Hugging Face's logo

caush
/
Clickbait1

Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Model card Files
xet
Metrics Community
2
caush commited on
Commit
c6ae772
·
1 Parent(s): 2cab340

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +97 -0
README.md CHANGED
@@ -1,3 +1,100 @@
1
  ---
2
  license: mit
 
 
 
 
 
3
  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
  ---
2
  license: mit
3
+ tags:
4
+ - generated_from_trainer
5
+ model-index:
6
+ - name: Clickbait1
7
+ results: []
8
  ---
9
+
10
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
11
+ should probably proofread and complete it, then remove this comment. -->
12
+
13
+ # Clickbait1
14
+
15
+ This model is a fine-tuned version of [microsoft/Multilingual-MiniLM-L12-H384](https://huggingface.co/microsoft/Multilingual-MiniLM-L12-H384) on the None dataset.
16
+ It achieves the following results on the evaluation set:
17
+ - Loss: 0.0260
18
+
19
+ ## Model description
20
+
21
+ More information needed
22
+
23
+ ## Intended uses & limitations
24
+
25
+ More information needed
26
+
27
+ ## Training and evaluation data
28
+
29
+ More information needed
30
+
31
+ ## Training procedure
32
+
33
+ ### Training hyperparameters
34
+
35
+ The following hyperparameters were used during training:
36
+ - learning_rate: 5e-05
37
+ - train_batch_size: 16
38
+ - eval_batch_size: 16
39
+ - seed: 42
40
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
41
+ - lr_scheduler_type: linear
42
+ - num_epochs: 4
43
+
44
+ ### Training results
45
+
46
+ | Training Loss | Epoch | Step | Validation Loss |
47
+ |:-------------:|:-----:|:----:|:---------------:|
48
+ | No log | 0.05 | 50 | 0.0390 |
49
+ | No log | 0.09 | 100 | 0.0365 |
50
+ | No log | 0.14 | 150 | 0.0321 |
51
+ | No log | 0.18 | 200 | 0.0319 |
52
+ | No log | 0.23 | 250 | 0.0350 |
53
+ | No log | 0.27 | 300 | 0.0317 |
54
+ | No log | 0.32 | 350 | 0.0304 |
55
+ | No log | 0.36 | 400 | 0.0283 |
56
+ | No log | 0.41 | 450 | 0.0300 |
57
+ | 0.0364 | 0.46 | 500 | 0.0282 |
58
+ | 0.0364 | 0.5 | 550 | 0.0285 |
59
+ | 0.0364 | 0.55 | 600 | 0.0276 |
60
+ | 0.0364 | 0.59 | 650 | 0.0278 |
61
+ | 0.0364 | 0.64 | 700 | 0.0293 |
62
+ | 0.0364 | 0.68 | 750 | 0.0280 |
63
+ | 0.0364 | 0.73 | 800 | 0.0320 |
64
+ | 0.0364 | 0.77 | 850 | 0.0269 |
65
+ | 0.0364 | 0.82 | 900 | 0.0269 |
66
+ | 0.0364 | 0.87 | 950 | 0.0271 |
67
+ | 0.0281 | 0.91 | 1000 | 0.0314 |
68
+ | 0.0281 | 0.96 | 1050 | 0.0265 |
69
+ | 0.0281 | 1.0 | 1100 | 0.0295 |
70
+ | 0.0281 | 1.05 | 1150 | 0.0295 |
71
+ | 0.0281 | 1.09 | 1200 | 0.0290 |
72
+ | 0.0281 | 1.14 | 1250 | 0.0281 |
73
+ | 0.0281 | 1.18 | 1300 | 0.0272 |
74
+ | 0.0281 | 1.23 | 1350 | 0.0273 |
75
+ | 0.0281 | 1.28 | 1400 | 0.0287 |
76
+ | 0.0281 | 1.32 | 1450 | 0.0267 |
77
+ | 0.026 | 1.37 | 1500 | 0.0284 |
78
+ | 0.026 | 1.41 | 1550 | 0.0264 |
79
+ | 0.026 | 1.46 | 1600 | 0.0273 |
80
+ | 0.026 | 1.5 | 1650 | 0.0280 |
81
+ | 0.026 | 1.55 | 1700 | 0.0266 |
82
+ | 0.026 | 1.59 | 1750 | 0.0260 |
83
+ | 0.026 | 1.64 | 1800 | 0.0266 |
84
+ | 0.026 | 1.68 | 1850 | 0.0268 |
85
+ | 0.026 | 1.73 | 1900 | 0.0269 |
86
+ | 0.026 | 1.78 | 1950 | 0.0260 |
87
+ | 0.0236 | 1.82 | 2000 | 0.0273 |
88
+ | 0.0236 | 1.87 | 2050 | 0.0272 |
89
+ | 0.0236 | 1.91 | 2100 | 0.0260 |
90
+ | 0.0236 | 1.96 | 2150 | 0.0269 |
91
+ | 0.0236 | 2.0 | 2200 | 0.0286 |
92
+ | 0.0236 | 2.05 | 2250 | 0.0266 |
93
+
94
+
95
+ ### Framework versions
96
+
97
+ - Transformers 4.18.0
98
+ - Pytorch 1.11.0a0+17540c5
99
+ - Datasets 2.1.0
100
+ - Tokenizers 0.12.1