Hugging Face's logo

diogopaes10
/
015-microsoft-deberta-v3-base-finetuned-yahoo-80_20

Text Classification
Transformers
PyTorch
TensorBoard
deberta-v2
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
diogopaes10 commited on
Commit
993905d
•
1 Parent(s): e510e24

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +93 -0
README.md ADDED
@@ -0,0 +1,93 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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: 015-microsoft-deberta-v3-base-finetuned-yahoo-80_20
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
+ # 015-microsoft-deberta-v3-base-finetuned-yahoo-80_20
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: 2.0709
24
+ - F1: 0.2744
25
+ - Accuracy: 0.35
26
+ - Precision: 0.2452
27
+ - Recall: 0.35
28
+ - System Ram Used: 3.9663
29
+ - System Ram Total: 83.4807
30
+ - Gpu Ram Allocated: 2.0874
31
+ - Gpu Ram Cached: 6.8516
32
+ - Gpu Ram Total: 39.5640
33
+ - Gpu Utilization: 14
34
+ - Disk Space Used: 24.7820
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: 40
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
+ | 2.3062 | 2.0 | 6 | 2.3028 | 0.025 | 0.1 | 0.0143 | 0.1 | 3.9009 | 83.4807 | 2.0874 | 6.8398 | 39.5640 | 51 | 24.7819 | 78.1898 |
67
+ | 2.304 | 4.0 | 12 | 2.3020 | 0.0722 | 0.15 | 0.0625 | 0.15 | 3.9032 | 83.4807 | 2.0873 | 6.8418 | 39.5640 | 56 | 24.7819 | 78.1898 |
68
+ | 2.2892 | 6.0 | 18 | 2.2997 | 0.0111 | 0.05 | 0.0063 | 0.05 | 3.9136 | 83.4807 | 2.0874 | 6.8418 | 39.5640 | 62 | 24.7819 | 78.1898 |
69
+ | 2.2729 | 8.0 | 24 | 2.2947 | 0.0190 | 0.1 | 0.0105 | 0.1 | 3.9411 | 83.4807 | 2.0873 | 6.8418 | 39.5640 | 56 | 24.7819 | 78.1898 |
70
+ | 2.2108 | 10.0 | 30 | 2.2843 | 0.0521 | 0.15 | 0.0333 | 0.15 | 3.9439 | 83.4807 | 2.0873 | 6.8418 | 39.5640 | 60 | 24.7819 | 78.1898 |
71
+ | 2.1482 | 12.0 | 36 | 2.2660 | 0.1417 | 0.2 | 0.1643 | 0.2 | 3.9451 | 83.4807 | 2.0873 | 6.8418 | 39.5640 | 48 | 24.7819 | 78.1898 |
72
+ | 2.0203 | 14.0 | 42 | 2.2328 | 0.2086 | 0.3 | 0.1617 | 0.3 | 3.9597 | 83.4807 | 2.0874 | 6.8418 | 39.5640 | 52 | 24.7819 | 78.1898 |
73
+ | 1.8707 | 16.0 | 48 | 2.2030 | 0.2019 | 0.3 | 0.1533 | 0.3 | 3.9691 | 83.4807 | 2.0873 | 6.8418 | 39.5640 | 55 | 24.7819 | 78.1898 |
74
+ | 1.701 | 18.0 | 54 | 2.1741 | 0.2638 | 0.35 | 0.2483 | 0.35 | 3.9705 | 83.4807 | 2.0873 | 6.8418 | 39.5640 | 58 | 24.7819 | 78.1898 |
75
+ | 1.5493 | 20.0 | 60 | 2.1379 | 0.2967 | 0.35 | 0.3 | 0.35 | 3.9699 | 83.4807 | 2.0874 | 6.8516 | 39.5640 | 57 | 24.7819 | 78.1898 |
76
+ | 1.4073 | 22.0 | 66 | 2.1232 | 0.2244 | 0.3 | 0.1952 | 0.3 | 3.9711 | 83.4807 | 2.0873 | 6.8516 | 39.5640 | 51 | 24.7819 | 78.1898 |
77
+ | 1.2447 | 24.0 | 72 | 2.1096 | 0.2344 | 0.3 | 0.2119 | 0.3 | 3.9705 | 83.4807 | 2.0873 | 6.8516 | 39.5640 | 49 | 24.7819 | 78.1898 |
78
+ | 1.155 | 26.0 | 78 | 2.0978 | 0.3178 | 0.4 | 0.3119 | 0.4 | 3.9663 | 83.4807 | 2.0874 | 6.8516 | 39.5640 | 56 | 24.7819 | 78.1898 |
79
+ | 1.0522 | 28.0 | 84 | 2.0805 | 0.2744 | 0.35 | 0.2452 | 0.35 | 3.9661 | 83.4807 | 2.0873 | 6.8516 | 39.5640 | 63 | 24.7820 | 78.1898 |
80
+ | 0.9741 | 30.0 | 90 | 2.0735 | 0.2744 | 0.35 | 0.2452 | 0.35 | 3.9575 | 83.4807 | 2.0873 | 6.8516 | 39.5640 | 59 | 24.7820 | 78.1898 |
81
+ | 0.9042 | 32.0 | 96 | 2.0793 | 0.2744 | 0.35 | 0.2452 | 0.35 | 3.9661 | 83.4807 | 2.0873 | 6.8516 | 39.5640 | 50 | 24.7820 | 78.1898 |
82
+ | 0.8497 | 34.0 | 102 | 2.0769 | 0.2744 | 0.35 | 0.2452 | 0.35 | 3.9654 | 83.4807 | 2.0874 | 6.8516 | 39.5640 | 58 | 24.7820 | 78.1898 |
83
+ | 0.8228 | 36.0 | 108 | 2.0736 | 0.2744 | 0.35 | 0.2452 | 0.35 | 3.9660 | 83.4807 | 2.0873 | 6.8516 | 39.5640 | 60 | 24.7820 | 78.1898 |
84
+ | 0.7908 | 38.0 | 114 | 2.0717 | 0.2744 | 0.35 | 0.2452 | 0.35 | 3.9659 | 83.4807 | 2.0873 | 6.8516 | 39.5640 | 59 | 24.7820 | 78.1898 |
85
+ | 0.7998 | 40.0 | 120 | 2.0709 | 0.2744 | 0.35 | 0.2452 | 0.35 | 3.9661 | 83.4807 | 2.0873 | 6.8516 | 39.5640 | 59 | 24.7820 | 78.1898 |
86
+
87
+
88
+ ### Framework versions
89
+
90
+ - Transformers 4.31.0
91
+ - Pytorch 2.0.1+cu118
92
+ - Datasets 2.13.1
93
+ - Tokenizers 0.13.3