Hugging Face's logo

Buseak
/
spellcorrector_1709_v7

Token Classification
Transformers
PyTorch
TensorBoard
canine
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
Buseak commited on
Commit
46e99ce
•
1 Parent(s): 6bbee39

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +84 -0
README.md ADDED
@@ -0,0 +1,84 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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: spellcorrector_1709_v7
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
+ # spellcorrector_1709_v7
19
+
20
+ This model is a fine-tuned version of [google/canine-s](https://huggingface.co/google/canine-s) on the None dataset.
21
+ It achieves the following results on the evaluation set:
22
+ - Loss: 0.0885
23
+ - Precision: 0.9610
24
+ - Recall: 0.9739
25
+ - F1: 0.9674
26
+ - Accuracy: 0.9742
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: 2e-05
46
+ - train_batch_size: 4
47
+ - eval_batch_size: 4
48
+ - seed: 42
49
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
50
+ - lr_scheduler_type: linear
51
+ - num_epochs: 20
52
+
53
+ ### Training results
54
+
55
+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
56
+ |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
57
+ | 0.2583 | 1.0 | 1951 | 0.2210 | 0.8849 | 0.9710 | 0.9260 | 0.9443 |
58
+ | 0.2244 | 2.0 | 3902 | 0.1992 | 0.8954 | 0.9685 | 0.9305 | 0.9466 |
59
+ | 0.2099 | 3.0 | 5853 | 0.1868 | 0.9021 | 0.9684 | 0.9341 | 0.9482 |
60
+ | 0.1989 | 4.0 | 7804 | 0.1789 | 0.9109 | 0.9634 | 0.9364 | 0.9500 |
61
+ | 0.1926 | 5.0 | 9755 | 0.1694 | 0.9141 | 0.9652 | 0.9389 | 0.9518 |
62
+ | 0.1837 | 6.0 | 11706 | 0.1605 | 0.9160 | 0.9697 | 0.9421 | 0.9540 |
63
+ | 0.1817 | 7.0 | 13657 | 0.1547 | 0.9209 | 0.9656 | 0.9427 | 0.9549 |
64
+ | 0.1723 | 8.0 | 15608 | 0.1484 | 0.9226 | 0.9687 | 0.9451 | 0.9564 |
65
+ | 0.1692 | 9.0 | 17559 | 0.1442 | 0.9269 | 0.9649 | 0.9455 | 0.9571 |
66
+ | 0.1642 | 10.0 | 19510 | 0.1386 | 0.9269 | 0.9697 | 0.9478 | 0.9587 |
67
+ | 0.1578 | 11.0 | 21461 | 0.1327 | 0.9310 | 0.9693 | 0.9497 | 0.9600 |
68
+ | 0.148 | 12.0 | 23412 | 0.1231 | 0.9393 | 0.9674 | 0.9532 | 0.9630 |
69
+ | 0.1455 | 13.0 | 25363 | 0.1172 | 0.9413 | 0.9711 | 0.9560 | 0.9653 |
70
+ | 0.1402 | 14.0 | 27314 | 0.1123 | 0.9476 | 0.9673 | 0.9573 | 0.9662 |
71
+ | 0.1323 | 15.0 | 29265 | 0.1056 | 0.9511 | 0.9694 | 0.9602 | 0.9685 |
72
+ | 0.1269 | 16.0 | 31216 | 0.0989 | 0.9521 | 0.9740 | 0.9629 | 0.9709 |
73
+ | 0.1225 | 17.0 | 33167 | 0.0953 | 0.9575 | 0.9716 | 0.9645 | 0.9720 |
74
+ | 0.1186 | 18.0 | 35118 | 0.0907 | 0.9582 | 0.9744 | 0.9662 | 0.9735 |
75
+ | 0.1169 | 19.0 | 37069 | 0.0897 | 0.9606 | 0.9734 | 0.9670 | 0.9738 |
76
+ | 0.113 | 20.0 | 39020 | 0.0885 | 0.9610 | 0.9739 | 0.9674 | 0.9742 |
77
+
78
+
79
+ ### Framework versions
80
+
81
+ - Transformers 4.28.0
82
+ - Pytorch 2.0.1+cu118
83
+ - Datasets 2.14.5
84
+ - Tokenizers 0.13.3