Yong-Sik commited on
Commit
e9562a6
1 Parent(s): e8850ee

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +79 -0
README.md ADDED
@@ -0,0 +1,79 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ base_model: distilbert-base-uncased
4
+ tags:
5
+ - generated_from_trainer
6
+ datasets:
7
+ - clinc_oos
8
+ metrics:
9
+ - accuracy
10
+ model-index:
11
+ - name: distilbert-base-uncased-finetuned-clinc
12
+ results:
13
+ - task:
14
+ name: Text Classification
15
+ type: text-classification
16
+ dataset:
17
+ name: clinc_oos
18
+ type: clinc_oos
19
+ config: plus
20
+ split: validation
21
+ args: plus
22
+ metrics:
23
+ - name: Accuracy
24
+ type: accuracy
25
+ value: 0.9170967741935484
26
+ ---
27
+
28
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
29
+ should probably proofread and complete it, then remove this comment. -->
30
+
31
+ # distilbert-base-uncased-finetuned-clinc
32
+
33
+ This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the clinc_oos dataset.
34
+ It achieves the following results on the evaluation set:
35
+ - Loss: 0.7724
36
+ - Accuracy: 0.9171
37
+
38
+ ## Model description
39
+
40
+ More information needed
41
+
42
+ ## Intended uses & limitations
43
+
44
+ More information needed
45
+
46
+ ## Training and evaluation data
47
+
48
+ More information needed
49
+
50
+ ## Training procedure
51
+
52
+ ### Training hyperparameters
53
+
54
+ The following hyperparameters were used during training:
55
+ - learning_rate: 2e-05
56
+ - train_batch_size: 48
57
+ - eval_batch_size: 48
58
+ - seed: 42
59
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
60
+ - lr_scheduler_type: linear
61
+ - num_epochs: 5
62
+
63
+ ### Training results
64
+
65
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
66
+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
67
+ | 4.2924 | 1.0 | 318 | 3.2762 | 0.7261 |
68
+ | 2.6142 | 2.0 | 636 | 1.8625 | 0.8384 |
69
+ | 1.5395 | 3.0 | 954 | 1.1513 | 0.8987 |
70
+ | 1.0092 | 4.0 | 1272 | 0.8540 | 0.9123 |
71
+ | 0.7936 | 5.0 | 1590 | 0.7724 | 0.9171 |
72
+
73
+
74
+ ### Framework versions
75
+
76
+ - Transformers 4.31.0
77
+ - Pytorch 2.0.1+cu118
78
+ - Datasets 2.14.4
79
+ - Tokenizers 0.13.3