Hugging Face's logo

Shushant
/
ApplicantTrackingSystemBERT

Fill-Mask
Transformers
PyTorch
TensorBoard
English
bert
Generated from Trainer
Model card Files
xet
Metrics Community
1
Shushant Pudasaini commited on
Commit
57ccd9f
·
1 Parent(s): 8d87817

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +99 -0
README.md ADDED
@@ -0,0 +1,99 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ tags:
3
+ - generated_from_trainer
4
+ model-index:
5
+ - name: training_bert
6
+ results: []
7
+ ---
8
+
9
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
10
+ should probably proofread and complete it, then remove this comment. -->
11
+
12
+ # training_bert
13
+
14
+ This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
15
+ It achieves the following results on the evaluation set:
16
+ - Loss: 4.0495
17
+
18
+ ## Model description
19
+
20
+ More information needed
21
+
22
+ ## Intended uses & limitations
23
+
24
+ More information needed
25
+
26
+ ## Training and evaluation data
27
+
28
+ More information needed
29
+
30
+ ## Training procedure
31
+
32
+ ### Training hyperparameters
33
+
34
+ The following hyperparameters were used during training:
35
+ - learning_rate: 5e-05
36
+ - train_batch_size: 128
37
+ - eval_batch_size: 128
38
+ - seed: 42
39
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
40
+ - lr_scheduler_type: linear
41
+ - num_epochs: 5
42
+
43
+ ### Training results
44
+
45
+ | Training Loss | Epoch | Step | Validation Loss |
46
+ |:-------------:|:-----:|:-----:|:---------------:|
47
+ | 6.7862 | 0.11 | 500 | 6.9461 |
48
+ | 5.9428 | 0.22 | 1000 | 6.4640 |
49
+ | 5.5463 | 0.33 | 1500 | 6.2736 |
50
+ | 5.1871 | 0.44 | 2000 | 5.8517 |
51
+ | 4.896 | 0.55 | 2500 | 5.6070 |
52
+ | 4.6557 | 0.66 | 3000 | 5.4669 |
53
+ | 4.4832 | 0.77 | 3500 | 5.3318 |
54
+ | 4.3368 | 0.88 | 4000 | 5.2414 |
55
+ | 4.1887 | 0.99 | 4500 | 5.0666 |
56
+ | 4.053 | 1.1 | 5000 | 4.9532 |
57
+ | 3.9653 | 1.21 | 5500 | 4.8288 |
58
+ | 3.8865 | 1.33 | 6000 | 4.6741 |
59
+ | 3.8294 | 1.44 | 6500 | 4.7943 |
60
+ | 3.7565 | 1.55 | 7000 | 4.7336 |
61
+ | 3.673 | 1.66 | 7500 | 4.4760 |
62
+ | 3.6447 | 1.77 | 8000 | 4.5856 |
63
+ | 3.5808 | 1.88 | 8500 | 4.6133 |
64
+ | 3.5329 | 1.99 | 9000 | 4.4766 |
65
+ | 3.4916 | 2.1 | 9500 | 4.5085 |
66
+ | 3.4392 | 2.21 | 10000 | 4.5306 |
67
+ | 3.4333 | 2.32 | 10500 | 4.5433 |
68
+ | 3.3905 | 2.43 | 11000 | 4.1829 |
69
+ | 3.3701 | 2.54 | 11500 | 4.2976 |
70
+ | 3.3345 | 2.65 | 12000 | 4.2817 |
71
+ | 3.2815 | 2.76 | 12500 | 4.3146 |
72
+ | 3.2689 | 2.87 | 13000 | 4.2634 |
73
+ | 3.2401 | 2.98 | 13500 | 4.0907 |
74
+ | 3.2068 | 3.09 | 14000 | 4.1130 |
75
+ | 3.2097 | 3.2 | 14500 | 4.2001 |
76
+ | 3.1627 | 3.31 | 15000 | 4.0852 |
77
+ | 3.1647 | 3.42 | 15500 | 4.0383 |
78
+ | 3.1294 | 3.53 | 16000 | 3.9377 |
79
+ | 3.1166 | 3.64 | 16500 | 4.0733 |
80
+ | 3.1028 | 3.75 | 17000 | 3.8429 |
81
+ | 3.0903 | 3.86 | 17500 | 4.1127 |
82
+ | 3.0877 | 3.98 | 18000 | 3.8605 |
83
+ | 3.0407 | 4.09 | 18500 | 3.8482 |
84
+ | 3.0452 | 4.2 | 19000 | 4.0345 |
85
+ | 3.0496 | 4.31 | 19500 | 3.8602 |
86
+ | 3.0229 | 4.42 | 20000 | 4.2268 |
87
+ | 3.0157 | 4.53 | 20500 | 3.8028 |
88
+ | 3.0037 | 4.64 | 21000 | 3.8668 |
89
+ | 2.9992 | 4.75 | 21500 | 3.9542 |
90
+ | 3.016 | 4.86 | 22000 | 3.9090 |
91
+ | 2.9804 | 4.97 | 22500 | 4.0495 |
92
+
93
+
94
+ ### Framework versions
95
+
96
+ - Transformers 4.25.1
97
+ - Pytorch 1.8.0+cu111
98
+ - Datasets 2.7.1
99
+ - Tokenizers 0.13.2