End of training

README.md

@@ -4,7 +4,7 @@ base_model: google/vit-base-patch16-224-in21k
 tags:
 - generated_from_trainer
 datasets:
-- imagefolder
+- beans
 metrics:
 - accuracy
 model-index:
@@ -14,15 +14,15 @@ model-index:
       name: Image Classification
       type: image-classification
     dataset:
-      name: imagefolder
-      type: imagefolder
+      name: beans
+      type: beans
       config: default
       split: train
       args: default
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.5375
+      value: 0.9420289855072463
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -30,10 +30,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # image_classification
 
-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.
+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 beans dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.3106
-- Accuracy: 0.5375
+- Loss: 0.3869
+- Accuracy: 0.9420
 
 ## Model description
 
@@ -61,42 +61,15 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 30
+- num_epochs: 3
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.367         | 1.0   | 10   | 1.5172          | 0.4437   |
-| 1.3337        | 2.0   | 20   | 1.5171          | 0.3875   |
-| 1.2582        | 3.0   | 30   | 1.4672          | 0.4813   |
-| 1.1813        | 4.0   | 40   | 1.3955          | 0.5      |
-| 1.1025        | 5.0   | 50   | 1.3617          | 0.5125   |
-| 1.0447        | 6.0   | 60   | 1.3491          | 0.5125   |
-| 0.9362        | 7.0   | 70   | 1.3079          | 0.5437   |
-| 0.8991        | 8.0   | 80   | 1.3291          | 0.4938   |
-| 0.8562        | 9.0   | 90   | 1.3445          | 0.4625   |
-| 0.7978        | 10.0  | 100  | 1.3168          | 0.5      |
-| 0.7183        | 11.0  | 110  | 1.2865          | 0.4875   |
-| 0.6941        | 12.0  | 120  | 1.2461          | 0.55     |
-| 0.6455        | 13.0  | 130  | 1.2330          | 0.6062   |
-| 0.6164        | 14.0  | 140  | 1.3818          | 0.4813   |
-| 0.5807        | 15.0  | 150  | 1.3250          | 0.5062   |
-| 0.5643        | 16.0  | 160  | 1.3206          | 0.5188   |
-| 0.5061        | 17.0  | 170  | 1.2957          | 0.5125   |
-| 0.478         | 18.0  | 180  | 1.3782          | 0.4625   |
-| 0.4615        | 19.0  | 190  | 1.2772          | 0.5563   |
-| 0.4514        | 20.0  | 200  | 1.2278          | 0.5375   |
-| 0.4196        | 21.0  | 210  | 1.2861          | 0.5188   |
-| 0.4589        | 22.0  | 220  | 1.2778          | 0.5375   |
-| 0.4303        | 23.0  | 230  | 1.2534          | 0.5687   |
-| 0.4023        | 24.0  | 240  | 1.3352          | 0.5312   |
-| 0.3967        | 25.0  | 250  | 1.3381          | 0.5375   |
-| 0.3725        | 26.0  | 260  | 1.2320          | 0.5625   |
-| 0.3757        | 27.0  | 270  | 1.2201          | 0.5625   |
-| 0.3913        | 28.0  | 280  | 1.2204          | 0.5563   |
-| 0.3982        | 29.0  | 290  | 1.2564          | 0.5437   |
-| 0.3765        | 30.0  | 300  | 1.3752          | 0.5      |
+| 0.9716        | 1.0   | 13   | 0.6693          | 0.9275   |
+| 0.6674        | 2.0   | 26   | 0.4463          | 0.9565   |
+| 0.5056        | 3.0   | 39   | 0.3736          | 0.9662   |
 
 
 ### Framework versions