update model card README.md

README.md

@@ -19,7 +19,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.8761682242990654
+      value: 0.8696261682242991
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -29,8 +29,8 @@ 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 image_folder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.3875
-- Accuracy: 0.8762
+- Loss: 0.3756
+- Accuracy: 0.8696
 
 ## Model description
 
@@ -50,11 +50,11 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 5e-05
-- train_batch_size: 8
-- eval_batch_size: 8
+- train_batch_size: 32
+- eval_batch_size: 32
 - seed: 42
 - gradient_accumulation_steps: 4
-- total_train_batch_size: 32
+- total_train_batch_size: 128
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
@@ -64,16 +64,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.5531        | 1.0   | 535  | 0.4938          | 0.8336   |
-| 0.4139        | 2.0   | 1070 | 0.4071          | 0.8612   |
-| 0.287         | 3.0   | 1605 | 0.3954          | 0.8643   |
-| 0.4211        | 4.0   | 2140 | 0.3906          | 0.8701   |
-| 0.316         | 5.0   | 2675 | 0.3716          | 0.8755   |
-| 0.2709        | 6.0   | 3210 | 0.3784          | 0.8736   |
-| 0.177         | 7.0   | 3745 | 0.3772          | 0.8745   |
-| 0.2409        | 8.0   | 4280 | 0.3875          | 0.8762   |
-| 0.1929        | 9.0   | 4815 | 0.3915          | 0.8708   |
-| 0.1877        | 10.0  | 5350 | 0.3881          | 0.8715   |
+| 0.5628        | 1.0   | 150  | 0.5357          | 0.8308   |
+| 0.4398        | 2.0   | 300  | 0.4311          | 0.8598   |
+| 0.4022        | 3.0   | 450  | 0.3958          | 0.8668   |
+| 0.3855        | 4.0   | 600  | 0.4030          | 0.8598   |
+| 0.3659        | 5.0   | 750  | 0.4125          | 0.8617   |
+| 0.3393        | 6.0   | 900  | 0.3840          | 0.8673   |
+| 0.3022        | 7.0   | 1050 | 0.3775          | 0.8673   |
+| 0.2941        | 8.0   | 1200 | 0.3742          | 0.8706   |
+| 0.2903        | 9.0   | 1350 | 0.3809          | 0.8696   |
+| 0.2584        | 10.0  | 1500 | 0.3756          | 0.8696   |
 
 
 ### Framework versions