Commit ·
d9ffeaf
1
Parent(s): 73a98af
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:
|
| 21 |
-
- Accuracy: 0.
|
| 22 |
|
| 23 |
## Model description
|
| 24 |
|
|
@@ -37,7 +36,7 @@ More information needed
|
|
| 37 |
### Training hyperparameters
|
| 38 |
|
| 39 |
The following hyperparameters were used during training:
|
| 40 |
-
- learning_rate:
|
| 41 |
- train_batch_size: 32
|
| 42 |
- eval_batch_size: 8
|
| 43 |
- seed: 42
|
|
@@ -50,25 +49,25 @@ The following hyperparameters were used during training:
|
|
| 50 |
|
| 51 |
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
| 52 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
|
| 53 |
-
|
|
| 54 |
-
| 1.
|
| 55 |
-
| 1.
|
| 56 |
-
| 1.
|
| 57 |
-
| 1.
|
| 58 |
-
| 1.
|
| 59 |
-
| 1.
|
| 60 |
-
| 0.
|
| 61 |
-
| 0.
|
| 62 |
-
| 0.
|
| 63 |
-
| 0.
|
| 64 |
-
| 0.
|
| 65 |
-
| 0.
|
| 66 |
-
| 0.
|
| 67 |
-
| 0.
|
| 68 |
-
| 0.
|
| 69 |
-
| 0.
|
| 70 |
-
| 0.
|
| 71 |
-
| 0.
|
| 72 |
|
| 73 |
|
| 74 |
### 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: 1.0113
|
| 20 |
+
- Accuracy: 0.7159
|
| 21 |
|
| 22 |
## Model description
|
| 23 |
|
|
|
|
| 36 |
### Training hyperparameters
|
| 37 |
|
| 38 |
The following hyperparameters were used during training:
|
| 39 |
+
- learning_rate: 2e-05
|
| 40 |
- train_batch_size: 32
|
| 41 |
- eval_batch_size: 8
|
| 42 |
- seed: 42
|
|
|
|
| 49 |
|
| 50 |
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
| 51 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
|
| 52 |
+
| 2.1091 | 0.14 | 1000 | 1.5708 | 0.6353 |
|
| 53 |
+
| 1.4147 | 0.28 | 2000 | 1.3138 | 0.6585 |
|
| 54 |
+
| 1.2355 | 0.41 | 3000 | 1.1873 | 0.6820 |
|
| 55 |
+
| 1.1718 | 0.55 | 4000 | 1.1535 | 0.6837 |
|
| 56 |
+
| 1.1154 | 0.69 | 5000 | 1.0924 | 0.6977 |
|
| 57 |
+
| 1.0914 | 0.83 | 6000 | 1.0666 | 0.7002 |
|
| 58 |
+
| 1.052 | 0.97 | 7000 | 1.0516 | 0.7029 |
|
| 59 |
+
| 0.9649 | 1.11 | 8000 | 1.0426 | 0.7033 |
|
| 60 |
+
| 0.9281 | 1.24 | 9000 | 1.0278 | 0.7113 |
|
| 61 |
+
| 0.9131 | 1.38 | 10000 | 1.0219 | 0.7106 |
|
| 62 |
+
| 0.9105 | 1.52 | 11000 | 1.0093 | 0.7136 |
|
| 63 |
+
| 0.9139 | 1.66 | 12000 | 1.0021 | 0.7157 |
|
| 64 |
+
| 0.901 | 1.8 | 13000 | 1.0019 | 0.7148 |
|
| 65 |
+
| 0.8916 | 1.94 | 14000 | 0.9940 | 0.7164 |
|
| 66 |
+
| 0.8142 | 2.07 | 15000 | 1.0117 | 0.7176 |
|
| 67 |
+
| 0.7494 | 2.21 | 16000 | 1.0149 | 0.7156 |
|
| 68 |
+
| 0.7489 | 2.35 | 17000 | 1.0146 | 0.7149 |
|
| 69 |
+
| 0.7392 | 2.49 | 18000 | 1.0147 | 0.7146 |
|
| 70 |
+
| 0.7447 | 2.63 | 19000 | 1.0113 | 0.7159 |
|
| 71 |
|
| 72 |
|
| 73 |
### Framework versions
|