Hugging Face's logo

apwic
/
sentiment-base-0

Transformers
TensorBoard
Safetensors
Indonesian
bert
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
apwic commited on
Commit
981615a
•
1 Parent(s): a1937c3

Model save

Browse files
Files changed (1) hide show
  1. README.md +26 -28
README.md CHANGED
@@ -1,6 +1,4 @@
1
  ---
2
- language:
3
- - id
4
  license: mit
5
  base_model: indolem/indobert-base-uncased
6
  tags:
@@ -22,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
22
 
23
  This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on an unknown dataset.
24
  It achieves the following results on the evaluation set:
25
- - Loss: 0.3540
26
- - Accuracy: 0.8546
27
- - Precision: 0.8233
28
- - Recall: 0.8297
29
- - F1: 0.8264
30
 
31
  ## Model description
32
 
@@ -48,7 +46,7 @@ The following hyperparameters were used during training:
48
  - learning_rate: 5e-05
49
  - train_batch_size: 30
50
  - eval_batch_size: 8
51
- - seed: 1
52
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
53
  - lr_scheduler_type: linear
54
  - num_epochs: 20.0
@@ -57,26 +55,26 @@ The following hyperparameters were used during training:
57
 
58
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
59
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
60
- | 0.5623 | 1.0 | 122 | 0.5053 | 0.7168 | 0.6410 | 0.5796 | 0.5795 |
61
- | 0.518 | 2.0 | 244 | 0.4861 | 0.7293 | 0.6674 | 0.5960 | 0.5998 |
62
- | 0.4835 | 3.0 | 366 | 0.4552 | 0.7694 | 0.7211 | 0.7094 | 0.7145 |
63
- | 0.4497 | 4.0 | 488 | 0.4223 | 0.7945 | 0.7521 | 0.7521 | 0.7521 |
64
- | 0.4266 | 5.0 | 610 | 0.3996 | 0.8170 | 0.7814 | 0.7680 | 0.7741 |
65
- | 0.3907 | 6.0 | 732 | 0.3830 | 0.8195 | 0.7818 | 0.7873 | 0.7845 |
66
- | 0.3742 | 7.0 | 854 | 0.3684 | 0.8346 | 0.8016 | 0.7955 | 0.7984 |
67
- | 0.3616 | 8.0 | 976 | 0.3720 | 0.8271 | 0.7902 | 0.8051 | 0.7968 |
68
- | 0.3294 | 9.0 | 1098 | 0.3689 | 0.8371 | 0.8019 | 0.8147 | 0.8077 |
69
- | 0.3207 | 10.0 | 1220 | 0.3632 | 0.8396 | 0.8047 | 0.8190 | 0.8111 |
70
- | 0.3214 | 11.0 | 1342 | 0.3577 | 0.8371 | 0.8017 | 0.8172 | 0.8086 |
71
- | 0.3167 | 12.0 | 1464 | 0.3607 | 0.8396 | 0.8046 | 0.8215 | 0.8119 |
72
- | 0.289 | 13.0 | 1586 | 0.3684 | 0.8346 | 0.7988 | 0.8155 | 0.8061 |
73
- | 0.2997 | 14.0 | 1708 | 0.3480 | 0.8496 | 0.8193 | 0.8161 | 0.8177 |
74
- | 0.2986 | 15.0 | 1830 | 0.3576 | 0.8496 | 0.8169 | 0.8261 | 0.8212 |
75
- | 0.2914 | 16.0 | 1952 | 0.3497 | 0.8496 | 0.8180 | 0.8211 | 0.8195 |
76
- | 0.278 | 17.0 | 2074 | 0.3540 | 0.8521 | 0.8207 | 0.8254 | 0.8229 |
77
- | 0.2887 | 18.0 | 2196 | 0.3516 | 0.8521 | 0.8207 | 0.8254 | 0.8229 |
78
- | 0.2829 | 19.0 | 2318 | 0.3537 | 0.8521 | 0.8207 | 0.8254 | 0.8229 |
79
- | 0.2771 | 20.0 | 2440 | 0.3540 | 0.8546 | 0.8233 | 0.8297 | 0.8264 |
80
 
