Model save

README.md

@@ -23,7 +23,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9586776859504132
+      value: 1.0
 ---
 
 <!-- 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 [umm-maybe/AI-image-detector](https://huggingface.co/umm-maybe/AI-image-detector) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2560
-- Accuracy: 0.9587
+- Loss: 0.0001
+- Accuracy: 1.0
 
 ## Model description
 
@@ -59,15 +59,14 @@ The following hyperparameters were used during training:
 - seed: 42
 - 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
-- num_epochs: 5
+- num_epochs: 3
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch  | Step | Validation Loss | Accuracy |
 |:-------------:|:------:|:----:|:---------------:|:--------:|
-| 0.0133        | 2.2727 | 50   | 0.1993          | 0.9835   |
-| 0.0007        | 4.5455 | 100  | 0.2560          | 0.9587   |
+| 0.0009        | 2.2727 | 50   | 0.0001          | 1.0      |
 
 
 ### Framework versions

all_results.json

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eval_results.json

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+}

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runs/Dec31_08-02-30_3dcd8bc8b582/events.out.tfevents.1735632318.3dcd8bc8b582.519.4

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train_results.json

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trainer_state.json

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