noniewiem commited on
Commit
122d008
1 Parent(s): c84d09c

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +74 -0
README.md ADDED
@@ -0,0 +1,74 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ tags:
3
+ - generated_from_trainer
4
+ datasets:
5
+ - glue
6
+ metrics:
7
+ - matthews_correlation
8
+ model-index:
9
+ - name: cola-pixel-handwritten-mean-vatrpp-256-128-4-3e-5-15000-420
10
+ results: []
11
+ ---
12
+
13
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
14
+ should probably proofread and complete it, then remove this comment. -->
15
+
16
+ # cola-pixel-handwritten-mean-vatrpp-256-128-4-3e-5-15000-420
17
+
18
+ This model is a fine-tuned version of [noniewiem/pixel-handwritten](https://huggingface.co/noniewiem/pixel-handwritten) on the glue dataset.
19
+ It achieves the following results on the evaluation set:
20
+ - Loss: 0.6172
21
+ - Matthews Correlation: 0.0
22
+
23
+ ## Model description
24
+
25
+ More information needed
26
+
27
+ ## Intended uses & limitations
28
+
29
+ More information needed
30
+
31
+ ## Training and evaluation data
32
+
33
+ More information needed
34
+
35
+ ## Training procedure
36
+
37
+ ### Training hyperparameters
38
+
39
+ The following hyperparameters were used during training:
40
+ - learning_rate: 3e-05
41
+ - train_batch_size: 128
42
+ - eval_batch_size: 8
43
+ - seed: 420
44
+ - gradient_accumulation_steps: 4
45
+ - total_train_batch_size: 512
46
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
47
+ - lr_scheduler_type: linear
48
+ - lr_scheduler_warmup_steps: 200
49
+ - training_steps: 15000
50
+ - mixed_precision_training: Native AMP
51
+
52
+ ### Training results
53
+
54
+ | Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
55
+ |:-------------:|:-----:|:----:|:---------------:|:--------------------:|
56
+ | 0.651 | 6.24 | 100 | 0.6248 | 0.0 |
57
+ | 0.6339 | 12.48 | 200 | 0.6229 | 0.0 |
58
+ | 0.6347 | 18.72 | 300 | 0.6188 | 0.0 |
59
+ | 0.6348 | 24.96 | 400 | 0.6178 | 0.0 |
60
+ | 0.6383 | 31.24 | 500 | 0.6179 | 0.0 |
61
+ | 0.633 | 37.48 | 600 | 0.6183 | 0.0 |
62
+ | 0.633 | 43.72 | 700 | 0.6159 | 0.0 |
63
+ | 0.6333 | 49.96 | 800 | 0.6181 | 0.0 |
64
+ | 0.6369 | 56.24 | 900 | 0.6213 | 0.0 |
65
+ | 0.6359 | 62.48 | 1000 | 0.6191 | 0.0 |
66
+ | 0.6348 | 68.72 | 1100 | 0.6172 | 0.0 |
67
+
68
+
69
+ ### Framework versions
70
+
71
+ - Transformers 4.17.0
72
+ - Pytorch 2.3.0+cu121
73
+ - Datasets 2.0.0
74
+ - Tokenizers 0.13.3