Hugging Face's logo

kensvin
/
emotion_classification

Image Classification
Transformers
PyTorch
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Model card Files
xet
Community
1
kensvin commited on
Commit
e5ea0be
·
1 Parent(s): a401336

End of training

Browse files
Files changed (2) hide show
  1. README.md +27 -10
  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: 0.11875
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: 2.0823
36
- - Accuracy: 0.1187
37
 
38
  ## Model description
39
 
@@ -53,25 +53,42 @@ More information needed
53
 
54
  The following hyperparameters were used during training:
55
  - learning_rate: 0.0001
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
61
- - num_epochs: 3
62
 
63
  ### Training results
64
 
65
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
66
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
67
- | No log | 1.0 | 80 | 2.0822 | 0.1062 |
68
- | No log | 2.0 | 160 | 2.0839 | 0.1125 |
69
- | No log | 3.0 | 240 | 2.0825 | 0.1187 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
70
 
71
 
72
  ### Framework versions
73
 
74
- - Transformers 4.33.1
75
  - Pytorch 2.0.1+cu118
76
  - Datasets 2.14.5
77
  - Tokenizers 0.13.3
 
22
  metrics:
23
  - name: Accuracy
24
  type: accuracy
25
+ value: 0.60625
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: 1.2024
36
+ - Accuracy: 0.6062
37
 
38
  ## Model description
39
 
 
53
 
54
  The following hyperparameters were used during training:
55
  - learning_rate: 0.0001
56
+ - train_batch_size: 64
57
+ - eval_batch_size: 64
58
  - seed: 42
59
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
60
  - lr_scheduler_type: linear
61
+ - num_epochs: 20
62
 
63
  ### Training results
64
 
65
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
66
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
67
+ | No log | 1.0 | 10 | 1.3600 | 0.4938 |
68
+ | No log | 2.0 | 20 | 1.2908 | 0.4938 |
69
+ | No log | 3.0 | 30 | 1.2799 | 0.5 |
70
+ | No log | 4.0 | 40 | 1.2110 | 0.5312 |
71
+ | No log | 5.0 | 50 | 1.2178 | 0.5188 |
72
+ | No log | 6.0 | 60 | 1.2189 | 0.5188 |
73
+ | No log | 7.0 | 70 | 1.2566 | 0.5375 |
74
+ | No log | 8.0 | 80 | 1.1838 | 0.5687 |
75
+ | No log | 9.0 | 90 | 1.2730 | 0.55 |
76
+ | No log | 10.0 | 100 | 1.2329 | 0.575 |
77
+ | No log | 11.0 | 110 | 1.2224 | 0.5563 |
78
+ | No log | 12.0 | 120 | 1.2729 | 0.5563 |
79
+ | No log | 13.0 | 130 | 1.2678 | 0.5687 |
80
+ | No log | 14.0 | 140 | 1.2423 | 0.5687 |
81
+ | No log | 15.0 | 150 | 1.1704 | 0.6312 |
82
+ | No log | 16.0 | 160 | 1.2925 | 0.5625 |
83
+ | No log | 17.0 | 170 | 1.3557 | 0.5312 |
84
+ | No log | 18.0 | 180 | 1.2951 | 0.5687 |
85
+ | No log | 19.0 | 190 | 1.2594 | 0.5625 |
86
+ | No log | 20.0 | 200 | 1.2463 | 0.5687 |
87
 
88
 
89
  ### Framework versions
90
 
91
+ - Transformers 4.33.2
92
  - Pytorch 2.0.1+cu118
93
  - Datasets 2.14.5
94
  - Tokenizers 0.13.3
pytorch_model.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:b9507c5e908ba81a5c0fca06d0d8b83b34105ceeb37bd4bc434b63deb2967234
3
  size 343287149
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:aa032f8567fae289f16978c0d20cf3d3d42406313877d0dbacabdd6964607ad8
3
  size 343287149