0685 | 0.4590 |
75
+ | 3.1898 | 5.9 | 720000 | 3.0464 | 0.4619 |
76
+ | 3.1651 | 6.14 | 750000 | 3.0226 | 0.4658 |
77
+ | 3.1477 | 6.39 | 780000 | 3.0025 | 0.4689 |
78
+ | 3.1276 | 6.64 | 810000 | 2.9838 | 0.4718 |
79
+ | 3.1102 | 6.88 | 840000 | 2.9690 | 0.4740 |
80
+ | 3.1046 | 7.13 | 870000 | 2.9563 | 0.4757 |
81
+ | 3.0817 | 7.37 | 900000 | 2.9477 | 0.4771 |
82
+ | 3.0813 | 7.62 | 930000 | 2.9397 | 0.4785 |
83
+ | 3.0709 | 7.87 | 960000 | 2.9259 | 0.4804 |
84
+ | 3.0528 | 8.11 | 990000 | 2.9208 | 0.4812 |
85
+ | 3.0541 | 8.36 | 1020000 | 2.9089 | 0.4829 |
86
+ | 3.0469 | 8.6 | 1050000 | 2.9015 | 0.4839 |
87
+ | 3.0377 | 8.85 | 1080000 | 2.8960 | 0.4848 |
88
+ | 3.0284 | 9.09 | 1110000 | 2.8859 | 0.4861 |
89
+ | 3.0224 | 9.34 | 1140000 | 2.8819 | 0.4867 |
90
+ | 3.019 | 9.59 | 1170000 | 2.8731 | 0.4878 |
91
+ | 3.0094 | 9.83 | 1200000 | 2.8687 | 0.4885 |
92
+ | 3.0065 | 10.08 | 1230000 | 2.8635 | 0.4893 |
93
+ | 2.9983 | 10.32 | 1260000 | 2.8561 | 0.4900 |
94
+ | 2.9834 | 10.57 | 1290000 | 2.8524 | 0.4907 |
95
+ | 2.9873 | 10.81 | 1320000 | 2.8484 | 0.4911 |
96
+ | 2.978 | 11.06 | 1350000 | 2.8414 | 0.4924 |
97
+ | 2.9709 | 11.31 | 1380000 | 2.8375 | 0.4927 |
98
+ | 2.9695 | 11.55 | 1410000 | 2.8353 | 0.4932 |
99
+ | 2.9607 | 11.8 | 1440000 | 2.8290 | 0.4941 |
100
+ | 2.9636 | 12.04 | 1470000 | 2.8267 | 0.4944 |
101
+ | 2.9584 | 12.29 | 1500000 | 2.8247 | 0.4946 |
102
+ | 2.9546 | 12.54 | 1530000 | 2.8196 | 0.4951 |
103
+ | 2.9544 | 12.78 | 1560000 | 2.8146 | 0.4959 |
104
+ | 2.9486 | 13.03 | 1590000 | 2.8132 | 0.4964 |
105
+ | 2.9413 | 13.27 | 1620000 | 2.8099 | 0.4967 |
106
+ | 2.9381 | 13.52 | 1650000 | 2.8081 | 0.4968 |
107
+ | 2.9389 | 13.76 | 1680000 | 2.8057 | 0.4973 |
108
+ | 2.9374 | 14.01 | 1710000 | 2.8028 | 0.4977 |
109
+ | 2.9341 | 14.26 | 1740000 | 2.8000 | 0.4978 |
110
+ | 2.9275 | 14.5 | 1770000 | 2.7978 | 0.4984 |
111
+ | 2.9319 | 14.75 | 1800000 | 2.7947 | 0.4989 |
112
+ | 2.9304 | 14.99 | 1830000 | 2.7920 | 0.4992 |
113
+
114
+
115
+ ### Framework versions
116
+
117
+ - Transformers 4.30.2
118
+ - Pytorch 1.14.0a0+410ce96
119
+ - Datasets 2.13.0
120
+ - Tokenizers 0.13.3