Model save

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9339596186203029
+      value: 0.9299317110705011
 ---
 
 <!-- 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 [facebook/dinov2-base](https://huggingface.co/facebook/dinov2-base) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2573
-- Accuracy: 0.9340
+- Loss: 0.2714
+- Accuracy: 0.9299
 
 ## Model description
 
@@ -53,11 +53,11 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 5e-05
-- train_batch_size: 4
-- eval_batch_size: 4
+- train_batch_size: 3
+- eval_batch_size: 3
 - seed: 42
-- gradient_accumulation_steps: 4
-- total_train_batch_size: 16
+- gradient_accumulation_steps: 3
+- total_train_batch_size: 9
 - 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 |
 |:-------------:|:-----:|:-----:|:---------------:|:--------:|
-| 0.6069        | 1.0   | 6167  | 0.3864          | 0.8464   |
-| 0.3116        | 2.0   | 12334 | 0.2723          | 0.8988   |
-| 0.1791        | 3.0   | 18501 | 0.2573          | 0.9340   |
+| 0.6782        | 1.0   | 15460 | 0.4996          | 0.8013   |
+| 0.4513        | 2.0   | 30920 | 0.3186          | 0.8837   |
+| 0.2692        | 3.0   | 46380 | 0.2714          | 0.9299   |
 
 
 ### Framework versions