Model save

README.md

@@ -23,7 +23,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9777131782945736
+      value: 0.9798934108527132
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -33,8 +33,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window16-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window16-256) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0636
-- Accuracy: 0.9777
+- Loss: 0.0568
+- Accuracy: 0.9799
 
 ## Model description
 
@@ -59,7 +59,7 @@ The following hyperparameters were used during training:
 - seed: 42
 - gradient_accumulation_steps: 4
 - total_train_batch_size: 32
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
 - num_epochs: 1
@@ -68,12 +68,12 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.103         | 1.0   | 516  | 0.0636          | 0.9777   |
+| 0.1279        | 1.0   | 516  | 0.0568          | 0.9799   |
 
 
 ### Framework versions
 
-- Transformers 4.44.2
-- Pytorch 2.5.0+cu121
+- Transformers 4.46.2
+- Pytorch 2.5.1+cu121
 - Datasets 3.1.0
-- Tokenizers 0.19.1
+- Tokenizers 0.20.3