Commit ·
b2b0bd6
1
Parent(s): 86f1486
update model card README.md
Browse files
README.md
CHANGED
|
@@ -1,7 +1,6 @@
|
|
| 1 |
---
|
| 2 |
license: apache-2.0
|
| 3 |
tags:
|
| 4 |
-
- image-classification
|
| 5 |
- generated_from_trainer
|
| 6 |
metrics:
|
| 7 |
- accuracy
|
|
@@ -15,10 +14,10 @@ should probably proofread and complete it, then remove this comment. -->
|
|
| 15 |
|
| 16 |
# vit-base-clothing-leafs-example-full-simple
|
| 17 |
|
| 18 |
-
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
|
| 19 |
It achieves the following results on the evaluation set:
|
| 20 |
-
- Loss: 1.
|
| 21 |
-
- Accuracy: 0.
|
| 22 |
|
| 23 |
## Model description
|
| 24 |
|
|
@@ -50,56 +49,56 @@ The following hyperparameters were used during training:
|
|
| 50 |
|
| 51 |
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
| 52 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
|
| 53 |
-
| 2.
|
| 54 |
-
| 2.
|
| 55 |
-
| 1.
|
| 56 |
-
| 1.
|
| 57 |
-
| 1.5127 | 0.69 | 5000 | 1.
|
| 58 |
-
| 1.
|
| 59 |
-
| 1.
|
| 60 |
-
| 1.
|
| 61 |
-
| 1.
|
| 62 |
-
| 1.
|
| 63 |
-
| 1.
|
| 64 |
-
| 1.
|
| 65 |
-
| 1.
|
| 66 |
-
| 1.
|
| 67 |
-
| 1.
|
| 68 |
-
| 1.
|
| 69 |
-
| 1.
|
| 70 |
-
| 1.
|
| 71 |
-
| 1.
|
| 72 |
-
| 1.
|
| 73 |
-
| 1.
|
| 74 |
-
| 1.
|
| 75 |
-
|
|
| 76 |
-
| 0.
|
| 77 |
-
|
|
| 78 |
-
|
|
| 79 |
-
|
|
| 80 |
-
| 0.
|
| 81 |
-
| 0.
|
| 82 |
-
| 0.
|
| 83 |
-
| 0.
|
| 84 |
-
| 0.
|
| 85 |
-
| 0.
|
| 86 |
-
| 0.
|
| 87 |
-
| 0.
|
| 88 |
-
| 0.
|
| 89 |
-
| 0.
|
| 90 |
-
| 0.
|
| 91 |
-
| 0.
|
| 92 |
-
| 0.
|
| 93 |
-
| 0.
|
| 94 |
-
| 0.
|
| 95 |
-
| 0.
|
| 96 |
-
| 0.
|
| 97 |
-
| 0.
|
| 98 |
-
| 0.
|
| 99 |
-
| 0.
|
| 100 |
-
| 0.
|
| 101 |
-
| 0.
|
| 102 |
-
| 0.
|
| 103 |
|
| 104 |
|
| 105 |
### Framework versions
|
|
|
|
| 1 |
---
|
| 2 |
license: apache-2.0
|
| 3 |
tags:
|
|
|
|
| 4 |
- generated_from_trainer
|
| 5 |
metrics:
|
| 6 |
- accuracy
|
|
|
|
| 14 |
|
| 15 |
# vit-base-clothing-leafs-example-full-simple
|
| 16 |
|
| 17 |
+
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 None dataset.
