Hugging Face's logo

muhammadravi251001
/
fine-tuned-DatasetQAS-TYDI-QA-ID-with-indobert-base-uncased-with-ITTL-without-freeze-LR-1e-05

Question Answering
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
muhammadravi251001 commited on
Commit
cc48f49
路
1 Parent(s): a2bd88a

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +27 -27
README.md CHANGED
@@ -16,9 +16,9 @@ should probably proofread and complete it, then remove this comment. -->
16
 
17
  This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on the None dataset.
18
  It achieves the following results on the evaluation set:
19
- - Loss: 1.2740
20
- - Exact Match: 56.0847
21
- - F1: 70.6246
22
 
23
  ## Model description
24
 
@@ -38,10 +38,10 @@ More information needed
38
 
39
  The following hyperparameters were used during training:
40
  - learning_rate: 1e-05
41
- - train_batch_size: 8
42
- - eval_batch_size: 8
43
  - seed: 42
44
- - gradient_accumulation_steps: 16
45
  - total_train_batch_size: 128
46
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
47
  - lr_scheduler_type: linear
@@ -51,31 +51,31 @@ The following hyperparameters were used during training:
51
 
52
  | Training Loss | Epoch | Step | Validation Loss | Exact Match | F1 |
53
  |:-------------:|:-----:|:----:|:---------------:|:-----------:|:-------:|
54
- | 6.306 | 0.5 | 19 | 3.7982 | 6.5256 | 20.3655 |
55
- | 6.306 | 1.0 | 38 | 2.8932 | 14.1093 | 26.0679 |
56
- | 3.9254 | 1.5 | 57 | 2.4798 | 19.4004 | 32.1438 |
57
- | 3.9254 | 2.0 | 76 | 2.2955 | 26.1023 | 37.6331 |
58
- | 3.9254 | 2.5 | 95 | 2.1688 | 26.9841 | 39.2632 |
59
- | 2.4328 | 3.0 | 114 | 2.0701 | 30.1587 | 41.3438 |
60
- | 2.4328 | 3.5 | 133 | 1.9789 | 33.1570 | 45.0539 |
61
- | 2.1127 | 4.0 | 152 | 1.8465 | 37.2134 | 48.9042 |
62
- | 2.1127 | 4.5 | 171 | 1.7699 | 38.9771 | 50.9760 |
63
- | 2.1127 | 5.0 | 190 | 1.6885 | 41.0935 | 54.1550 |
64
- | 1.7875 | 5.5 | 209 | 1.5785 | 45.1499 | 58.6783 |
65
- | 1.7875 | 6.0 | 228 | 1.4954 | 49.2063 | 62.7869 |
66
- | 1.7875 | 6.5 | 247 | 1.4186 | 51.8519 | 65.7461 |
67
- | 1.5267 | 7.0 | 266 | 1.3734 | 53.4392 | 67.6141 |
68
- | 1.5267 | 7.5 | 285 | 1.3419 | 54.1446 | 68.2563 |
69
- | 1.3317 | 8.0 | 304 | 1.3116 | 55.5556 | 69.1996 |
70
- | 1.3317 | 8.5 | 323 | 1.2936 | 56.0847 | 69.9806 |
71
- | 1.3317 | 9.0 | 342 | 1.2900 | 56.2610 | 70.1634 |
72
- | 1.2556 | 9.5 | 361 | 1.2771 | 55.7319 | 70.1143 |
73
- | 1.2556 | 10.0 | 380 | 1.2740 | 56.0847 | 70.6246 |
74
 
75
 
76
  ### Framework versions
77
 
78
- - Transformers 4.26.1
79
  - Pytorch 1.13.1+cu117
80
  - Datasets 2.2.0
81
  - Tokenizers 0.13.2
 
16
 
17
  This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on the None dataset.
18
  It achieves the following results on the evaluation set:
19
+ - Loss: 1.2784
20
+ - Exact Match: 53.4392
21
+ - F1: 68.7244
22
 
23
  ## Model description
24
 
 
38
 
39
  The following hyperparameters were used during training:
40
  - learning_rate: 1e-05
41
+ - train_batch_size: 4
42
+ - eval_batch_size: 4
43
  - seed: 42
44
+ - gradient_accumulation_steps: 32
45
  - total_train_batch_size: 128
46
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
47
  - lr_scheduler_type: linear
 
51
 
52
  | Training Loss | Epoch | Step | Validation Loss | Exact Match | F1 |
53
  |:-------------:|:-----:|:----:|:---------------:|:-----------:|:-------:|
54
+ | 6.1764 | 0.5 | 19 | 3.7674 | 10.4056 | 23.6332 |
55
+ | 6.1764 | 1.0 | 38 | 2.7985 | 19.5767 | 32.6228 |
56
+ | 3.8085 | 1.49 | 57 | 2.4169 | 22.0459 | 35.4084 |
57
+ | 3.8085 | 1.99 | 76 | 2.2811 | 25.9259 | 38.3963 |
58
+ | 3.8085 | 2.49 | 95 | 2.1607 | 28.0423 | 40.3901 |
59
+ | 2.3932 | 2.99 | 114 | 2.0488 | 31.0406 | 43.7059 |
60
+ | 2.3932 | 3.49 | 133 | 1.9787 | 34.3915 | 46.3655 |
61
+ | 2.0772 | 3.98 | 152 | 1.8661 | 37.2134 | 49.1483 |
62
+ | 2.0772 | 4.48 | 171 | 1.7893 | 40.2116 | 52.4989 |
63
+ | 2.0772 | 4.98 | 190 | 1.7014 | 41.9753 | 54.9197 |
64
+ | 1.7645 | 5.48 | 209 | 1.5940 | 44.2681 | 58.2134 |
65
+ | 1.7645 | 5.98 | 228 | 1.4972 | 46.2081 | 60.4997 |
66
+ | 1.7645 | 6.47 | 247 | 1.4214 | 48.8536 | 63.4371 |
67
+ | 1.5035 | 6.97 | 266 | 1.3676 | 50.6173 | 65.4663 |
68
+ | 1.5035 | 7.47 | 285 | 1.3357 | 52.2046 | 67.1759 |
69
+ | 1.3206 | 7.97 | 304 | 1.3149 | 53.0864 | 68.0698 |
70
+ | 1.3206 | 8.47 | 323 | 1.2988 | 53.4392 | 68.3971 |
71
+ | 1.3206 | 8.96 | 342 | 1.2894 | 53.6155 | 68.8897 |
72
+ | 1.2472 | 9.46 | 361 | 1.2820 | 53.4392 | 68.5835 |
73
+ | 1.2472 | 9.96 | 380 | 1.2784 | 53.4392 | 68.7244 |
74
 
75
 
76
  ### Framework versions
77
 
78
+ - Transformers 4.27.4
79
  - Pytorch 1.13.1+cu117
80
  - Datasets 2.2.0
81
  - Tokenizers 0.13.2