End of training

README.md

@@ -1,10 +1,10 @@
 ---
 license: apache-2.0
-base_model: google/vit-base-patch16-224-in21k
+base_model: google/vit-base-patch16-224
 tags:
 - generated_from_trainer
 datasets:
-- imagefolder
+- pokemon-classification
 metrics:
 - accuracy
 model-index:
@@ -14,15 +14,15 @@ model-index:
       name: Image Classification
       type: image-classification
     dataset:
-      name: imagefolder
-      type: imagefolder
-      config: default
-      split: train
-      args: default
+      name: pokemon-classification
+      type: pokemon-classification
+      config: full
+      split: train[:4800]
+      args: full
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.48125
+      value: 0.8854166666666666
 ---
 
 <!-- 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](https://huggingface.co/google/vit-base-patch16-224) on the pokemon-classification dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.4287
-- Accuracy: 0.4813
+- Loss: 0.8072
+- Accuracy: 0.8854
 
 ## Model description
 
@@ -58,22 +58,20 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 5
+- num_epochs: 3
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 1.0   | 40   | 1.7991          | 0.3      |
-| No log        | 2.0   | 80   | 1.5897          | 0.425    |
-| No log        | 3.0   | 120  | 1.5036          | 0.4562   |
-| No log        | 4.0   | 160  | 1.4381          | 0.5125   |
-| No log        | 5.0   | 200  | 1.4394          | 0.4813   |
+| No log        | 1.0   | 240  | 2.0511          | 0.7427   |
+| No log        | 2.0   | 480  | 0.9657          | 0.8792   |
+| 2.3005        | 3.0   | 720  | 0.8118          | 0.8833   |
 
 
 ### Framework versions
 
-- Transformers 4.33.1
+- Transformers 4.33.3
 - Pytorch 2.0.1+cu118
 - Datasets 2.14.5
 - Tokenizers 0.13.3