End of training

README.md

@@ -23,7 +23,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.39375
+      value: 0.5625
 ---
 
 <!-- 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 [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.8689
-- Accuracy: 0.3937
+- Loss: 1.2464
+- Accuracy: 0.5625
 
 ## Model description
 
@@ -62,14 +62,15 @@ The following hyperparameters were used during training:
 - 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
+- num_epochs: 50
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.8309        | 10.0  | 100  | 1.8611          | 0.35     |
+| 1.1547        | 20.0  | 200  | 1.3886          | 0.4437   |
+| 0.8794        | 40.0  | 400  | 1.2265          | 0.55     |
 
 
 ### Framework versions

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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 size 343242432

runs/Sep06_11-35-13_c027da26715b/events.out.tfevents.1725623123.c027da26715b.482.3

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+oid sha256:abe7ceef6af530c10754324b374466c93fa77407fbc3a7d4a3b0051ff12fda5d
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