End of training

README.md

@@ -4,7 +4,7 @@ base_model: google/vit-base-patch16-224-in21k
 tags:
 - generated_from_trainer
 datasets:
-- beans
+- imagefolder
 metrics:
 - accuracy
 model-index:
@@ -14,15 +14,15 @@ model-index:
       name: Image Classification
       type: image-classification
     dataset:
-      name: beans
-      type: beans
+      name: imagefolder
+      type: imagefolder
       config: default
       split: train
       args: default
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9420289855072463
+      value: 0.53125
 ---
 
 <!-- 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 beans 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 imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.3869
-- Accuracy: 0.9420
+- Loss: 1.2727
+- Accuracy: 0.5312
 
 ## Model description
 
@@ -61,20 +61,37 @@ 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: 3
+- num_epochs: 20
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 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   |
+| 2.0804        | 1.0   | 10   | 2.0714          | 0.1625   |
+| 2.0428        | 2.0   | 20   | 2.0324          | 0.2313   |
+| 1.9463        | 3.0   | 30   | 1.8978          | 0.3438   |
+| 1.7768        | 4.0   | 40   | 1.7234          | 0.375    |
+| 1.6163        | 5.0   | 50   | 1.6029          | 0.4188   |
+| 1.509         | 6.0   | 60   | 1.5122          | 0.5      |
+| 1.4118        | 7.0   | 70   | 1.4839          | 0.4375   |
+| 1.3381        | 8.0   | 80   | 1.4268          | 0.475    |
+| 1.2653        | 9.0   | 90   | 1.4095          | 0.4813   |
+| 1.1979        | 10.0  | 100  | 1.3504          | 0.5375   |
+| 1.1219        | 11.0  | 110  | 1.3293          | 0.4875   |
+| 1.0858        | 12.0  | 120  | 1.3023          | 0.4875   |
+| 1.0214        | 13.0  | 130  | 1.3063          | 0.5188   |
+| 1.0085        | 14.0  | 140  | 1.3306          | 0.5312   |
+| 0.9615        | 15.0  | 150  | 1.2838          | 0.5      |
+| 0.9277        | 16.0  | 160  | 1.3073          | 0.5125   |
+| 0.898         | 17.0  | 170  | 1.2606          | 0.5437   |
+| 0.8747        | 18.0  | 180  | 1.3116          | 0.5437   |
+| 0.8657        | 19.0  | 190  | 1.3171          | 0.5375   |
+| 0.8462        | 20.0  | 200  | 1.2619          | 0.525    |
 
 
 ### Framework versions
 
 - Transformers 4.33.2
-- Pytorch 2.0.1+cu117
-- Datasets 2.14.4
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
 - Tokenizers 0.13.3

pytorch_model.bin

@@ -1,3 +1,3 @@
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+oid sha256:bc5dffc550be0278a1c71b95eef8358431de851e79b100c0954d01b380be9e03
 size 343287149