Tomor0720 commited on
Commit
507f2f8
1 Parent(s): 2bc7285

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +80 -0
README.md ADDED
@@ -0,0 +1,80 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: mit
3
+ tags:
4
+ - generated_from_trainer
5
+ datasets:
6
+ - glue
7
+ metrics:
8
+ - accuracy
9
+ - f1
10
+ model-index:
11
+ - name: deberta-large-finetuned-qqp
12
+ results:
13
+ - task:
14
+ name: Text Classification
15
+ type: text-classification
16
+ dataset:
17
+ name: glue
18
+ type: glue
19
+ config: qqp
20
+ split: train
21
+ args: qqp
22
+ metrics:
23
+ - name: Accuracy
24
+ type: accuracy
25
+ value: 0.8985901558248826
26
+ - name: F1
27
+ type: f1
28
+ value: 0.8648292232625608
29
+ ---
30
+
31
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
32
+ should probably proofread and complete it, then remove this comment. -->
33
+
34
+ # deberta-large-finetuned-qqp
35
+
36
+ This model is a fine-tuned version of [microsoft/deberta-large](https://huggingface.co/microsoft/deberta-large) on the glue dataset.
37
+ It achieves the following results on the evaluation set:
38
+ - Loss: 0.2635
39
+ - Accuracy: 0.8986
40
+ - F1: 0.8648
41
+
42
+ ## Model description
43
+
44
+ More information needed
45
+
46
+ ## Intended uses & limitations
47
+
48
+ More information needed
49
+
50
+ ## Training and evaluation data
51
+
52
+ More information needed
53
+
54
+ ## Training procedure
55
+
56
+ ### Training hyperparameters
57
+
58
+ The following hyperparameters were used during training:
59
+ - learning_rate: 2e-05
60
+ - train_batch_size: 16
61
+ - eval_batch_size: 16
62
+ - seed: 42
63
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
64
+ - lr_scheduler_type: linear
65
+ - num_epochs: 2
66
+
67
+ ### Training results
68
+
69
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
70
+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
71
+ | 0.4058 | 1.0 | 22741 | 0.3923 | 0.8496 | 0.8108 |
72
+ | 0.2347 | 2.0 | 45482 | 0.2635 | 0.8986 | 0.8648 |
73
+
74
+
75
+ ### Framework versions
76
+
77
+ - Transformers 4.25.1
78
+ - Pytorch 1.13.1+cu116
79
+ - Datasets 2.8.0
80
+ - Tokenizers 0.13.2