End of training

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.36875
+      value: 0.44375
 ---
 
 <!-- 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: 1.5998
-- Accuracy: 0.3688
+- Loss: 1.5356
+- Accuracy: 0.4437
 
 ## Model description
 
@@ -53,11 +53,11 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 5e-05
-- train_batch_size: 32
-- eval_batch_size: 32
+- train_batch_size: 16
+- eval_batch_size: 16
 - seed: 42
 - gradient_accumulation_steps: 4
-- total_train_batch_size: 128
+- total_train_batch_size: 64
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
@@ -67,16 +67,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 1.0   | 5    | 2.0612          | 0.1812   |
-| 2.0585        | 2.0   | 10   | 2.0091          | 0.3125   |
-| 2.0585        | 3.0   | 15   | 1.9362          | 0.375    |
-| 1.9064        | 4.0   | 20   | 1.8335          | 0.3812   |
-| 1.9064        | 5.0   | 25   | 1.7466          | 0.35     |
-| 1.7196        | 6.0   | 30   | 1.6906          | 0.3312   |
-| 1.7196        | 7.0   | 35   | 1.6453          | 0.375    |
-| 1.5947        | 8.0   | 40   | 1.6180          | 0.4125   |
-| 1.5947        | 9.0   | 45   | 1.5876          | 0.4375   |
-| 1.5433        | 10.0  | 50   | 1.5849          | 0.4062   |
+| 2.0785        | 1.0   | 10   | 2.0617          | 0.125    |
+| 2.0054        | 2.0   | 20   | 1.9826          | 0.275    |
+| 1.8694        | 3.0   | 30   | 1.8516          | 0.325    |
+| 1.7212        | 4.0   | 40   | 1.7082          | 0.3812   |
+| 1.6101        | 5.0   | 50   | 1.6297          | 0.4375   |
+| 1.5409        | 6.0   | 60   | 1.5981          | 0.4188   |
+| 1.4801        | 7.0   | 70   | 1.5526          | 0.4437   |
+| 1.433         | 8.0   | 80   | 1.5574          | 0.4813   |
+| 1.4056        | 9.0   | 90   | 1.5094          | 0.5062   |
+| 1.3797        | 10.0  | 100  | 1.5232          | 0.4688   |
 
 
 ### Framework versions