|
| 18 |
It achieves the following results on the evaluation set:
|
| 19 |
+
- Loss: 1.0692
|
| 20 |
+
- Accuracy: 0.6973
|
| 21 |
|
| 22 |
## Model description
|
| 23 |
|
|
|
|
| 49 |
|
| 50 |
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
| 51 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
|
| 52 |
+
| 2.8236 | 0.14 | 1000 | 2.3487 | 0.4711 |
|
| 53 |
+
| 2.1379 | 0.28 | 2000 | 1.9659 | 0.5445 |
|
| 54 |
+
| 1.8288 | 0.41 | 3000 | 1.7367 | 0.6094 |
|
| 55 |
+
| 1.6449 | 0.55 | 4000 | 1.5850 | 0.6326 |
|
| 56 |
+
| 1.5127 | 0.69 | 5000 | 1.4778 | 0.6462 |
|
| 57 |
+
| 1.4122 | 0.83 | 6000 | 1.3994 | 0.6565 |
|
| 58 |
+
| 1.3623 | 0.97 | 7000 | 1.3487 | 0.6620 |
|
| 59 |
+
| 1.293 | 1.11 | 8000 | 1.2994 | 0.6671 |
|
| 60 |
+
| 1.2382 | 1.24 | 9000 | 1.2702 | 0.6702 |
|
| 61 |
+
| 1.2186 | 1.38 | 10000 | 1.2421 | 0.6729 |
|
| 62 |
+
| 1.1912 | 1.52 | 11000 | 1.2220 | 0.6747 |
|
| 63 |
+
| 1.1798 | 1.66 | 12000 | 1.1974 | 0.6797 |
|
| 64 |
+
| 1.1605 | 1.8 | 13000 | 1.1833 | 0.6827 |
|
| 65 |
+
| 1.1454 | 1.94 | 14000 | 1.1689 | 0.6838 |
|
| 66 |
+
| 1.1076 | 2.07 | 15000 | 1.1666 | 0.6821 |
|
| 67 |
+
| 1.0882 | 2.21 | 16000 | 1.1562 | 0.6836 |
|
| 68 |
+
| 1.0832 | 2.35 | 17000 | 1.1426 | 0.6874 |
|
| 69 |
+
| 1.0698 | 2.49 | 18000 | 1.1318 | 0.6873 |
|
| 70 |
+
| 1.0752 | 2.63 | 19000 | 1.1396 | 0.6843 |
|
| 71 |
+
| 1.0659 | 2.77 | 20000 | 1.1167 | 0.6903 |
|
| 72 |
+
| 1.0561 | 2.9 | 21000 | 1.1178 | 0.6880 |
|
| 73 |
+
| 1.0328 | 3.04 | 22000 | 1.1114 | 0.6906 |
|
| 74 |
+
| 1.0299 | 3.18 | 23000 | 1.1057 | 0.6917 |
|
| 75 |
+
| 0.9961 | 3.32 | 24000 | 1.1056 | 0.6913 |
|
| 76 |
+
| 1.0128 | 3.46 | 25000 | 1.0973 | 0.6938 |
|
| 77 |
+
| 1.0118 | 3.6 | 26000 | 1.0931 | 0.6942 |
|
| 78 |
+
| 1.0045 | 3.73 | 27000 | 1.0898 | 0.6937 |
|
| 79 |
+
| 0.9923 | 3.87 | 28000 | 1.0859 | 0.6959 |
|
| 80 |
+
| 0.9988 | 4.01 | 29000 | 1.0852 | 0.6944 |
|
| 81 |
+
| 0.9773 | 4.15 | 30000 | 1.0893 | 0.6930 |
|
| 82 |
+
| 0.9577 | 4.29 | 31000 | 1.0807 | 0.6968 |
|
| 83 |
+
| 0.9748 | 4.43 | 32000 | 1.0789 | 0.6957 |
|
| 84 |
+
| 0.9777 | 4.56 | 33000 | 1.0864 | 0.6924 |
|
| 85 |
+
| 0.9536 | 4.7 | 34000 | 1.0813 | 0.6949 |
|
| 86 |
+
| 0.9507 | 4.84 | 35000 | 1.0795 | 0.6950 |
|
| 87 |
+
| 0.9627 | 4.98 | 36000 | 1.0755 | 0.6955 |
|
| 88 |
+
| 0.9399 | 5.12 | 37000 | 1.0770 | 0.6961 |
|
| 89 |
+
| 0.9357 | 5.26 | 38000 | 1.0759 | 0.6961 |
|
| 90 |
+
| 0.943 | 5.39 | 39000 | 1.0721 | 0.6966 |
|
| 91 |
+
| 0.9244 | 5.53 | 40000 | 1.0704 | 0.6969 |
|
| 92 |
+
| 0.9231 | 5.67 | 41000 | 1.0727 | 0.6960 |
|
| 93 |
+
| 0.9294 | 5.81 | 42000 | 1.0716 | 0.6970 |
|
| 94 |
+
| 0.9416 | 5.95 | 43000 | 1.0694 | 0.6981 |
|
| 95 |
+
| 0.9248 | 6.08 | 44000 | 1.0678 | 0.6991 |
|
| 96 |
+
| 0.9137 | 6.22 | 45000 | 1.0701 | 0.6976 |
|
| 97 |
+
| 0.91 | 6.36 | 46000 | 1.0689 | 0.6972 |
|
| 98 |
+
| 0.9256 | 6.5 | 47000 | 1.0671 | 0.6975 |
|
| 99 |
+
| 0.9085 | 6.64 | 48000 | 1.0678 | 0.6985 |
|
| 100 |
+
| 0.9169 | 6.78 | 49000 | 1.0690 | 0.6984 |
|
| 101 |
+
| 0.9087 | 6.91 | 50000 | 1.0692 | 0.6973 |
|
| 102 |
|
| 103 |
|
| 104 |
### Framework versions
|