Hugging Face's logo

aimarsg
/
testlink-class-2

Token Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
aimarsg commited on
Commit
1b83e43
•
1 Parent(s): e662dcf

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +35 -35
README.md CHANGED
@@ -19,11 +19,11 @@ should probably proofread and complete it, then remove this comment. -->
19
 
20
  This model is a fine-tuned version of [PlanTL-GOB-ES/bsc-bio-ehr-es-pharmaconer](https://huggingface.co/PlanTL-GOB-ES/bsc-bio-ehr-es-pharmaconer) on an unknown dataset.
21
  It achieves the following results on the evaluation set:
22
- - Loss: 0.1903
23
- - Precision: 0.6705
24
  - Recall: 0.6901
25
- - F1: 0.6801
26
- - Accuracy: 0.9752
27
 
28
  ## Model description
29
 
@@ -42,7 +42,7 @@ More information needed
42
  ### Training hyperparameters
43
 
44
  The following hyperparameters were used during training:
45
- - learning_rate: 7e-05
46
  - train_batch_size: 32
47
  - eval_batch_size: 8
48
  - seed: 42
@@ -54,36 +54,36 @@ The following hyperparameters were used during training:
54
 
55
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
56
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
57
- | No log | 1.0 | 29 | 0.1665 | 0.5894 | 0.7135 | 0.6455 | 0.9717 |
58
- | No log | 2.0 | 58 | 0.1726 | 0.6864 | 0.6784 | 0.6824 | 0.9745 |
59
- | No log | 3.0 | 87 | 0.1412 | 0.6398 | 0.6959 | 0.6667 | 0.9748 |
60
- | No log | 4.0 | 116 | 0.1735 | 0.6646 | 0.6374 | 0.6507 | 0.9737 |
61
- | No log | 5.0 | 145 | 0.2060 | 0.4448 | 0.7544 | 0.5597 | 0.9592 |
62
- | No log | 6.0 | 174 | 0.1974 | 0.6529 | 0.6491 | 0.6510 | 0.9710 |
63
- | No log | 7.0 | 203 | 0.1564 | 0.6062 | 0.6842 | 0.6429 | 0.9726 |
64
- | No log | 8.0 | 232 | 0.1690 | 0.5580 | 0.7310 | 0.6329 | 0.9693 |
65
- | No log | 9.0 | 261 | 0.1869 | 0.6805 | 0.6725 | 0.6765 | 0.9736 |
66
- | No log | 10.0 | 290 | 0.1729 | 0.6894 | 0.6491 | 0.6687 | 0.9754 |
67
- | No log | 11.0 | 319 | 0.1793 | 0.7114 | 0.6199 | 0.6625 | 0.9754 |
68
- | No log | 12.0 | 348 | 0.1703 | 0.5805 | 0.6959 | 0.6330 | 0.9723 |
69
- | No log | 13.0 | 377 | 0.1649 | 0.6429 | 0.6842 | 0.6629 | 0.9739 |
70
- | No log | 14.0 | 406 | 0.1832 | 0.7081 | 0.6667 | 0.6867 | 0.9758 |
71
- | No log | 15.0 | 435 | 0.1877 | 0.7063 | 0.6608 | 0.6828 | 0.9763 |
72
- | No log | 16.0 | 464 | 0.1828 | 0.6981 | 0.6491 | 0.6727 | 0.9763 |
73
- | No log | 17.0 | 493 | 0.1666 | 0.6842 | 0.6842 | 0.6842 | 0.9767 |
74
- | 0.0032 | 18.0 | 522 | 0.1795 | 0.5982 | 0.7661 | 0.6718 | 0.9732 |
75
- | 0.0032 | 19.0 | 551 | 0.1728 | 0.6543 | 0.7193 | 0.6852 | 0.9765 |
76
- | 0.0032 | 20.0 | 580 | 0.1781 | 0.6425 | 0.7251 | 0.6813 | 0.9754 |
77
- | 0.0032 | 21.0 | 609 | 0.1747 | 0.6743 | 0.6901 | 0.6821 | 0.9765 |
78
- | 0.0032 | 22.0 | 638 | 0.1815 | 0.6173 | 0.7076 | 0.6594 | 0.9743 |
79
- | 0.0032 | 23.0 | 667 | 0.1863 | 0.6842 | 0.6842 | 0.6842 | 0.9761 |
80
- | 0.0032 | 24.0 | 696 | 0.1871 | 0.6742 | 0.7018 | 0.6877 | 0.9758 |
81
- | 0.0032 | 25.0 | 725 | 0.1912 | 0.6517 | 0.6784 | 0.6648 | 0.9745 |
82
- | 0.0032 | 26.0 | 754 | 0.1907 | 0.6839 | 0.6959 | 0.6899 | 0.9758 |
83
- | 0.0032 | 27.0 | 783 | 0.1904 | 0.6630 | 0.7018 | 0.6818 | 0.9747 |
84
- | 0.0032 | 28.0 | 812 | 0.1895 | 0.6630 | 0.7018 | 0.6818 | 0.9748 |
85
- | 0.0032 | 29.0 | 841 | 0.1903 | 0.6648 | 0.6959 | 0.68 | 0.9750 |
86
- | 0.0032 | 30.0 | 870 | 0.1903 | 0.6705 | 0.6901 | 0.6801 | 0.9752 |
87
 
