End of training

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.7247910863509749
+      value: 0.9233983286908078
 ---
 
 <!-- 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 [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 3.0045
-- Accuracy: 0.7248
+- Loss: 0.3754
+- Accuracy: 0.9234
 
 ## Model description
 
@@ -53,11 +53,11 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 5e-05
-- train_batch_size: 128
-- eval_batch_size: 128
+- train_batch_size: 16
+- eval_batch_size: 16
 - seed: 42
 - gradient_accumulation_steps: 4
-- total_train_batch_size: 512
+- 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
@@ -67,9 +67,9 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.182         | 1.0   | 195  | -0.8006         | 0.7227   |
-| 0.1055        | 2.0   | 391  | -1.0724         | 0.7400   |
-| 0.0931        | 2.99  | 585  | 3.0045          | 0.7248   |
+| 0.0776        | 1.0   | 1562 | 0.2637          | 0.9251   |
+| 0.0241        | 2.0   | 3125 | 0.3806          | 0.9213   |
+| 0.0367        | 3.0   | 4686 | 0.3754          | 0.9234   |
 
 
 ### Framework versions

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:3c45b9009043eea3acfda99353da5a722eb719cc61e14be5ba9136974c0115ea
+oid sha256:580d2f27d23634c0f75781261cf0abd5035a872c98da0b098278ebc6e2527c9f
 size 110371676