End of training

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9911111111111112
+      value: 0.992
 ---
 
 <!-- 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 [02shanky/vit-finetuned-cifar10](https://huggingface.co/02shanky/vit-finetuned-cifar10) on the cifar10 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0336
-- Accuracy: 0.9911
+- Loss: 0.0306
+- Accuracy: 0.992
 
 ## Model description
 
@@ -53,21 +53,24 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 0.0001
-- train_batch_size: 16
-- eval_batch_size: 16
+- train_batch_size: 32
+- eval_batch_size: 32
 - seed: 42
 - gradient_accumulation_steps: 4
-- total_train_batch_size: 64
+- total_train_batch_size: 128
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 2
+- num_epochs: 5
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.306         | 1.0   | 633  | 0.0478          | 0.986    |
-| 0.2268        | 2.0   | 1266 | 0.0336          | 0.9911   |
+| No log        | 1.0   | 316  | 0.0619          | 0.9836   |
+| 0.2651        | 2.0   | 633  | 0.0460          | 0.9867   |
+| 0.2651        | 3.0   | 949  | 0.0415          | 0.9878   |
+| 0.1967        | 4.0   | 1266 | 0.0326          | 0.9916   |
+| 0.1552        | 4.99  | 1580 | 0.0306          | 0.992    |
 
 
 ### Framework versions