Hugging Face's logo

BTX24
/
beit-base-patch16-224-pt22k-ft22k-finetuned-stroke-binary

Image Classification
Transformers
TensorBoard
Safetensors
beit
Generated from Trainer
Model card Files Metrics Community
BTX24 commited on
Commit
94d304f
·
verified ·
1 Parent(s): c6f99f6

Model save

Browse files
Files changed (2) hide show
  1. README.md +108 -0
  2. model.safetensors +1 -1
README.md ADDED
@@ -0,0 +1,108 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: transformers
3
+ license: apache-2.0
4
+ base_model: microsoft/beit-base-patch16-224-pt22k-ft22k
5
+ tags:
6
+ - generated_from_trainer
7
+ metrics:
8
+ - accuracy
9
+ - f1
10
+ - precision
11
+ - recall
12
+ model-index:
13
+ - name: beit-base-patch16-224-pt22k-ft22k-finetuned-stroke-binary
14
+ results: []
15
+ ---
16
+
17
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
18
+ should probably proofread and complete it, then remove this comment. -->
19
+
20
+ # beit-base-patch16-224-pt22k-ft22k-finetuned-stroke-binary
21
+
22
+ This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on an unknown dataset.
23
+ It achieves the following results on the evaluation set:
24
+ - Loss: 0.2066
25
+ - Accuracy: 0.9181
26
+ - F1: 0.9170
27
+ - Precision: 0.9201
28
+ - Recall: 0.9181
29
+
30
+ ## Model description
31
+
32
+ More information needed
33
+
34
+ ## Intended uses & limitations
35
+
36
+ More information needed
37
+
38
+ ## Training and evaluation data
39
+
40
+ More information needed
41
+
42
+ ## Training procedure
43
+
44
+ ### Training hyperparameters
45
+
46
+ The following hyperparameters were used during training:
47
+ - learning_rate: 2e-05
48
+ - train_batch_size: 16
49
+ - eval_batch_size: 8
50
+ - seed: 42
51
+ - gradient_accumulation_steps: 4
52
+ - total_train_batch_size: 64
53
+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
54
+ - lr_scheduler_type: cosine_with_restarts
55
+ - lr_scheduler_warmup_ratio: 0.1
56
+ - num_epochs: 48
57
+ - mixed_precision_training: Native AMP
58
+
59
+ ### Training results
60
+
61
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
62
+ |:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
63
+ | 0.7256 | 1.2477 | 100 | 0.6913 | 0.5685 | 0.4823 | 0.4731 | 0.5685 |
64
+ | 0.6695 | 2.4954 | 200 | 0.6480 | 0.6210 | 0.5164 | 0.5987 | 0.6210 |
65
+ | 0.5963 | 3.7430 | 300 | 0.5882 | 0.6725 | 0.6118 | 0.6993 | 0.6725 |
66
+ | 0.518 | 4.9907 | 400 | 0.4990 | 0.7481 | 0.7167 | 0.7891 | 0.7481 |
67
+ | 0.4325 | 6.2477 | 500 | 0.4090 | 0.8073 | 0.7957 | 0.8232 | 0.8073 |
68
+ | 0.3848 | 7.4954 | 600 | 0.3703 | 0.8340 | 0.8257 | 0.8482 | 0.8340 |
69
+ | 0.3532 | 8.7430 | 700 | 0.3958 | 0.8313 | 0.8201 | 0.8564 | 0.8313 |
70
+ | 0.3297 | 9.9907 | 800 | 0.3257 | 0.8611 | 0.8558 | 0.8718 | 0.8611 |
71
