End of training

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.48125
+      value: 0.50625
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 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: 1.4776
-- Accuracy: 0.4813
+- Loss: 1.5890
+- Accuracy: 0.5062
 
 ## Model description
 
@@ -52,35 +52,34 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 5e-05
+- learning_rate: 3e-05
 - train_batch_size: 64
 - eval_batch_size: 64
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 16
+- num_epochs: 15
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 1.0   | 10   | 2.0310          | 0.2562   |
-| No log        | 2.0   | 20   | 1.9290          | 0.35     |
-| No log        | 3.0   | 30   | 1.8243          | 0.425    |
-| No log        | 4.0   | 40   | 1.7218          | 0.4562   |
-| No log        | 5.0   | 50   | 1.6600          | 0.4437   |
-| No log        | 6.0   | 60   | 1.6212          | 0.45     |
-| No log        | 7.0   | 70   | 1.5844          | 0.425    |
-| No log        | 8.0   | 80   | 1.5498          | 0.4437   |
-| No log        | 9.0   | 90   | 1.5272          | 0.4688   |
-| No log        | 10.0  | 100  | 1.5168          | 0.4562   |
-| No log        | 11.0  | 110  | 1.5019          | 0.4562   |
-| No log        | 12.0  | 120  | 1.4895          | 0.4562   |
-| No log        | 13.0  | 130  | 1.4857          | 0.475    |
-| No log        | 14.0  | 140  | 1.4810          | 0.4688   |
-| No log        | 15.0  | 150  | 1.4786          | 0.4688   |
-| No log        | 16.0  | 160  | 1.4776          | 0.4813   |
+| No log        | 1.0   | 10   | 2.0332          | 0.25     |
+| No log        | 2.0   | 20   | 1.9720          | 0.3125   |
+| No log        | 3.0   | 30   | 1.8937          | 0.3688   |
+| No log        | 4.0   | 40   | 1.8265          | 0.375    |
+| No log        | 5.0   | 50   | 1.7561          | 0.3937   |
+| No log        | 6.0   | 60   | 1.7083          | 0.45     |
+| No log        | 7.0   | 70   | 1.6719          | 0.4375   |
+| No log        | 8.0   | 80   | 1.6415          | 0.4688   |
+| No log        | 9.0   | 90   | 1.6237          | 0.4813   |
+| No log        | 10.0  | 100  | 1.6041          | 0.4938   |
+| No log        | 11.0  | 110  | 1.5890          | 0.5062   |
+| No log        | 12.0  | 120  | 1.5774          | 0.5      |
+| No log        | 13.0  | 130  | 1.5700          | 0.5      |
+| No log        | 14.0  | 140  | 1.5659          | 0.5062   |
+| No log        | 15.0  | 150  | 1.5643          | 0.5062   |
 
 
 ### Framework versions

model.safetensors

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