Hugging Face's logo

Noureddinesa
/
Output_LayoutLMv3_v7

Token Classification
Transformers
PyTorch
TensorBoard
layoutlmv3
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
Noureddinesa commited on
Commit
cdd5d10
•
1 Parent(s): 4db8087

End of training

Browse files
Files changed (3) hide show
  1. README.md +90 -0
  2. pytorch_model.bin +1 -1
  3. runs/Apr12_20-20-24_ip-10-192-11-37/events.out.tfevents.1712953510.ip-10-192-11-37.3710.0 +2 -2
README.md ADDED
@@ -0,0 +1,90 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: cc-by-nc-sa-4.0
3
+ tags:
4
+ - generated_from_trainer
5
+ metrics:
6
+ - precision
7
+ - recall
8
+ - f1
9
+ - accuracy
10
+ model-index:
11
+ - name: Output_LayoutLMv3_v10
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
+ # Output_LayoutLMv3_v10
19
+
20
+ This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on an unknown dataset.
21
+ It achieves the following results on the evaluation set:
22
+ - Loss: 0.1075
23
+ - Precision: 0.7928
24
+ - Recall: 0.8
25
+ - F1: 0.7964
26
+ - Accuracy: 0.9723
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: 1e-06
46
+ - train_batch_size: 12
47
+ - eval_batch_size: 12
48
+ - seed: 42
49
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
50
+ - lr_scheduler_type: cosine
51
+ - training_steps: 2600
52
+
53
+ ### Training results
54
+
55
+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
56
+ |:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
57
+ | No log | 9.09 | 100 | 0.4138 | 0.0 | 0.0 | 0.0 | 0.8962 |
58
+ | No log | 18.18 | 200 | 0.2709 | 0.1667 | 0.0273 | 0.0469 | 0.9014 |
59
+ | No log | 27.27 | 300 | 0.2003 | 0.6234 | 0.4364 | 0.5134 | 0.9360 |
60
+ | No log | 36.36 | 400 | 0.1711 | 0.6496 | 0.6909 | 0.6696 | 0.9481 |
61
+ | 0.3384 | 45.45 | 500 | 0.1624 | 0.6667 | 0.7273 | 0.6957 | 0.9498 |
62
+ | 0.3384 | 54.55 | 600 | 0.1502 | 0.6803 | 0.7545 | 0.7155 | 0.9550 |
63
+ | 0.3384 | 63.64 | 700 | 0.1428 | 0.7227 | 0.7818 | 0.7511 | 0.9602 |
64
+ | 0.3384 | 72.73 | 800 | 0.1452 | 0.7049 | 0.7818 | 0.7414 | 0.9550 |
65
+ | 0.3384 | 81.82 | 900 | 0.1260 | 0.7544 | 0.7818 | 0.7679 | 0.9671 |
66
+ | 0.0995 | 90.91 | 1000 | 0.1254 | 0.7544 | 0.7818 | 0.7679 | 0.9671 |
67
+ | 0.0995 | 100.0 | 1100 | 0.1211 | 0.7863 | 0.8364 | 0.8106 | 0.9706 |
68
+ | 0.0995 | 109.09 | 1200 | 0.1093 | 0.7739 | 0.8091 | 0.7911 | 0.9706 |
69
+ | 0.0995 | 118.18 | 1300 | 0.1081 | 0.7946 | 0.8091 | 0.8018 | 0.9723 |
70
+ | 0.0995 | 127.27 | 1400 | 0.1108 | 0.7778 | 0.8273 | 0.8018 | 0.9723 |
71
+ | 0.0608 | 136.36 | 1500 | 0.1115 | 0.7627 | 0.8182 | 0.7895 | 0.9706 |
72
+ | 0.0608 | 145.45 | 1600 | 0.1034 | 0.8053 | 0.8273 | 0.8161 | 0.9740 |
73
+ | 0.0608 | 154.55 | 1700 | 0.1050 | 0.7895 | 0.8182 | 0.8036 | 0.9723 |
74
+ | 0.0608 | 163.64 | 1800 | 0.1093 | 0.7739 | 0.8091 | 0.7911 | 0.9706 |
75
+ | 0.0608 | 172.73 | 1900 | 0.1043 | 0.7965 | 0.8182 | 0.8072 | 0.9723 |
76
+ | 0.0443 | 181.82 | 2000 | 0.1048 | 0.8036 | 0.8182 | 0.8108 | 0.9758 |
77
+ | 0.0443 | 190.91 | 2100 | 0.1067 | 0.8036 | 0.8182 | 0.8108 | 0.9758 |
78
+ | 0.0443 | 200.0 | 2200 | 0.1069 | 0.8036 | 0.8182 | 0.8108 | 0.9740 |
79
+ | 0.0443 | 209.09 | 2300 | 0.1083 | 0.7928 | 0.8 | 0.7964 | 0.9723 |
80
+ | 0.0443 | 218.18 | 2400 | 0.1079 | 0.7928 | 0.8 | 0.7964 | 0.9723 |
81
+ | 0.0381 | 227.27 | 2500 | 0.1076 | 0.7928 | 0.8 | 0.7964 | 0.9723 |
82
+ | 0.0381 | 236.36 | 2600 | 0.1075 | 0.7928 | 0.8 | 0.7964 | 0.9723 |
83
+
84
+
85
+ ### Framework versions
86
+
87
+ - Transformers 4.29.2
88
+ - Pytorch 2.2.2+cu121
89
+ - Datasets 2.18.0
90
+ - Tokenizers 0.13.3
pytorch_model.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:edb88e086df9c832a549a88a9feb376c8249b6cfc51ef0bcf533370d347cecaa
3
  size 501408230
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a2501d773ae7bb0d19b59e1c065d98ff8ba04b563ee86b62a8ef67296c6f042d
3
  size 501408230
runs/Apr12_20-20-24_ip-10-192-11-37/events.out.tfevents.1712953510.ip-10-192-11-37.3710.0 CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:064b6bc638dd632e0c1f149a5e4a5933ae15f1268da27e37197787a7064cccad
3
- size 17222
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6044f76a68f4e91ccc4e8f83d49dfdc8ceb885ddc91c5b8763d06b1c6f0d7adf
3
+ size 18048