+ | 0.3281 | 11.2477 | 900 | 0.3169 | 0.8666 | 0.8612 | 0.8791 | 0.8666 |
72
+ | 0.2938 | 12.4954 | 1000 | 0.2814 | 0.8865 | 0.8841 | 0.8900 | 0.8865 |
73
+ | 0.2866 | 13.7430 | 1100 | 0.2828 | 0.8869 | 0.8837 | 0.8943 | 0.8869 |
74
+ | 0.2884 | 14.9907 | 1200 | 0.2929 | 0.8847 | 0.8810 | 0.8936 | 0.8847 |
75
+ | 0.2808 | 16.2477 | 1300 | 0.2458 | 0.9014 | 0.8999 | 0.9034 | 0.9014 |
76
+ | 0.258 | 17.4954 | 1400 | 0.2351 | 0.9091 | 0.9080 | 0.9102 | 0.9091 |
77
+ | 0.2744 | 18.7430 | 1500 | 0.2516 | 0.9014 | 0.8994 | 0.9057 | 0.9014 |
78
+ | 0.261 | 19.9907 | 1600 | 0.2453 | 0.9068 | 0.9050 | 0.9107 | 0.9068 |
79
+ | 0.2519 | 21.2477 | 1700 | 0.2564 | 0.8987 | 0.8961 | 0.9051 | 0.8987 |
80
+ | 0.2595 | 22.4954 | 1800 | 0.2318 | 0.9095 | 0.9079 | 0.9129 | 0.9095 |
81
+ | 0.2548 | 23.7430 | 1900 | 0.2196 | 0.9136 | 0.9128 | 0.9142 | 0.9136 |
82
+ | 0.2327 | 24.9907 | 2000 | 0.2376 | 0.9068 | 0.9050 | 0.9110 | 0.9068 |
83
+ | 0.2563 | 26.2477 | 2100 | 0.2421 | 0.9028 | 0.9005 | 0.9083 | 0.9028 |
84
+ | 0.2348 | 27.4954 | 2200 | 0.2213 | 0.9109 | 0.9095 | 0.9132 | 0.9109 |
85
+ | 0.2427 | 28.7430 | 2300 | 0.2308 | 0.9077 | 0.9060 | 0.9116 | 0.9077 |
86
+ | 0.2166 | 29.9907 | 2400 | 0.2152 | 0.9141 | 0.9128 | 0.9165 | 0.9141 |
87
+ | 0.2345 | 31.2477 | 2500 | 0.2283 | 0.9068 | 0.9049 | 0.9114 | 0.9068 |
88
+ | 0.2355 | 32.4954 | 2600 | 0.2173 | 0.9118 | 0.9103 | 0.9149 | 0.9118 |
89
+ | 0.2291 | 33.7430 | 2700 | 0.2149 | 0.9127 | 0.9113 | 0.9155 | 0.9127 |
90
+ | 0.2319 | 34.9907 | 2800 | 0.2123 | 0.9141 | 0.9127 | 0.9167 | 0.9141 |
91
+ | 0.222 | 36.2477 | 2900 | 0.2053 | 0.9181 | 0.9171 | 0.9197 | 0.9181 |
92
+ | 0.2235 | 37.4954 | 3000 | 0.2121 | 0.9141 | 0.9127 | 0.9166 | 0.9141 |
93
+ | 0.2221 | 38.7430 | 3100 | 0.2013 | 0.9195 | 0.9188 | 0.9200 | 0.9195 |
94
+ | 0.2262 | 39.9907 | 3200 | 0.2029 | 0.9222 | 0.9214 | 0.9234 | 0.9222 |
95
+ | 0.2171 | 41.2477 | 3300 | 0.2075 | 0.9181 | 0.9170 | 0.9202 | 0.9181 |
96
+ | 0.2268 | 42.4954 | 3400 | 0.2045 | 0.9190 | 0.9180 | 0.9208 | 0.9190 |
97
+ | 0.2222 | 43.7430 | 3500 | 0.2050 | 0.9204 | 0.9194 | 0.9222 | 0.9204 |
98
+ | 0.2169 | 44.9907 | 3600 | 0.2070 | 0.9177 | 0.9165 | 0.9197 | 0.9177 |
99
+ | 0.2245 | 46.2477 | 3700 | 0.2064 | 0.9181 | 0.9170 | 0.9201 | 0.9181 |
100
+ | 0.2148 | 47.4954 | 3800 | 0.2066 | 0.9181 | 0.9170 | 0.9201 | 0.9181 |
101
+
102
+
103
+ ### Framework versions
104
+
105
+ - Transformers 4.48.3
106
+ - Pytorch 2.6.0+cu124
107
+ - Datasets 3.4.0
108
+ - Tokenizers 0.21.0
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:3c66cc7f01384f3f9c33e4390166eefaa4149119a8e9f57b76cd335484a8d990
3
  size 490550160
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:20c0c7575856e0f3765b64860ebe05b00a982d151decbb6ff1a3accddb0ccf74
3
  size 490550160