Hugging Face's logo

zhiguoxu
/
bert-base-chinese-finetuned-split

Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
2
zhiguoxu commited on
Commit
ebb117c
•
1 Parent(s): 36afdbb

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +21 -21
README.md CHANGED
@@ -15,7 +15,7 @@ should probably proofread and complete it, then remove this comment. -->
15
 
16
  This model is a fine-tuned version of [bert-base-chinese](https://huggingface.co/bert-base-chinese) on an unknown dataset.
17
  It achieves the following results on the evaluation set:
18
- - Loss: 0.0177
19
  - F1: 1.0
20
 
21
  ## Model description
@@ -47,26 +47,26 @@ The following hyperparameters were used during training:
47
 
48
  | Training Loss | Epoch | Step | Validation Loss | F1 |
49
  |:-------------:|:-----:|:----:|:---------------:|:------:|
50
- | 3.8485 | 1.0 | 1 | 1.9458 | 0.0 |
51
- | 2.0072 | 2.0 | 2 | 0.8351 | 0.0 |
52
- | 0.8935 | 3.0 | 3 | 0.4898 | 0.0 |
53
- | 0.5205 | 4.0 | 4 | 0.3869 | 0.0 |
54
- | 0.4011 | 5.0 | 5 | 0.2898 | 0.0 |
55
- | 0.3135 | 6.0 | 6 | 0.2673 | 0.0769 |
56
- | 0.291 | 7.0 | 7 | 0.2318 | 0.2143 |
57
- | 0.2611 | 8.0 | 8 | 0.1855 | 0.0769 |
58
- | 0.2101 | 9.0 | 9 | 0.1557 | 0.2759 |
59
- | 0.1809 | 10.0 | 10 | 0.1254 | 0.5714 |
60
- | 0.1661 | 11.0 | 11 | 0.1004 | 0.8636 |
61
- | 0.1307 | 12.0 | 12 | 0.0840 | 0.96 |
62
- | 0.1081 | 13.0 | 13 | 0.0696 | 0.96 |
63
- | 0.0942 | 14.0 | 14 | 0.0540 | 0.96 |
64
- | 0.071 | 15.0 | 15 | 0.0407 | 0.9796 |
65
- | 0.0659 | 16.0 | 16 | 0.0318 | 0.9796 |
66
- | 0.0492 | 17.0 | 17 | 0.0256 | 0.9796 |
67
- | 0.0426 | 18.0 | 18 | 0.0214 | 1.0 |
68
- | 0.0407 | 19.0 | 19 | 0.0189 | 1.0 |
69
- | 0.0354 | 20.0 | 20 | 0.0177 | 1.0 |
70
 
71
 
72
  ### Framework versions
 
15
 
16
  This model is a fine-tuned version of [bert-base-chinese](https://huggingface.co/bert-base-chinese) on an unknown dataset.
17
  It achieves the following results on the evaluation set:
18
+ - Loss: 0.0154
19
  - F1: 1.0
20
 
21
  ## Model description
 
47
 
48
  | Training Loss | Epoch | Step | Validation Loss | F1 |
49
  |:-------------:|:-----:|:----:|:---------------:|:------:|
50
+ | 3.4938 | 1.0 | 1 | 1.6750 | 0.0 |
51
+ | 1.7935 | 2.0 | 2 | 0.7116 | 0.0 |
52
+ | 0.7945 | 3.0 | 3 | 0.5122 | 0.0 |
53
+ | 0.5331 | 4.0 | 4 | 0.4022 | 0.0 |
54
+ | 0.4232 | 5.0 | 5 | 0.3155 | 0.0 |
55
+ | 0.3449 | 6.0 | 6 | 0.2706 | 0.0 |
56
+ | 0.2951 | 7.0 | 7 | 0.2177 | 0.1481 |
57
+ | 0.2455 | 8.0 | 8 | 0.1809 | 0.2143 |
58
+ | 0.2115 | 9.0 | 9 | 0.1463 | 0.6486 |
59
+ | 0.1631 | 10.0 | 10 | 0.1210 | 0.8636 |
60
+ | 0.1427 | 11.0 | 11 | 0.0988 | 0.8889 |
61
+ | 0.1227 | 12.0 | 12 | 0.0736 | 0.9583 |
62
+ | 0.098 | 13.0 | 13 | 0.0528 | 0.9796 |
63
+ | 0.0769 | 14.0 | 14 | 0.0399 | 1.0 |
64
+ | 0.0616 | 15.0 | 15 | 0.0319 | 1.0 |
65
+ | 0.0526 | 16.0 | 16 | 0.0267 | 1.0 |
66
+ | 0.0505 | 17.0 | 17 | 0.0216 | 1.0 |
67
+ | 0.0337 | 18.0 | 18 | 0.0182 | 1.0 |
68
+ | 0.034 | 19.0 | 19 | 0.0163 | 1.0 |
69
+ | 0.0275 | 20.0 | 20 | 0.0154 | 1.0 |
70
 
71
 
72
  ### Framework versions