Hugging Face's logo

SetFit
/
deberta-v3-large__sst2__train-16-9

Text Classification
Transformers
PyTorch
deberta-v2
Generated from Trainer
Inference Endpoints
Model card Files Community
2
lewtun HF staff commited on
Commit
ae35625
•
1 Parent(s): 6998f9e

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +109 -0
README.md ADDED
@@ -0,0 +1,109 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: mit
3
+ tags:
4
+ - generated_from_trainer
5
+ metrics:
6
+ - accuracy
7
+ model-index:
8
+ - name: deberta-v3-large__sst2__train-16-9
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
+ # deberta-v3-large__sst2__train-16-9
16
+
17
+ This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on the None dataset.
18
+ It achieves the following results on the evaluation set:
19
+ - Loss: 1.2598
20
+ - Accuracy: 0.7809
21
+
22
+ ## Model description
23
+
24
+ More information needed
25
+
26
+ ## Intended uses & limitations
27
+
28
+ More information needed
29
+
30
+ ## Training and evaluation data
31
+
32
+ More information needed
33
+
34
+ ## Training procedure
35
+
36
+ ### Training hyperparameters
37
+
38
+ The following hyperparameters were used during training:
39
+ - learning_rate: 2e-05
40
+ - train_batch_size: 4
41
+ - eval_batch_size: 4
42
+ - seed: 42
43
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
44
+ - lr_scheduler_type: linear
45
+ - num_epochs: 50
46
+ - mixed_precision_training: Native AMP
47
+
48
+ ### Training results
49
+
50
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
51
+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
52
+ | 0.6887 | 1.0 | 7 | 0.7452 | 0.2857 |
53
+ | 0.6889 | 2.0 | 14 | 0.7988 | 0.2857 |
54
+ | 0.6501 | 3.0 | 21 | 0.8987 | 0.2857 |
55
+ | 0.4286 | 4.0 | 28 | 0.9186 | 0.4286 |
56
+ | 0.3591 | 5.0 | 35 | 0.5566 | 0.7143 |
57
+ | 0.0339 | 6.0 | 42 | 1.1130 | 0.5714 |
58
+ | 0.013 | 7.0 | 49 | 1.8296 | 0.7143 |
59
+ | 0.0041 | 8.0 | 56 | 1.7069 | 0.7143 |
60
+ | 0.0023 | 9.0 | 63 | 1.1942 | 0.7143 |
61
+ | 0.0022 | 10.0 | 70 | 0.6054 | 0.7143 |
62
+ | 0.0011 | 11.0 | 77 | 0.3872 | 0.7143 |
63
+ | 0.0006 | 12.0 | 84 | 0.3217 | 0.7143 |
64
+ | 0.0005 | 13.0 | 91 | 0.2879 | 0.8571 |
65
+ | 0.0005 | 14.0 | 98 | 0.2640 | 0.8571 |
66
+ | 0.0004 | 15.0 | 105 | 0.2531 | 0.8571 |
67
+ | 0.0003 | 16.0 | 112 | 0.2384 | 0.8571 |
68
+ | 0.0004 | 17.0 | 119 | 0.2338 | 0.8571 |
69
+ | 0.0003 | 18.0 | 126 | 0.2314 | 0.8571 |
70
+ | 0.0003 | 19.0 | 133 | 0.2276 | 0.8571 |
71
+ | 0.0003 | 20.0 | 140 | 0.2172 | 0.8571 |
72
+ | 0.0003 | 21.0 | 147 | 0.2069 | 0.8571 |
73
+ | 0.0002 | 22.0 | 154 | 0.2018 | 0.8571 |
74
+ | 0.0002 | 23.0 | 161 | 0.2005 | 0.8571 |
75
+ | 0.0002 | 24.0 | 168 | 0.1985 | 0.8571 |
76
+ | 0.0002 | 25.0 | 175 | 0.1985 | 1.0 |
77
+ | 0.0002 | 26.0 | 182 | 0.1955 | 1.0 |
78
+ | 0.0002 | 27.0 | 189 | 0.1967 | 1.0 |
79
+ | 0.0002 | 28.0 | 196 | 0.1918 | 1.0 |
80
+ | 0.0002 | 29.0 | 203 | 0.1888 | 1.0 |
81
+ | 0.0002 | 30.0 | 210 | 0.1864 | 1.0 |
82
+ | 0.0002 | 31.0 | 217 | 0.1870 | 1.0 |
83
+ | 0.0002 | 32.0 | 224 | 0.1892 | 1.0 |
84
+ | 0.0002 | 33.0 | 231 | 0.1917 | 1.0 |
85
+ | 0.0002 | 34.0 | 238 | 0.1869 | 1.0 |
86
+ | 0.0002 | 35.0 | 245 | 0.1812 | 1.0 |
87
+ | 0.0001 | 36.0 | 252 | 0.1777 | 1.0 |
88
+ | 0.0002 | 37.0 | 259 | 0.1798 | 1.0 |
89
+ | 0.0002 | 38.0 | 266 | 0.1824 | 0.8571 |
90
+ | 0.0002 | 39.0 | 273 | 0.1846 | 0.8571 |
91
+ | 0.0002 | 40.0 | 280 | 0.1839 | 0.8571 |
92
+ | 0.0001 | 41.0 | 287 | 0.1826 | 0.8571 |
93
+ | 0.0001 | 42.0 | 294 | 0.1779 | 0.8571 |
94
+ | 0.0002 | 43.0 | 301 | 0.1762 | 0.8571 |
95
+ | 0.0001 | 44.0 | 308 | 0.1742 | 1.0 |
96
+ | 0.0002 | 45.0 | 315 | 0.1708 | 1.0 |
97
+ | 0.0001 | 46.0 | 322 | 0.1702 | 1.0 |
98
+ | 0.0001 | 47.0 | 329 | 0.1699 | 1.0 |
99
+ | 0.0001 | 48.0 | 336 | 0.1695 | 1.0 |
100
+ | 0.0001 | 49.0 | 343 | 0.1683 | 1.0 |
101
+ | 0.0001 | 50.0 | 350 | 0.1681 | 1.0 |
102
+
103
+
104
+ ### Framework versions
105
+
106
+ - Transformers 4.15.0
107
+ - Pytorch 1.10.2+cu102
108
+ - Datasets 1.18.2
109
+ - Tokenizers 0.10.3