Hugging Face's logo

diogopaes10
/
011-microsoft-deberta-v3-base-finetuned-yahoo-8000_2000

Text Classification
Transformers
PyTorch
TensorBoard
deberta-v2
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
diogopaes10 commited on
Commit
0dfc416
•
1 Parent(s): 66fe6a4

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +92 -0
README.md ADDED
@@ -0,0 +1,92 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: mit
3
+ base_model: microsoft/deberta-v3-base
4
+ tags:
5
+ - generated_from_trainer
6
+ metrics:
7
+ - f1
8
+ - accuracy
9
+ - precision
10
+ - recall
11
+ model-index:
12
+ - name: 011-microsoft-deberta-v3-base-finetuned-yahoo-8000_2000
13
+ results: []
14
+ ---
15
+
16
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
17
+ should probably proofread and complete it, then remove this comment. -->
18
+
19
+ # 011-microsoft-deberta-v3-base-finetuned-yahoo-8000_2000
20
+
21
+ This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
22
+ It achieves the following results on the evaluation set:
23
+ - Loss: 1.8660
24
+ - F1: 0.7055
25
+ - Accuracy: 0.7045
26
+ - Precision: 0.7076
27
+ - Recall: 0.7045
28
+ - System Ram Used: 4.2773
29
+ - System Ram Total: 83.4807
30
+ - Gpu Ram Allocated: 2.0897
31
+ - Gpu Ram Cached: 25.8555
32
+ - Gpu Ram Total: 39.5640
33
+ - Gpu Utilization: 48
34
+ - Disk Space Used: 35.8287
35
+ - Disk Space Total: 78.1898
36
+
37
+ ## Model description
38
+
39
+ More information needed
40
+
41
+ ## Intended uses & limitations
42
+
43
+ More information needed
44
+
45
+ ## Training and evaluation data
46
+
47
+ More information needed
48
+
49
+ ## Training procedure
50
+
51
+ ### Training hyperparameters
52
+
53
+ The following hyperparameters were used during training:
54
+ - learning_rate: 2e-05
55
+ - train_batch_size: 32
56
+ - eval_batch_size: 32
57
+ - seed: 42
58
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
59
+ - lr_scheduler_type: linear
60
+ - num_epochs: 15
61
+
62
+ ### Training results
63
+
64
+ | Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy | Precision | Recall | System Ram Used | System Ram Total | Gpu Ram Allocated | Gpu Ram Cached | Gpu Ram Total | Gpu Utilization | Disk Space Used | Disk Space Total |
65
+ |:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:---------:|:------:|:---------------:|:----------------:|:-----------------:|:--------------:|:-------------:|:---------------:|:---------------:|:----------------:|
66
+ | 1.6916 | 0.75 | 188 | 1.1063 | 0.6708 | 0.6755 | 0.6900 | 0.6755 | 4.0191 | 83.4807 | 2.0898 | 25.8555 | 39.5640 | 50 | 24.8064 | 78.1898 |
67
+ | 0.9694 | 1.5 | 376 | 0.9586 | 0.7181 | 0.7195 | 0.7198 | 0.7195 | 4.2536 | 83.4807 | 2.0898 | 25.8555 | 39.5640 | 50 | 29.6418 | 78.1898 |