81
 
82
  ### Framework versions
 
1
  ---
 
 
2
  license: mit
3
  base_model: indolem/indobert-base-uncased
4
  tags:
 
20
 
21
  This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on an unknown dataset.
22
  It achieves the following results on the evaluation set:
23
+ - Loss: 0.8105
24
+ - Accuracy: 0.9023
25
+ - Precision: 0.8828
26
+ - Recall: 0.8808
27
+ - F1: 0.8818
28
 
29
  ## Model description
30
 
 
46
  - learning_rate: 5e-05
47
  - train_batch_size: 30
48
  - eval_batch_size: 8
49
+ - seed: 42
50
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
51
  - lr_scheduler_type: linear
52
  - num_epochs: 20.0
 
55
 
56
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
57
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
58
+ | 0.4267 | 1.0 | 122 | 0.3586 | 0.8797 | 0.8892 | 0.8149 | 0.8409 |
59
+ | 0.2234 | 2.0 | 244 | 0.3668 | 0.8697 | 0.8395 | 0.8853 | 0.8539 |
60
+ | 0.126 | 3.0 | 366 | 0.4554 | 0.8922 | 0.8632 | 0.8938 | 0.8756 |
61
+ | 0.0886 | 4.0 | 488 | 0.4441 | 0.9073 | 0.8957 | 0.8769 | 0.8855 |
62
+ | 0.0611 | 5.0 | 610 | 0.4923 | 0.9048 | 0.8881 | 0.8801 | 0.8839 |
63
+ | 0.0366 | 6.0 | 732 | 0.6796 | 0.8997 | 0.8748 | 0.8891 | 0.8814 |
64
+ | 0.0358 | 7.0 | 854 | 0.5746 | 0.9048 | 0.8935 | 0.8726 | 0.8821 |
65
+ | 0.0272 | 8.0 | 976 | 0.5953 | 0.8947 | 0.8718 | 0.8755 | 0.8737 |
66
+ | 0.0231 | 9.0 | 1098 | 0.6506 | 0.8997 | 0.8891 | 0.8641 | 0.8752 |
67
+ | 0.0141 | 10.0 | 1220 | 0.6854 | 0.9023 | 0.8814 | 0.8833 | 0.8824 |
68
+ | 0.023 | 11.0 | 1342 | 0.7218 | 0.9023 | 0.8814 | 0.8833 | 0.8824 |
69
+ | 0.0067 | 12.0 | 1464 | 0.7695 | 0.9023 | 0.8814 | 0.8833 | 0.8824 |
70
+ | 0.0064 | 13.0 | 1586 | 0.9004 | 0.8797 | 0.8496 | 0.8749 | 0.8602 |
71
+ | 0.0103 | 14.0 | 1708 | 0.7978 | 0.9023 | 0.8792 | 0.8883 | 0.8835 |
72
+ | 0.0072 | 15.0 | 1830 | 0.8251 | 0.8997 | 0.8791 | 0.8791 | 0.8791 |
73
+ | 0.0054 | 16.0 | 1952 | 0.7715 | 0.9023 | 0.8814 | 0.8833 | 0.8824 |
74
+ | 0.0038 | 17.0 | 2074 | 0.7821 | 0.9073 | 0.8920 | 0.8819 | 0.8867 |
75
+ | 0.0021 | 18.0 | 2196 | 0.8211 | 0.8972 | 0.8754 | 0.8773 | 0.8764 |
76
+ | 0.0022 | 19.0 | 2318 | 0.8162 | 0.8997 | 0.8791 | 0.8791 | 0.8791 |
77
+ | 0.0027 | 20.0 | 2440 | 0.8105 | 0.9023 | 0.8828 | 0.8808 | 0.8818 |
78
 
79
 
80
  ### Framework versions