Hugging Face's logo

ongkn
/
attraction-classifier

Image Classification
Transformers
Safetensors
vit
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
5
ongkn commited on
Commit
a638f69
•
1 Parent(s): cfbd23b

End of training

Browse files
Files changed (2) hide show
  1. README.md +11 -10
  2. model.safetensors +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
22
  metrics:
23
  - name: Accuracy
24
  type: accuracy
25
- value: 0.8050847457627118
26
  ---
27
 
28
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +32,8 @@ 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-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
34
  It achieves the following results on the evaluation set:
35
- - Loss: 0.4771
36
- - Accuracy: 0.8051
37
 
38
  ## Model description
39
 
@@ -61,19 +61,20 @@ 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: 0.05
64
- - num_epochs: 20
65
  - mixed_precision_training: Native AMP
66
 
67
  ### Training results
68
 
69
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
70
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
71
- | 0.4945 | 3.01 | 50 | 0.4621 | 0.7669 |
72
- | 0.3739 | 6.02 | 100 | 0.4412 | 0.8072 |
73
- | 0.3005 | 9.02 | 150 | 0.4343 | 0.8008 |
74
- | 0.2583 | 12.03 | 200 | 0.4364 | 0.8157 |
75
- | 0.2166 | 15.04 | 250 | 0.4975 | 0.8093 |
76
- | 0.1874 | 18.05 | 300 | 0.4771 | 0.8051 |
 
77
 
78
 
79
  ### Framework versions
 
22
  metrics:
23
  - name: Accuracy
24
  type: accuracy
25
+ value: 0.809322033898305
26
  ---
27
 
28
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
32
 
33
  This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
34
  It achieves the following results on the evaluation set:
35
+ - Loss: 0.5064
36
+ - Accuracy: 0.8093
37
 
38
  ## Model description
39
 
 
61
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
62
  - lr_scheduler_type: linear
63
  - lr_scheduler_warmup_ratio: 0.05
64
+ - num_epochs: 25
65
  - mixed_precision_training: Native AMP
66
 
67
  ### Training results
68
 
69
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
70
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
71
+ | 0.4908 | 3.01 | 50 | 0.5141 | 0.7797 |
72
+ | 0.3766 | 6.02 | 100 | 0.4485 | 0.7839 |
73
+ | 0.3121 | 9.02 | 150 | 0.4550 | 0.7903 |
74
+ | 0.2569 | 12.03 | 200 | 0.3977 | 0.8305 |
75
+ | 0.215 | 15.04 | 250 | 0.4732 | 0.7987 |
76
+ | 0.186 | 18.05 | 300 | 0.4804 | 0.8072 |
77
+ | 0.1568 | 21.05 | 350 | 0.5064 | 0.8093 |
78
 
79
 
80
  ### Framework versions
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:d0653577e10187bb7db9e5fdf76bddf703ee5472ace9d4b1a4afbaf89456e352
3
  size 343223968
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f71be68b33f08a5dbd89e23375c86fe2c0ba53e4c39f5ed6f217a9737c5c56fc
3
  size 343223968