Hugging Face's logo

fahmindra
/
emotion_classification

Image Classification
Transformers
PyTorch
vit
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
fahmindra commited on
Commit
7451c50
•
1 Parent(s): e5d1fc1

End of training

Browse files
Files changed (2) hide show
  1. README.md +14 -7
  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: 0.25
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: 1.9278
36
- - Accuracy: 0.25
37
 
38
  ## Model description
39
 
@@ -61,15 +61,22 @@ 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
- | 2.0639 | 1.0 | 10 | 2.0407 | 0.225 |
71
- | 1.9692 | 2.0 | 20 | 1.9676 | 0.2562 |
72
- | 1.8947 | 3.0 | 30 | 1.9273 | 0.275 |
 
 
 
 
 
 
 
73
 
74
 
75
  ### Framework versions
 
22
  metrics:
23
  - name: Accuracy
24
  type: accuracy
25
+ value: 0.46875
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: 1.4050
36
+ - Accuracy: 0.4688
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: 0.1
64
+ - num_epochs: 10
65
 
66
  ### Training results
67
 
68
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
69
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
70
+ | 1.8187 | 1.0 | 10 | 1.8406 | 0.3063 |
71
+ | 1.6795 | 2.0 | 20 | 1.6701 | 0.3688 |
72
+ | 1.5506 | 3.0 | 30 | 1.5578 | 0.45 |
73
+ | 1.4417 | 4.0 | 40 | 1.5077 | 0.4875 |
74
+ | 1.3707 | 5.0 | 50 | 1.4297 | 0.5062 |
75
+ | 1.3167 | 6.0 | 60 | 1.4157 | 0.4938 |
76
+ | 1.267 | 7.0 | 70 | 1.3779 | 0.525 |
77
+ | 1.2197 | 8.0 | 80 | 1.3784 | 0.5 |
78
+ | 1.191 | 9.0 | 90 | 1.3701 | 0.5188 |
79
+ | 1.1649 | 10.0 | 100 | 1.3611 | 0.4938 |
80
 
81
 
82
  ### Framework versions
pytorch_model.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:3868b5c3430e458ae8915e24549181d9797d2b5cc274336b83c61c967a4d6e5a
3
  size 343287149
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:2077d28e4cd3493972a95ca8c1af9625fa0ed889330c24d348c00752922a1d15
3
  size 343287149