68
+ | 0.8509 | 2.26 | 564 | 0.9748 | 0.7070 | 0.712 | 0.7161 | 0.712 | 4.1602 | 83.4807 | 2.0898 | 25.8555 | 39.5640 | 46 | 29.6418 | 78.1898 |
69
+ | 0.7475 | 3.01 | 752 | 0.9447 | 0.7122 | 0.714 | 0.7148 | 0.714 | 4.1607 | 83.4807 | 2.0898 | 25.8555 | 39.5640 | 50 | 29.6420 | 78.1898 |
70
+ | 0.5841 | 3.76 | 940 | 1.0064 | 0.7077 | 0.711 | 0.7225 | 0.711 | 4.1889 | 83.4807 | 2.0898 | 25.8555 | 39.5640 | 47 | 29.6420 | 78.1898 |
71
+ | 0.4972 | 4.51 | 1128 | 1.0585 | 0.7110 | 0.714 | 0.7129 | 0.714 | 4.1766 | 83.4807 | 2.0898 | 25.8555 | 39.5640 | 47 | 29.6421 | 78.1898 |
72
+ | 0.4555 | 5.26 | 1316 | 1.1175 | 0.7086 | 0.7075 | 0.7151 | 0.7075 | 4.2257 | 83.4807 | 2.0898 | 25.8555 | 39.5640 | 46 | 33.7652 | 78.1898 |
73
+ | 0.3535 | 6.02 | 1504 | 1.1749 | 0.7032 | 0.708 | 0.7077 | 0.708 | 4.2302 | 83.4807 | 2.0898 | 25.8555 | 39.5640 | 50 | 33.7653 | 78.1898 |
74
+ | 0.2614 | 6.77 | 1692 | 1.2028 | 0.7056 | 0.709 | 0.7079 | 0.709 | 4.2376 | 83.4807 | 2.0898 | 25.8555 | 39.5640 | 49 | 33.7654 | 78.1898 |
75
+ | 0.2321 | 7.52 | 1880 | 1.2961 | 0.7019 | 0.698 | 0.7085 | 0.698 | 4.2248 | 83.4807 | 2.0898 | 25.8555 | 39.5640 | 49 | 33.7656 | 78.1898 |
76
+ | 0.197 | 8.27 | 2068 | 1.3960 | 0.7098 | 0.712 | 0.7137 | 0.712 | 4.2194 | 83.4807 | 2.0898 | 25.8555 | 39.5640 | 45 | 33.7657 | 78.1898 |
77
+ | 0.1505 | 9.02 | 2256 | 1.4310 | 0.7093 | 0.7075 | 0.7133 | 0.7075 | 4.2418 | 83.4807 | 2.0898 | 25.8555 | 39.5640 | 48 | 35.8277 | 78.1898 |
78
+ | 0.1132 | 9.78 | 2444 | 1.5454 | 0.7053 | 0.7045 | 0.7097 | 0.7045 | 4.2931 | 83.4807 | 2.0898 | 25.8555 | 39.5640 | 48 | 35.8278 | 78.1898 |
79
+ | 0.0979 | 10.53 | 2632 | 1.6420 | 0.7090 | 0.708 | 0.7171 | 0.708 | 4.2793 | 83.4807 | 2.0898 | 25.8555 | 39.5640 | 45 | 35.8281 | 78.1898 |
80
+ | 0.0818 | 11.28 | 2820 | 1.6869 | 0.7062 | 0.7065 | 0.7102 | 0.7065 | 4.2822 | 83.4807 | 2.0898 | 25.8555 | 39.5640 | 49 | 35.8281 | 78.1898 |
81
+ | 0.062 | 12.03 | 3008 | 1.7818 | 0.7043 | 0.701 | 0.7123 | 0.701 | 4.2864 | 83.4807 | 2.0901 | 25.8555 | 39.5640 | 50 | 35.8282 | 78.1898 |
82
+ | 0.0433 | 12.78 | 3196 | 1.7981 | 0.7080 | 0.707 | 0.7110 | 0.707 | 4.2666 | 83.4807 | 2.0898 | 25.8555 | 39.5640 | 49 | 35.8282 | 78.1898 |
83
+ | 0.0368 | 13.54 | 3384 | 1.8403 | 0.7079 | 0.7055 | 0.7131 | 0.7055 | 4.2783 | 83.4807 | 2.0898 | 25.8555 | 39.5640 | 47 | 35.8285 | 78.1898 |
84
+ | 0.0379 | 14.29 | 3572 | 1.8536 | 0.7052 | 0.705 | 0.7074 | 0.705 | 4.3013 | 83.4807 | 2.0898 | 25.8555 | 39.5640 | 47 | 35.8286 | 78.1898 |
85
+
86
+
87
+ ### Framework versions
88
+
89
+ - Transformers 4.31.0
90
+ - Pytorch 2.0.1+cu118
91
+ - Datasets 2.13.1
92
+ - Tokenizers 0.13.3