Hugging Face's logo

luogefeng
/
git-base-pokemon

Text Generation
Transformers
PyTorch
git
Generated from Trainer
Inference Endpoints
Model card Files Community
luogefeng commited on
Commit
f1ac37a
•
1 Parent(s): 2f3966f

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +108 -0
README.md ADDED
@@ -0,0 +1,108 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: mit
3
+ tags:
4
+ - generated_from_trainer
5
+ datasets:
6
+ - imagefolder
7
+ model-index:
8
+ - name: git-base-pokemon
9
+ results: []
10
+ ---
11
+
12
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
13
+ should probably proofread and complete it, then remove this comment. -->
14
+
15
+ # git-base-pokemon
16
+
17
+ This model is a fine-tuned version of [microsoft/git-base](https://huggingface.co/microsoft/git-base) on the imagefolder dataset.
18
+ It achieves the following results on the evaluation set:
19
+ - Loss: 0.0396
20
+ - Wer Score: 6.0488
21
+
22
+ ## Model description
23
+
24
+ More information needed
25
+
26
+ ## Intended uses & limitations
27
+
28
+ More information needed
29
+
30
+ ## Training and evaluation data
31
+
32
+ More information needed
33
+
34
+ ## Training procedure
35
+
36
+ ### Training hyperparameters
37
+
38
+ The following hyperparameters were used during training:
39
+ - learning_rate: 5e-05
40
+ - train_batch_size: 8
41
+ - eval_batch_size: 8
42
+ - seed: 42
43
+ - gradient_accumulation_steps: 2
44
+ - total_train_batch_size: 16
45
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
46
+ - lr_scheduler_type: linear
47
+ - num_epochs: 50
48
+ - mixed_precision_training: Native AMP
49
+
50
+ ### Training results
51
+
52
+ | Training Loss | Epoch | Step | Validation Loss | Wer Score |
53
+ |:-------------:|:-----:|:----:|:---------------:|:---------:|
54
+ | 7.3484 | 1.06 | 50 | 4.4320 | 10.6547 |
55
+ | 2.1536 | 2.13 | 100 | 0.2910 | 1.8947 |
56
+ | 0.0909 | 3.19 | 150 | 0.0322 | 0.3684 |
57
+ | 0.0278 | 4.26 | 200 | 0.0275 | 0.3659 |
58
+ | 0.0211 | 5.32 | 250 | 0.0271 | 0.8858 |
59
+ | 0.0185 | 6.38 | 300 | 0.0267 | 0.6778 |
60
+ | 0.0155 | 7.45 | 350 | 0.0272 | 7.8190 |
61
+ | 0.0129 | 8.51 | 400 | 0.0279 | 3.2452 |
62
+ | 0.0108 | 9.57 | 450 | 0.0280 | 15.0462 |
63
+ | 0.0082 | 10.64 | 500 | 0.0291 | 10.0372 |
64
+ | 0.0069 | 11.7 | 550 | 0.0303 | 15.1592 |
65
+ | 0.0048 | 12.77 | 600 | 0.0321 | 15.4493 |
66
+ | 0.0033 | 13.83 | 650 | 0.0322 | 16.2439 |
67
+ | 0.0022 | 14.89 | 700 | 0.0350 | 17.7125 |
68
+ | 0.0017 | 15.96 | 750 | 0.0340 | 16.8357 |
69
+ | 0.0011 | 17.02 | 800 | 0.0354 | 16.8780 |
70
+ | 0.0009 | 18.09 | 850 | 0.0351 | 17.3273 |
71
+ | 0.0006 | 19.15 | 900 | 0.0364 | 16.4788 |
72
+ | 0.0005 | 20.21 | 950 | 0.0368 | 15.4442 |
73
+ | 0.0004 | 21.28 | 1000 | 0.0368 | 16.2336 |
74
+ | 0.0004 | 22.34 | 1050 | 0.0375 | 14.1168 |
75
+ | 0.0004 | 23.4 | 1100 | 0.0375 | 14.4365 |
76
+ | 0.0004 | 24.47 | 1150 | 0.0373 | 12.3890 |
77
+ | 0.0004 | 25.53 | 1200 | 0.0379 | 8.7843 |
78
+ | 0.0004 | 26.6 | 1250 | 0.0382 | 9.2298 |
79
+ | 0.0003 | 27.66 | 1300 | 0.0383 | 8.8562 |
80
+ | 0.0003 | 28.72 | 1350 | 0.0384 | 9.5777 |
81
+ | 0.0003 | 29.79 | 1400 | 0.0383 | 8.6021 |
82
+ | 0.0003 | 30.85 | 1450 | 0.0387 | 7.9782 |
83
+ | 0.0003 | 31.91 | 1500 | 0.0387 | 7.7394 |
84
+ | 0.0003 | 32.98 | 1550 | 0.0388 | 7.6431 |
85
+ | 0.0003 | 34.04 | 1600 | 0.0389 | 6.9037 |
86
+ | 0.0003 | 35.11 | 1650 | 0.0391 | 6.8665 |
87
+ | 0.0003 | 36.17 | 1700 | 0.0392 | 6.0526 |
88
+ | 0.0003 | 37.23 | 1750 | 0.0394 | 5.6996 |
89
+ | 0.0003 | 38.3 | 1800 | 0.0393 | 6.1361 |
90
+ | 0.0003 | 39.36 | 1850 | 0.0394 | 5.9127 |
91
+ | 0.0003 | 40.43 | 1900 | 0.0394 | 5.6816 |
92
+ | 0.0003 | 41.49 | 1950 | 0.0394 | 5.3723 |
93
+ | 0.0003 | 42.55 | 2000 | 0.0395 | 4.8806 |
94
+ | 0.0002 | 43.62 | 2050 | 0.0395 | 6.9178 |
95
+ | 0.0002 | 44.68 | 2100 | 0.0395 | 6.2953 |
96
+ | 0.0002 | 45.74 | 2150 | 0.0395 | 6.1142 |
97
+ | 0.0002 | 46.81 | 2200 | 0.0396 | 6.0642 |
98
+ | 0.0002 | 47.87 | 2250 | 0.0396 | 6.0077 |
99
+ | 0.0002 | 48.94 | 2300 | 0.0396 | 6.0026 |
100
+ | 0.0002 | 50.0 | 2350 | 0.0396 | 6.0488 |
101
+
102
+
103
+ ### Framework versions
104
+
105
+ - Transformers 4.29.2
106
+ - Pytorch 2.0.1+cu117
107
+ - Datasets 2.12.0
108
+ - Tokenizers 0.13.3