haesun commited on
Commit
6ec33aa
1 Parent(s): cbd8c23

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +17 -17
README.md CHANGED
@@ -21,7 +21,7 @@ model-index:
21
  metrics:
22
  - name: Accuracy
23
  type: accuracy
24
- value: 0.9470967741935484
25
  ---
26
 
27
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,8 +31,8 @@ should probably proofread and complete it, then remove this comment. -->
31
 
32
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the clinc_oos dataset.
33
  It achieves the following results on the evaluation set:
34
- - Loss: 0.3180
35
- - Accuracy: 0.9471
36
 
37
  ## Model description
38
 
@@ -63,21 +63,21 @@ The following hyperparameters were used during training:
63
 
64
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
65
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
66
- | 2.8197 | 1.0 | 318 | 2.0528 | 0.7435 |
67
- | 1.5825 | 2.0 | 636 | 1.0403 | 0.8684 |
68
- | 0.8215 | 3.0 | 954 | 0.5924 | 0.9110 |
69
- | 0.486 | 4.0 | 1272 | 0.4252 | 0.9345 |
70
- | 0.3488 | 5.0 | 1590 | 0.3693 | 0.9452 |
71
- | 0.2872 | 6.0 | 1908 | 0.3440 | 0.9452 |
72
- | 0.2564 | 7.0 | 2226 | 0.3297 | 0.9468 |
73
- | 0.2393 | 8.0 | 2544 | 0.3241 | 0.9465 |
74
- | 0.2317 | 9.0 | 2862 | 0.3208 | 0.9471 |
75
- | 0.2265 | 10.0 | 3180 | 0.3180 | 0.9471 |
76
 
77
 
78
  ### Framework versions
79
 
80
- - Transformers 4.22.2
81
- - Pytorch 1.12.1+cu113
82
- - Datasets 2.5.1
83
- - Tokenizers 0.12.1
 
21
  metrics:
22
  - name: Accuracy
23
  type: accuracy
24
+ value: 0.9448387096774193
25
  ---
26
 
27
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
31
 
32
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the clinc_oos dataset.
33
  It achieves the following results on the evaluation set:
34
+ - Loss: 0.1894
35
+ - Accuracy: 0.9448
36
 
37
  ## Model description
38
 
 
63
 
64
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
65
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
66
+ | 1.6133 | 1.0 | 318 | 1.0679 | 0.7290 |
67
+ | 0.8231 | 2.0 | 636 | 0.5164 | 0.8652 |
68
+ | 0.4289 | 3.0 | 954 | 0.3019 | 0.9168 |
69
+ | 0.2722 | 4.0 | 1272 | 0.2336 | 0.9335 |
70
+ | 0.214 | 5.0 | 1590 | 0.2117 | 0.94 |
71
+ | 0.1914 | 6.0 | 1908 | 0.2007 | 0.9445 |
72
+ | 0.1785 | 7.0 | 2226 | 0.1947 | 0.9435 |
73
+ | 0.1716 | 8.0 | 2544 | 0.1919 | 0.9468 |
74
+ | 0.1674 | 9.0 | 2862 | 0.1901 | 0.9452 |
75
+ | 0.1659 | 10.0 | 3180 | 0.1894 | 0.9448 |
76
 
77
 
78
  ### Framework versions
79
 
80
+ - Transformers 4.25.1
81
+ - Pytorch 1.13.0+cu116
82
+ - Datasets 2.8.0
83
+ - Tokenizers 0.13.2