Hugging Face's logo

aimarsg
/
ner-2

Token Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
aimarsg commited on
Commit
2f3d323
•
1 Parent(s): c1c1675

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +94 -0
README.md ADDED
@@ -0,0 +1,94 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ tags:
4
+ - generated_from_trainer
5
+ metrics:
6
+ - precision
7
+ - recall
8
+ - f1
9
+ - accuracy
10
+ model-index:
11
+ - name: ner-2
12
+ results: []
13
+ ---
14
+
15
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
16
+ should probably proofread and complete it, then remove this comment. -->
17
+
18
+ # ner-2
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: 0.1791
23
+ - Precision: 0.5224
24
+ - Recall: 0.6222
25
+ - F1: 0.5680
26
+ - Accuracy: 0.9631
27
+
28
+ ## Model description
29
+
30
+ More information needed
31
+
32
+ ## Intended uses & limitations
33
+
34
+ More information needed
35
+
36
+ ## Training and evaluation data
37
+
38
+ More information needed
39
+
40
+ ## Training procedure
41
+
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
49
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
50
+ - lr_scheduler_type: linear
51
+ - num_epochs: 30
52
+
53
+ ### Training results
54
+
55
+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
56
+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
57
+ | No log | 1.0 | 29 | 0.2584 | 0.0 | 0.0 | 0.0 | 0.9365 |
58
+ | No log | 2.0 | 58 | 0.2386 | 0.1364 | 0.0133 | 0.0243 | 0.9458 |
59
+ | No log | 3.0 | 87 | 0.2312 | 0.2368 | 0.04 | 0.0684 | 0.9466 |
60
+ | No log | 4.0 | 116 | 0.1806 | 0.2809 | 0.2222 | 0.2481 | 0.9422 |
61
+ | No log | 5.0 | 145 | 0.1446 | 0.4453 | 0.2711 | 0.3370 | 0.9558 |
62
+ | No log | 6.0 | 174 | 0.1575 | 0.3778 | 0.3022 | 0.3358 | 0.9493 |
63
+ | No log | 7.0 | 203 | 0.1255 | 0.5081 | 0.4178 | 0.4585 | 0.9601 |
64
+ | No log | 8.0 | 232 | 0.1290 | 0.4599 | 0.4844 | 0.4719 | 0.9596 |
65
+ | No log | 9.0 | 261 | 0.1383 | 0.4844 | 0.4844 | 0.4844 | 0.9597 |
66
+ | No log | 10.0 | 290 | 0.1534 | 0.4313 | 0.6133 | 0.5064 | 0.9519 |
67
+ | No log | 11.0 | 319 | 0.1575 | 0.4423 | 0.6133 | 0.5140 | 0.9560 |
68
+ | No log | 12.0 | 348 | 0.1437 | 0.5888 | 0.5156 | 0.5498 | 0.9670 |
69
+ | No log | 13.0 | 377 | 0.1605 | 0.5 | 0.5911 | 0.5418 | 0.9589 |
70
+ | No log | 14.0 | 406 | 0.1529 | 0.5459 | 0.5289 | 0.5372 | 0.9640 |
71
+ | No log | 15.0 | 435 | 0.1569 | 0.5097 | 0.5867 | 0.5455 | 0.9618 |
72
+ | No log | 16.0 | 464 | 0.1656 | 0.4980 | 0.5644 | 0.5292 | 0.9607 |
73
+ | No log | 17.0 | 493 | 0.1602 | 0.5583 | 0.5956 | 0.5763 | 0.9622 |
74
+ | 0.0843 | 18.0 | 522 | 0.1767 | 0.4897 | 0.6356 | 0.5532 | 0.9589 |
75
+ | 0.0843 | 19.0 | 551 | 0.1642 | 0.5551 | 0.6044 | 0.5787 | 0.9641 |
76
+ | 0.0843 | 20.0 | 580 | 0.1635 | 0.6418 | 0.5733 | 0.6056 | 0.9679 |
77
+ | 0.0843 | 21.0 | 609 | 0.1706 | 0.5423 | 0.6267 | 0.5814 | 0.9635 |
78
+ | 0.0843 | 22.0 | 638 | 0.1691 | 0.5437 | 0.6089 | 0.5744 | 0.9638 |
79
+ | 0.0843 | 23.0 | 667 | 0.1743 | 0.5357 | 0.6 | 0.5660 | 0.9631 |
80
+ | 0.0843 | 24.0 | 696 | 0.1800 | 0.5176 | 0.6533 | 0.5776 | 0.9627 |
81
+ | 0.0843 | 25.0 | 725 | 0.1789 | 0.5 | 0.6 | 0.5455 | 0.9620 |
82
+ | 0.0843 | 26.0 | 754 | 0.1754 | 0.5388 | 0.5867 | 0.5617 | 0.9638 |
83
+ | 0.0843 | 27.0 | 783 | 0.1797 | 0.5164 | 0.6311 | 0.5680 | 0.9627 |
84
+ | 0.0843 | 28.0 | 812 | 0.1816 | 0.5321 | 0.6267 | 0.5755 | 0.9633 |
85
+ | 0.0843 | 29.0 | 841 | 0.1793 | 0.5222 | 0.6267 | 0.5697 | 0.9631 |
86
+ | 0.0843 | 30.0 | 870 | 0.1791 | 0.5224 | 0.6222 | 0.5680 | 0.9631 |
87
+
88
+
89
+ ### Framework versions
90
+
91
+ - Transformers 4.28.1
92
+ - Pytorch 2.0.0+cu118
93
+ - Datasets 2.11.0
94
+ - Tokenizers 0.13.3