Hugging Face's logo

henryscheible
/
gpt2_stereoset_finetuned

Text Classification
Transformers
PyTorch
gpt2
Generated from Trainer
Eval Results
text-generation-inference
Inference Endpoints
Model card Files Community
3
henryscheible commited on
Commit
8ca41e2
•
1 Parent(s): 1678c1a

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +121 -0
README.md ADDED
@@ -0,0 +1,121 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: mit
3
+ tags:
4
+ - generated_from_trainer
5
+ datasets:
6
+ - stereoset
7
+ metrics:
8
+ - accuracy
9
+ model-index:
10
+ - name: gpt2_stereoset_finetuned
11
+ results:
12
+ - task:
13
+ name: Text Classification
14
+ type: text-classification
15
+ dataset:
16
+ name: stereoset
17
+ type: stereoset
18
+ config: intersentence
19
+ split: validation
20
+ args: intersentence
21
+ metrics:
22
+ - name: Accuracy
23
+ type: accuracy
24
+ value: 0.7087912087912088
25
+ ---
26
+
27
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
28
+ should probably proofread and complete it, then remove this comment. -->
29
+
30
+ # gpt2_stereoset_finetuned
31
+
32
+ This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the stereoset dataset.
33
+ It achieves the following results on the evaluation set:
34
+ - Loss: 0.6545
35
+ - Accuracy: 0.7088
36
+
37
+ ## Model description
38
+
39
+ More information needed
40
+
41
+ ## Intended uses & limitations
42
+
43
+ More information needed
44
+
45
+ ## Training and evaluation data
46
+
47
+ More information needed
48
+
49
+ ## Training procedure
50
+
51
+ ### Training hyperparameters
52
+
53
+ The following hyperparameters were used during training:
54
+ - learning_rate: 5e-05
55
+ - train_batch_size: 128
56
+ - eval_batch_size: 64
57
+ - seed: 42
58
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
59
+ - lr_scheduler_type: linear
60
+ - num_epochs: 10
61
+
62
+ ### Training results
63
+
64
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
65
+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
66
+ | No log | 0.21 | 5 | 1.1855 | 0.5259 |
67
+ | No log | 0.42 | 10 | 0.7056 | 0.5338 |
68
+ | No log | 0.62 | 15 | 0.7009 | 0.5400 |
69
+ | No log | 0.83 | 20 | 0.7230 | 0.5173 |
70
+ | No log | 1.04 | 25 | 0.6666 | 0.5989 |
71
+ | No log | 1.25 | 30 | 0.6812 | 0.5699 |
72
+ | No log | 1.46 | 35 | 0.6479 | 0.6272 |
73
+ | No log | 1.67 | 40 | 0.6323 | 0.6484 |
74
+ | No log | 1.88 | 45 | 0.6306 | 0.6515 |
75
+ | No log | 2.08 | 50 | 0.6474 | 0.6633 |
76
+ | No log | 2.29 | 55 | 0.6158 | 0.6641 |
77
+ | No log | 2.5 | 60 | 0.6059 | 0.6703 |
78
+ | No log | 2.71 | 65 | 0.6151 | 0.6695 |
79
+ | No log | 2.92 | 70 | 0.5860 | 0.6782 |
80
+ | No log | 3.12 | 75 | 0.5808 | 0.6907 |
81
+ | No log | 3.33 | 80 | 0.5953 | 0.6915 |
82
+ | No log | 3.54 | 85 | 0.5860 | 0.6994 |
83
+ | No log | 3.75 | 90 | 0.5918 | 0.6947 |
84
+ | No log | 3.96 | 95 | 0.5915 | 0.6797 |
85
+ | No log | 4.17 | 100 | 0.5779 | 0.7041 |
86
+ | No log | 4.38 | 105 | 0.5902 | 0.7151 |
87
+ | No log | 4.58 | 110 | 0.5740 | 0.7080 |
88
+ | No log | 4.79 | 115 | 0.5640 | 0.7088 |
89
+ | No log | 5.0 | 120 | 0.5786 | 0.6947 |
90
+ | No log | 5.21 | 125 | 0.5892 | 0.6978 |
91
+ | No log | 5.42 | 130 | 0.5722 | 0.7096 |
92
+ | No log | 5.62 | 135 | 0.5743 | 0.7064 |
93
+ | No log | 5.83 | 140 | 0.5873 | 0.7057 |
94
+ | No log | 6.04 | 145 | 0.5915 | 0.7033 |
95
+ | No log | 6.25 | 150 | 0.5978 | 0.7009 |
96
+ | No log | 6.46 | 155 | 0.6034 | 0.6931 |
97
+ | No log | 6.67 | 160 | 0.5908 | 0.7111 |
98
+ | No log | 6.88 | 165 | 0.5954 | 0.6947 |
99
+ | No log | 7.08 | 170 | 0.5882 | 0.7033 |
100
+ | No log | 7.29 | 175 | 0.5895 | 0.7151 |
101
+ | No log | 7.5 | 180 | 0.6077 | 0.7104 |
102
+ | No log | 7.71 | 185 | 0.6121 | 0.7151 |
103
+ | No log | 7.92 | 190 | 0.6086 | 0.7151 |
104
+ | No log | 8.12 | 195 | 0.6182 | 0.7127 |
105
+ | No log | 8.33 | 200 | 0.6412 | 0.7072 |
106
+ | No log | 8.54 | 205 | 0.6425 | 0.7049 |
107
+ | No log | 8.75 | 210 | 0.6369 | 0.7135 |
108
+ | No log | 8.96 | 215 | 0.6405 | 0.7111 |
109
+ | No log | 9.17 | 220 | 0.6431 | 0.7135 |
110
+ | No log | 9.38 | 225 | 0.6474 | 0.7127 |
111
+ | No log | 9.58 | 230 | 0.6595 | 0.7041 |
112
+ | No log | 9.79 | 235 | 0.6580 | 0.7041 |
113
+ | No log | 10.0 | 240 | 0.6545 | 0.7088 |
114
+
115
+
116
+ ### Framework versions
117
+
118
+ - Transformers 4.26.1
119
+ - Pytorch 1.13.1
120
+ - Datasets 2.9.0
121
+ - Tokenizers 0.13.2