88
 
89
  ### Framework versions
 
19
 
20
  This model is a fine-tuned version of [PlanTL-GOB-ES/bsc-bio-ehr-es-pharmaconer](https://huggingface.co/PlanTL-GOB-ES/bsc-bio-ehr-es-pharmaconer) on an unknown dataset.
21
  It achieves the following results on the evaluation set:
22
+ - Loss: 0.2116
23
+ - Precision: 0.7516
24
  - Recall: 0.6901
25
+ - F1: 0.7195
26
+ - Accuracy: 0.9758
27
 
28
  ## Model description
29
 
 
42
  ### Training hyperparameters
43
 
44
  The following hyperparameters were used during training:
45
+ - learning_rate: 7.5e-05
46
  - train_batch_size: 32
47
  - eval_batch_size: 8
48
  - seed: 42
 
54
 
55
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
56
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
57
+ | No log | 1.0 | 29 | 0.2388 | 0.7315 | 0.6374 | 0.6813 | 0.9739 |
58
+ | No log | 2.0 | 58 | 0.1956 | 0.6169 | 0.7251 | 0.6667 | 0.9723 |
59
+ | No log | 3.0 | 87 | 0.1637 | 0.6302 | 0.7076 | 0.6667 | 0.9730 |
60
+ | No log | 4.0 | 116 | 0.2107 | 0.6810 | 0.6491 | 0.6647 | 0.9741 |
61
+ | No log | 5.0 | 145 | 0.1987 | 0.6981 | 0.6491 | 0.6727 | 0.9745 |
62
+ | No log | 6.0 | 174 | 0.1524 | 0.7355 | 0.6667 | 0.6994 | 0.9756 |
63
+ | No log | 7.0 | 203 | 0.1933 | 0.7664 | 0.6140 | 0.6818 | 0.9750 |
64
+ | No log | 8.0 | 232 | 0.2150 | 0.7836 | 0.6140 | 0.6885 | 0.9747 |
65
+ | No log | 9.0 | 261 | 0.1700 | 0.7405 | 0.6842 | 0.7112 | 0.9761 |
66
+ | No log | 10.0 | 290 | 0.1626 | 0.6142 | 0.7076 | 0.6576 | 0.9730 |
67
+ | No log | 11.0 | 319 | 0.1826 | 0.7035 | 0.7076 | 0.7055 | 0.9761 |
68
+ | No log | 12.0 | 348 | 0.1724 | 0.6802 | 0.6842 | 0.6822 | 0.9758 |
69
+ | No log | 13.0 | 377 | 0.1823 | 0.7852 | 0.6199 | 0.6928 | 0.9741 |
70
+ | No log | 14.0 | 406 | 0.1833 | 0.7284 | 0.6901 | 0.7087 | 0.9761 |
71
+ | No log | 15.0 | 435 | 0.1816 | 0.5853 | 0.7427 | 0.6546 | 0.9701 |
72
+ | No log | 16.0 | 464 | 0.2084 | 0.7770 | 0.6725 | 0.7210 | 0.9761 |
73
+ | No log | 17.0 | 493 | 0.2043 | 0.7069 | 0.7193 | 0.7130 | 0.9748 |
74
+ | 0.0022 | 18.0 | 522 | 0.1996 | 0.6541 | 0.7076 | 0.6798 | 0.9741 |
75
+ | 0.0022 | 19.0 | 551 | 0.2013 | 0.7484 | 0.6959 | 0.7212 | 0.9763 |
76
+ | 0.0022 | 20.0 | 580 | 0.1933 | 0.7159 | 0.7368 | 0.7262 | 0.9770 |
77
+ | 0.0022 | 21.0 | 609 | 0.1931 | 0.7101 | 0.7018 | 0.7059 | 0.9759 |
78
+ | 0.0022 | 22.0 | 638 | 0.1946 | 0.7052 | 0.7135 | 0.7093 | 0.9759 |
79
+ | 0.0022 | 23.0 | 667 | 0.1968 | 0.6936 | 0.7018 | 0.6977 | 0.9752 |
80
+ | 0.0022 | 24.0 | 696 | 0.2076 | 0.7296 | 0.6784 | 0.7030 | 0.9754 |
81
+ | 0.0022 | 25.0 | 725 | 0.2076 | 0.7296 | 0.6784 | 0.7030 | 0.9756 |
82
+ | 0.0022 | 26.0 | 754 | 0.2051 | 0.6941 | 0.6901 | 0.6921 | 0.9747 |
83
+ | 0.0022 | 27.0 | 783 | 0.2106 | 0.7342 | 0.6784 | 0.7052 | 0.9752 |
84
+ | 0.0022 | 28.0 | 812 | 0.2093 | 0.7312 | 0.6842 | 0.7069 | 0.9752 |
85
+ | 0.0022 | 29.0 | 841 | 0.2112 | 0.7516 | 0.6901 | 0.7195 | 0.9758 |
86
+ | 0.0022 | 30.0 | 870 | 0.2116 | 0.7516 | 0.6901 | 0.7195 | 0.9758 |
87
 
88
 
89
  ### Framework versions