Update README.md

README.md

@@ -36,13 +36,14 @@ language:
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
 
-# dinov2-base-finetuned-dia_eye
+
+Diabetic_RetinoPathy_detection
 
 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: 0.4215
-- Accuracy: 0.88
-- F1: 0.8802
+- Loss: 0.2262
+- Accuracy: 0.968
+- F1: 0.9678
 
 ## Model description
 
@@ -67,7 +68,7 @@ The following hyperparameters were used during training:
 - seed: 42
 - gradient_accumulation_steps: 4
 - total_train_batch_size: 16
-- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
 - num_epochs: 10
@@ -76,21 +77,22 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 1.2812        | 1.0   | 250  | 1.1659          | 0.494    | 0.4460 |
-| 1.0885        | 2.0   | 500  | 1.1570          | 0.46     | 0.4098 |
-| 1.0673        | 3.0   | 750  | 1.1951          | 0.51     | 0.4777 |
-| 0.9863        | 4.0   | 1000 | 0.8480          | 0.622    | 0.6316 |
-| 0.8241        | 5.0   | 1250 | 0.7028          | 0.706    | 0.7049 |
-| 0.7208        | 6.0   | 1500 | 0.7059          | 0.712    | 0.6910 |
-| 0.5563        | 7.0   | 1750 | 0.5728          | 0.782    | 0.7813 |
-| 0.3988        | 8.0   | 2000 | 0.5472          | 0.826    | 0.8239 |
-| 0.4643        | 9.0   | 2250 | 0.4736          | 0.85     | 0.8503 |
-| 0.2625        | 10.0  | 2500 | 0.4215          | 0.88     | 0.8802 |
+| 0.3853        | 1.0   | 250  | 0.4918          | 0.874    | 0.8729 |
+| 0.5345        | 2.0   | 500  | 0.4390          | 0.878    | 0.8771 |
+| 0.4693        | 3.0   | 750  | 0.3857          | 0.88     | 0.8796 |
+| 0.1933        | 4.0   | 1000 | 0.3444          | 0.894    | 0.8948 |
+| 0.3146        | 5.0   | 1250 | 0.2456          | 0.936    | 0.9362 |
+| 0.1832        | 6.0   | 1500 | 0.3369          | 0.924    | 0.9229 |
+| 0.1407        | 7.0   | 1750 | 0.3425          | 0.946    | 0.9454 |
+| 0.1462        | 8.0   | 2000 | 0.2864          | 0.948    | 0.9476 |
+| 0.0905        | 9.0   | 2250 | 0.2177          | 0.956    | 0.9560 |
+| 0.0859        | 10.0  | 2500 | 0.2262          | 0.968    | 0.9678 |
 
 
 ### Framework versions
 
-- Transformers 4.48.3
-- Pytorch 2.6.0+cu124
-- Datasets 3.4.0
-- Tokenizers 0.21.0
+- Transformers 4.45.1
+- Pytorch 2.4.0
+- Datasets 3.0.1
+- Tokenizers 0.20.0
+