Hugging Face's logo

rafelsiregar
/
image_classification

Image Classification
Transformers
PyTorch
vit
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
1
rafelsiregar commited on
Commit
34b5d9b
•
1 Parent(s): f024f00

End of training

Browse files
Files changed (2) hide show
  1. README.md +15 -15
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
22
  metrics:
23
  - name: Accuracy
24
  type: accuracy
25
- value: 0.575
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: 1.2512
36
- - Accuracy: 0.575
37
 
38
  ## Model description
39
 
@@ -53,8 +53,8 @@ More information needed
53
 
54
  The following hyperparameters were used during training:
55
  - learning_rate: 5e-05
56
- - train_batch_size: 16
57
- - eval_batch_size: 16
58
  - seed: 42
59
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
60
  - lr_scheduler_type: linear
@@ -64,16 +64,16 @@ The following hyperparameters were used during training:
64
 
65
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
66
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
67
- | No log | 1.0 | 40 | 1.7667 | 0.3187 |
68
- | No log | 2.0 | 80 | 1.5919 | 0.425 |
69
- | No log | 3.0 | 120 | 1.4461 | 0.4062 |
70
- | No log | 4.0 | 160 | 1.3533 | 0.4938 |
71
- | No log | 5.0 | 200 | 1.3375 | 0.5188 |
72
- | No log | 6.0 | 240 | 1.2784 | 0.5125 |
73
- | No log | 7.0 | 280 | 1.2552 | 0.5375 |
74
- | No log | 8.0 | 320 | 1.2863 | 0.5 |
75
- | No log | 9.0 | 360 | 1.2583 | 0.5375 |
76
- | No log | 10.0 | 400 | 1.2408 | 0.5875 |
77
 
78
 
79
  ### Framework versions
 
22
  metrics:
23
  - name: Accuracy
24
  type: accuracy
25
+ value: 0.5375
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: 1.3341
36
+ - Accuracy: 0.5375
37
 
38
  ## Model description
39
 
 
53
 
54
  The following hyperparameters were used during training:
55
  - learning_rate: 5e-05
56
+ - train_batch_size: 8
57
+ - eval_batch_size: 8
58
  - seed: 42
59
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
60
  - lr_scheduler_type: linear
 
64
 
65
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
66
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
67
+ | No log | 1.0 | 80 | 1.3975 | 0.4062 |
68
+ | No log | 2.0 | 160 | 1.3917 | 0.4875 |
69
+ | No log | 3.0 | 240 | 1.2964 | 0.5 |
70
+ | No log | 4.0 | 320 | 1.2587 | 0.5312 |
71
+ | No log | 5.0 | 400 | 1.2705 | 0.5125 |
72
+ | No log | 6.0 | 480 | 1.2557 | 0.55 |
73
+ | 0.7469 | 7.0 | 560 | 1.3400 | 0.525 |
74
+ | 0.7469 | 8.0 | 640 | 1.3586 | 0.5687 |
75
+ | 0.7469 | 9.0 | 720 | 1.3317 | 0.5563 |
76
+ | 0.7469 | 10.0 | 800 | 1.2965 | 0.5687 |
77
 
78
 
79
  ### Framework versions
pytorch_model.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:a4d930a204b510b4f773f39c869213b347bbe1d4c1d6a15f762fc873d4348d09
3
  size 343287149
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0b0953da18b64ee1c95f1e54df0fe448bfd9e63c53ba96c81826c28c084cab06
3
  size 343287149