chia commited on
Commit
ac92022
1 Parent(s): f320ccc

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +76 -76
README.md CHANGED
@@ -1,76 +1,76 @@
1
- ---
2
- license: apache-2.0
3
- tags:
4
- - generated_from_trainer
5
- datasets:
6
- - clinc_oos
7
- metrics:
8
- - accuracy
9
- model-index:
10
- - name: distilbert-base-uncased-finetuned-clinc
11
- results:
12
- - task:
13
- name: Text Classification
14
- type: text-classification
15
- dataset:
16
- name: clinc_oos
17
- type: clinc_oos
18
- args: plus
19
- metrics:
20
- - name: Accuracy
21
- type: accuracy
22
- value: 0.9167741935483871
23
- ---
24
-
25
- <!-- This model card has been generated automatically according to the information the Trainer had access to. You
26
- should probably proofread and complete it, then remove this comment. -->
27
-
28
- # distilbert-base-uncased-finetuned-clinc
29
-
30
- This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the clinc_oos dataset.
31
- It achieves the following results on the evaluation set:
32
- - Loss: 0.7778
33
- - Accuracy: 0.9168
34
-
35
- ## Model description
36
-
37
- More information needed
38
-
39
- ## Intended uses & limitations
40
-
41
- More information needed
42
-
43
- ## Training and evaluation data
44
-
45
- More information needed
46
-
47
- ## Training procedure
48
-
49
- ### Training hyperparameters
50
-
51
- The following hyperparameters were used during training:
52
- - learning_rate: 2e-05
53
- - train_batch_size: 48
54
- - eval_batch_size: 48
55
- - seed: 42
56
- - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
57
- - lr_scheduler_type: linear
58
- - num_epochs: 5
59
-
60
- ### Training results
61
-
62
- | Training Loss | Epoch | Step | Validation Loss | Accuracy |
63
- |:-------------:|:-----:|:----:|:---------------:|:--------:|
64
- | 4.2883 | 1.0 | 318 | 3.2779 | 0.7394 |
65
- | 2.623 | 2.0 | 636 | 1.8741 | 0.8287 |
66
- | 1.544 | 3.0 | 954 | 1.1618 | 0.89 |
67
- | 1.0111 | 4.0 | 1272 | 0.8601 | 0.9090 |
68
- | 0.7998 | 5.0 | 1590 | 0.7778 | 0.9168 |
69
-
70
-
71
- ### Framework versions
72
-
73
- - Transformers 4.11.3
74
- - Pytorch 1.12.1+cu113
75
- - Datasets 1.16.1
76
- - Tokenizers 0.10.3
 
1
+ ---
2
+ license: apache-2.0
3
+ tags:
4
+ - generated_from_trainer
5
+ datasets:
6
+ - clinc_oos
7
+ metrics:
8
+ - accuracy
9
+ model-index:
10
+ - name: distilbert-base-uncased-finetuned-clinc
11
+ results:
12
+ - task:
13
+ name: Text Classification
14
+ type: text-classification
15
+ dataset:
16
+ name: clinc_oos
17
+ type: clinc_oos
18
+ args: plus
19
+ metrics:
20
+ - name: Accuracy
21
+ type: accuracy
22
+ value: 0.9170967741935484
23
+ ---
24
+
25
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
26
+ should probably proofread and complete it, then remove this comment. -->
27
+
28
+ # distilbert-base-uncased-finetuned-clinc
29
+
30
+ This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the clinc_oos dataset.
31
+ It achieves the following results on the evaluation set:
32
+ - Loss: 0.7778
33
+ - Accuracy: 0.9171
34
+
35
+ ## Model description
36
+
37
+ More information needed
38
+
39
+ ## Intended uses & limitations
40
+
41
+ More information needed
42
+
43
+ ## Training and evaluation data
44
+
45
+ More information needed
46
+
47
+ ## Training procedure
48
+
49
+ ### Training hyperparameters
50
+
51
+ The following hyperparameters were used during training:
52
+ - learning_rate: 2e-05
53
+ - train_batch_size: 48
54
+ - eval_batch_size: 48
55
+ - seed: 42
56
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
57
+ - lr_scheduler_type: linear
58
+ - num_epochs: 5
59
+
60
+ ### Training results
61
+
62
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
63
+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
64
+ | 4.2882 | 1.0 | 318 | 3.2777 | 0.7390 |
65
+ | 2.6228 | 2.0 | 636 | 1.8739 | 0.8287 |
66
+ | 1.5439 | 3.0 | 954 | 1.1619 | 0.8894 |
67
+ | 1.0111 | 4.0 | 1272 | 0.8601 | 0.9094 |
68
+ | 0.7999 | 5.0 | 1590 | 0.7778 | 0.9171 |
69
+
70
+
71
+ ### Framework versions
72
+
73
+ - Transformers 4.11.3
74
+ - Pytorch 1.12.1+cpu
75
+ - Datasets 2.4.0
76
+ - Tokenizers 0.10.3