baptiste commited on
Commit
75f2bdd
1 Parent(s): 79e59b7

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +91 -0
README.md ADDED
@@ -0,0 +1,91 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: mit
3
+ tags:
4
+ - generated_from_trainer
5
+ datasets:
6
+ - conll2003
7
+ metrics:
8
+ - precision
9
+ - recall
10
+ - f1
11
+ - accuracy
12
+ model-index:
13
+ - name: deberta-finetuned-ner
14
+ results:
15
+ - task:
16
+ name: Token Classification
17
+ type: token-classification
18
+ dataset:
19
+ name: conll2003
20
+ type: conll2003
21
+ args: conll2003
22
+ metrics:
23
+ - name: Precision
24
+ type: precision
25
+ value: 0.9577488309953239
26
+ - name: Recall
27
+ type: recall
28
+ value: 0.9651632446987546
29
+ - name: F1
30
+ type: f1
31
+ value: 0.961441743503772
32
+ - name: Accuracy
33
+ type: accuracy
34
+ value: 0.9907182964622135
35
+ ---
36
+
37
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
38
+ should probably proofread and complete it, then remove this comment. -->
39
+
40
+ # deberta-finetuned-ner
41
+
42
+ This model is a fine-tuned version of [microsoft/deberta-base](https://huggingface.co/microsoft/deberta-base) on the conll2003 dataset.
43
+ It achieves the following results on the evaluation set:
44
+ - Loss: 0.0515
45
+ - Precision: 0.9577
46
+ - Recall: 0.9652
47
+ - F1: 0.9614
48
+ - Accuracy: 0.9907
49
+
50
+ ## Model description
51
+
52
+ More information needed
53
+
54
+ ## Intended uses & limitations
55
+
56
+ More information needed
57
+
58
+ ## Training and evaluation data
59
+
60
+ More information needed
61
+
62
+ ## Training procedure
63
+
64
+ ### Training hyperparameters
65
+
66
+ The following hyperparameters were used during training:
67
+ - learning_rate: 2e-05
68
+ - train_batch_size: 8
69
+ - eval_batch_size: 8
70
+ - seed: 42
71
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
72
+ - lr_scheduler_type: linear
73
+ - num_epochs: 5
74
+
75
+ ### Training results
76
+
77
+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
78
+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
79
+ | 0.0742 | 1.0 | 1756 | 0.0526 | 0.9390 | 0.9510 | 0.9450 | 0.9868 |
80
+ | 0.0374 | 2.0 | 3512 | 0.0528 | 0.9421 | 0.9554 | 0.9487 | 0.9879 |
81
+ | 0.0205 | 3.0 | 5268 | 0.0505 | 0.9505 | 0.9636 | 0.9570 | 0.9900 |
82
+ | 0.0089 | 4.0 | 7024 | 0.0528 | 0.9531 | 0.9636 | 0.9583 | 0.9898 |
83
+ | 0.0076 | 5.0 | 8780 | 0.0515 | 0.9577 | 0.9652 | 0.9614 | 0.9907 |
84
+
85
+
86
+ ### Framework versions
87
+
88
+ - Transformers 4.20.1
89
+ - Pytorch 1.12.0+cu113
90
+ - Datasets 2.3.2
91
+ - Tokenizers 0.12.1