Hugging Face's logo

HorcruxNo13
/
vit-base-patch16-224

Image Classification
Transformers
PyTorch
vit
Generated from Trainer
Eval Results (legacy)
Model card Files
xet
 Community
1
HorcruxNo13 commited on
Commit
86c5540
·
1 Parent(s): ac178d6

Model save

Browse files
Files changed (2) hide show
  1. README.md +29 -11
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -7,6 +7,8 @@ datasets:
7
  - imagefolder
8
  metrics:
9
  - accuracy
 
 
10
  model-index:
11
  - name: vit-base-patch16-224
12
  results:
@@ -22,7 +24,13 @@ model-index:
22
  metrics:
23
  - name: Accuracy
24
  type: accuracy
25
- value: 0.7433333333333333
 
 
 
 
 
 
26
  ---
27
 
28
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +40,11 @@ should probably proofread and complete it, then remove this comment. -->
32
 
33
  This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
34
  It achieves the following results on the evaluation set:
35
- - Loss: 0.6275
36
- - Accuracy: 0.7433
 
 
 
37
 
38
  ## Model description
39
 
@@ -61,20 +72,27 @@ The following hyperparameters were used during training:
61
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
62
  - lr_scheduler_type: linear
63
  - lr_scheduler_warmup_ratio: 0.1
64
- - num_epochs: 3
65
 
66
  ### Training results
67
 
68
- | Training Loss | Epoch | Step | Validation Loss | Accuracy |
69
- |:-------------:|:-----:|:----:|:---------------:|:--------:|
70
- | No log | 1.0 | 8 | 2.6943 | 0.6833 |
71
- | 5.3331 | 2.0 | 16 | 0.6308 | 0.7417 |
72
- | 0.6715 | 3.0 | 24 | 0.6677 | 0.6458 |
 
 
 
 
 
 
 
73
 
74
 
75
  ### Framework versions
76
 
77
- - Transformers 4.32.1
78
  - Pytorch 2.0.1+cu118
79
- - Datasets 2.14.4
80
  - Tokenizers 0.13.3
 
7
  - imagefolder
8
  metrics:
9
  - accuracy
10
+ - precision
11
+ - recall
12
  model-index:
13
  - name: vit-base-patch16-224
14
  results:
 
24
  metrics:
25
  - name: Accuracy
26
  type: accuracy
27
+ value: 0.8033333333333333
28
+ - name: Precision
29
+ type: precision
30
+ value: 0.7988653846153846
31
+ - name: Recall
32
+ type: recall
33
+ value: 0.8033333333333333
34
  ---
35
 
36
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
40
 
41
  This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
42
  It achieves the following results on the evaluation set:
43
+ - Loss: 0.4775
44
+ - Accuracy: 0.8033
45
+ - Precision: 0.7989
46
+ - Recall: 0.8033
47
+ - F1 Score: 0.7784
48
 
49
  ## Model description
50
 
 
72
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
73
  - lr_scheduler_type: linear
74
  - lr_scheduler_warmup_ratio: 0.1
75
+ - num_epochs: 10
76
 
77
  ### Training results
78
 
79
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 Score |
80
+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|
81
+ | No log | 1.0 | 8 | 0.5941 | 0.7333 | 0.5378 | 0.7333 | 0.6205 |
82
+ | 0.6385 | 2.0 | 16 | 0.5391 | 0.775 | 0.7830 | 0.775 | 0.7210 |
83
+ | 0.546 | 3.0 | 24 | 0.5417 | 0.775 | 0.7658 | 0.775 | 0.7321 |
84
+ | 0.481 | 4.0 | 32 | 0.5486 | 0.7833 | 0.8030 | 0.7833 | 0.7313 |
85
+ | 0.3841 | 5.0 | 40 | 0.5420 | 0.7875 | 0.7825 | 0.7875 | 0.7515 |
86
+ | 0.3841 | 6.0 | 48 | 0.5246 | 0.8292 | 0.8358 | 0.8292 | 0.8068 |
87
+ | 0.2565 | 7.0 | 56 | 0.5763 | 0.8083 | 0.8070 | 0.8083 | 0.7821 |
88
+ | 0.1605 | 8.0 | 64 | 0.5433 | 0.825 | 0.8180 | 0.825 | 0.8120 |
89
+ | 0.0824 | 9.0 | 72 | 0.6010 | 0.8125 | 0.8027 | 0.8125 | 0.7994 |
90
+ | 0.0489 | 10.0 | 80 | 0.6063 | 0.8125 | 0.8032 | 0.8125 | 0.7977 |
91
 
92
 
93
  ### Framework versions
94
 
95
+ - Transformers 4.33.2
96
  - Pytorch 2.0.1+cu118
97
+ - Datasets 2.14.5
98
  - Tokenizers 0.13.3
pytorch_model.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:895c7bf9450341593a92b17af82be2d85b5eff94462cc825774dd4bacb907298
3
  size 343268717
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a10521d07dc61f533d0d5a9bec8d2c44bba11613456d4bab737402f7e4b9eda4
3
  size 343268717