End of training

README.md

@@ -17,12 +17,12 @@ model-index:
       name: fair_face
       type: fair_face
       config: '0.25'
-      split: train[:5000]
+      split: validation
       args: '0.25'
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.152
+      value: 0.21252510498448055
 ---
 
 <!-- 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 [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the fair_face dataset.
 It achieves the following results on the evaluation set:
-- Loss: 4.1666
-- Accuracy: 0.152
+- Loss: 3.6347
+- Accuracy: 0.2125
 
 ## Model description
 
@@ -61,15 +61,18 @@ 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: 0.2
-- num_epochs: 10
+- num_epochs: 1
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 4.7179        | 3.17  | 50   | 4.5313          | 0.094    |
-| 4.3281        | 6.35  | 100  | 4.2542          | 0.122    |
-| 4.1225        | 9.52  | 150  | 4.1666          | 0.152    |
+| 4.7855        | 0.15  | 50   | 4.6444          | 0.0511   |
+| 4.4242        | 0.29  | 100  | 4.2124          | 0.1418   |
+| 4.0596        | 0.44  | 150  | 3.9402          | 0.1744   |
+| 3.859         | 0.59  | 200  | 3.7823          | 0.1956   |
+| 3.7392        | 0.74  | 250  | 3.6877          | 0.2105   |
+| 3.6424        | 0.88  | 300  | 3.6347          | 0.2125   |
 
 
 ### Framework versions

model.safetensors

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training_args.bin

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