Hugging Face's logo

SkyR
/
roberta-base-ours-run-3

Text Classification
Transformers
PyTorch
roberta
Generated from Trainer
Model card Files
xet
Community
2
SkyR commited on
Commit
a5802c0
·
1 Parent(s): 4c40c1d

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +83 -0
README.md ADDED
@@ -0,0 +1,83 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: mit
3
+ tags:
4
+ - generated_from_trainer
5
+ metrics:
6
+ - accuracy
7
+ - precision
8
+ - recall
9
+ - f1
10
+ model-index:
11
+ - name: run-3
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
+ # run-3
19
+
20
+ This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
21
+ It achieves the following results on the evaluation set:
22
+ - Loss: 2.4223
23
+ - Accuracy: 0.75
24
+ - Precision: 0.7128
25
+ - Recall: 0.6998
26
+ - F1: 0.7043
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: 5e-05
46
+ - train_batch_size: 32
47
+ - eval_batch_size: 32
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 | Accuracy | Precision | Recall | F1 |
56
+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
57
+ | 1.0025 | 1.0 | 50 | 0.8925 | 0.63 | 0.6703 | 0.5704 | 0.5060 |
58
+ | 0.8187 | 2.0 | 100 | 0.7915 | 0.595 | 0.6007 | 0.5926 | 0.5344 |
59
+ | 0.5671 | 3.0 | 150 | 0.9573 | 0.695 | 0.6520 | 0.6350 | 0.6380 |
60
+ | 0.3218 | 4.0 | 200 | 0.9195 | 0.68 | 0.6447 | 0.6539 | 0.6461 |
61
+ | 0.2208 | 5.0 | 250 | 1.2429 | 0.715 | 0.6801 | 0.6617 | 0.6663 |
62
+ | 0.1614 | 6.0 | 300 | 1.5295 | 0.71 | 0.6736 | 0.6543 | 0.6423 |
63
+ | 0.1129 | 7.0 | 350 | 2.1055 | 0.71 | 0.6779 | 0.6413 | 0.6511 |
64
+ | 0.098 | 8.0 | 400 | 1.9579 | 0.705 | 0.6697 | 0.6558 | 0.6601 |
65
+ | 0.0479 | 9.0 | 450 | 2.0535 | 0.72 | 0.6794 | 0.6663 | 0.6711 |
66
+ | 0.0173 | 10.0 | 500 | 2.5381 | 0.7 | 0.6838 | 0.6604 | 0.6608 |
67
+ | 0.0308 | 11.0 | 550 | 2.4592 | 0.735 | 0.7014 | 0.6851 | 0.6901 |
68
+ | 0.0265 | 12.0 | 600 | 2.3131 | 0.725 | 0.6910 | 0.6845 | 0.6849 |
69
+ | 0.016 | 13.0 | 650 | 2.4025 | 0.74 | 0.7035 | 0.6915 | 0.6949 |
70
+ | 0.013 | 14.0 | 700 | 2.3933 | 0.745 | 0.7070 | 0.6831 | 0.6909 |
71
+ | 0.016 | 15.0 | 750 | 2.6819 | 0.725 | 0.7006 | 0.6738 | 0.6759 |
72
+ | 0.0126 | 16.0 | 800 | 2.3679 | 0.74 | 0.7050 | 0.6839 | 0.6898 |
73
+ | 0.0023 | 17.0 | 850 | 2.5252 | 0.745 | 0.7119 | 0.6880 | 0.6933 |
74
+ | 0.01 | 18.0 | 900 | 2.5598 | 0.74 | 0.7056 | 0.6828 | 0.6906 |
75
+ | 0.0093 | 19.0 | 950 | 2.4353 | 0.745 | 0.7057 | 0.6922 | 0.6974 |
76
+ | 0.0039 | 20.0 | 1000 | 2.4223 | 0.75 | 0.7128 | 0.6998 | 0.7043 |
77
+
78
+
79
+ ### Framework versions
80
+
81
+ - Transformers 4.25.1
82
+ - Pytorch 1.13.1+cu116
83
+ - Tokenizers 0.13.2