muhtasham commited on
Commit
c106643
1 Parent(s): 7ca7934

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +92 -0
README.md ADDED
@@ -0,0 +1,92 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ tags:
4
+ - generated_from_trainer
5
+ datasets:
6
+ - wnut_17
7
+ metrics:
8
+ - precision
9
+ - recall
10
+ - f1
11
+ - accuracy
12
+ model-index:
13
+ - name: bert-small-finetuned-xglue-ner-longer10
14
+ results:
15
+ - task:
16
+ name: Token Classification
17
+ type: token-classification
18
+ dataset:
19
+ name: wnut_17
20
+ type: wnut_17
21
+ config: wnut_17
22
+ split: train
23
+ args: wnut_17
24
+ metrics:
25
+ - name: Precision
26
+ type: precision
27
+ value: 0.5436746987951807
28
+ - name: Recall
29
+ type: recall
30
+ value: 0.4318181818181818
31
+ - name: F1
32
+ type: f1
33
+ value: 0.48133333333333334
34
+ - name: Accuracy
35
+ type: accuracy
36
+ value: 0.9250487441220323
37
+ ---
38
+
39
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
40
+ should probably proofread and complete it, then remove this comment. -->
41
+
42
+ # bert-small-finetuned-xglue-ner-longer10
43
+
44
+ This model is a fine-tuned version of [muhtasham/bert-small-finetuned-xglue-ner-longer6](https://huggingface.co/muhtasham/bert-small-finetuned-xglue-ner-longer6) on the wnut_17 dataset.
45
+ It achieves the following results on the evaluation set:
46
+ - Loss: 0.4645
47
+ - Precision: 0.5437
48
+ - Recall: 0.4318
49
+ - F1: 0.4813
50
+ - Accuracy: 0.9250
51
+
52
+ ## Model description
53
+
54
+ More information needed
55
+
56
+ ## Intended uses & limitations
57
+
58
+ More information needed
59
+
60
+ ## Training and evaluation data
61
+
62
+ More information needed
63
+
64
+ ## Training procedure
65
+
66
+ ### Training hyperparameters
67
+
68
+ The following hyperparameters were used during training:
69
+ - learning_rate: 2e-05
70
+ - train_batch_size: 8
71
+ - eval_batch_size: 8
72
+ - seed: 42
73
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
74
+ - lr_scheduler_type: linear
75
+ - num_epochs: 4
76
+
77
+ ### Training results
78
+
79
+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
80
+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
81
+ | No log | 1.0 | 425 | 0.4872 | 0.6164 | 0.3959 | 0.4822 | 0.9253 |
82
+ | 0.0385 | 2.0 | 850 | 0.4528 | 0.5512 | 0.4246 | 0.4797 | 0.9256 |
83
+ | 0.0317 | 3.0 | 1275 | 0.4638 | 0.5431 | 0.4294 | 0.4796 | 0.9246 |
84
+ | 0.0308 | 4.0 | 1700 | 0.4645 | 0.5437 | 0.4318 | 0.4813 | 0.9250 |
85
+
86
+
87
+ ### Framework versions
88
+
89
+ - Transformers 4.21.1
90
+ - Pytorch 1.12.1+cu113
91
+ - Datasets 2.4.0
92
+ - Tokenizers 0.12.1