Hugging Face's logo

gchabcou
/
my_awesome_food_model

Image Classification
Transformers
PyTorch
vit
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
gchabcou commited on
Commit
83ad28a
•
1 Parent(s): 46a035b

End of training

Browse files
Files changed (2) hide show
  1. README.md +15 -8
  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: 0.885
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 food101 dataset.
34
  It achieves the following results on the evaluation set:
35
- - Loss: 1.6290
36
- - Accuracy: 0.885
37
 
38
  ## Model description
39
 
@@ -52,7 +52,7 @@ More information needed
52
  ### Training hyperparameters
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
@@ -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
- | 2.7273 | 0.99 | 62 | 2.5332 | 0.832 |
71
- | 1.8643 | 2.0 | 125 | 1.7844 | 0.89 |
72
- | 1.6056 | 2.98 | 186 | 1.6290 | 0.885 |
 
 
 
 
 
 
 
73
 
74
 
75
  ### Framework versions
 
22
  metrics:
23
  - name: Accuracy
24
  type: accuracy
25
+ value: 0.9
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 food101 dataset.
34
  It achieves the following results on the evaluation set:
35
+ - Loss: 0.8834
36
+ - Accuracy: 0.9
37
 
38
  ## Model description
39
 
 
52
  ### Training hyperparameters
53
 
54
  The following hyperparameters were used during training:
55
+ - learning_rate: 3e-05
56
  - train_batch_size: 16
57
  - eval_batch_size: 16
58
  - seed: 42
 
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
+ | 3.6073 | 0.99 | 62 | 3.3725 | 0.818 |
71
+ | 2.2956 | 2.0 | 125 | 2.1579 | 0.854 |
72
+ | 1.7042 | 2.99 | 187 | 1.6201 | 0.887 |
73
+ | 1.3278 | 4.0 | 250 | 1.3513 | 0.89 |
74
+ | 1.1314 | 4.99 | 312 | 1.1549 | 0.908 |
75
+ | 1.007 | 6.0 | 375 | 1.0737 | 0.889 |
76
+ | 0.905 | 6.99 | 437 | 0.9600 | 0.906 |
77
+ | 0.8227 | 8.0 | 500 | 0.9113 | 0.912 |
78
+ | 0.7948 | 8.99 | 562 | 0.8908 | 0.909 |
79
+ | 0.7598 | 9.92 | 620 | 0.8834 | 0.9 |
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:f700d1b728388f3396bca99c64ba30faccc7a5e081d2f14cbfea380ada06ac68
3
  size 343573229
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5050821baabcce7fc7cf4d5ad6547815ae75ec1b833d935c69e96ad4046e5116
3
  size 343573229