End of training

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.53125
+      value: 0.5375
 ---
 
 <!-- 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 imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.8129
-- Accuracy: 0.5312
+- Loss: 1.3694
+- Accuracy: 0.5375
 
 ## Model description
 
@@ -53,38 +53,41 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 5e-05
-- train_batch_size: 16
-- eval_batch_size: 16
+- train_batch_size: 64
+- eval_batch_size: 64
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: cosine_with_restarts
-- lr_scheduler_warmup_steps: 30
-- num_epochs: 15
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 9
+- num_epochs: 18
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 1.0   | 40   | 1.4349          | 0.45     |
-| No log        | 2.0   | 80   | 1.4560          | 0.5      |
-| No log        | 3.0   | 120  | 1.5158          | 0.4813   |
-| No log        | 4.0   | 160  | 1.4489          | 0.5125   |
-| No log        | 5.0   | 200  | 1.8968          | 0.425    |
-| No log        | 6.0   | 240  | 1.6870          | 0.5062   |
-| No log        | 7.0   | 280  | 1.6759          | 0.4813   |
-| No log        | 8.0   | 320  | 1.6498          | 0.5312   |
-| No log        | 9.0   | 360  | 1.7581          | 0.5      |
-| No log        | 10.0  | 400  | 1.7798          | 0.5      |
-| No log        | 11.0  | 440  | 1.6983          | 0.525    |
-| No log        | 12.0  | 480  | 1.7756          | 0.5375   |
-| 0.1761        | 13.0  | 520  | 1.7346          | 0.5125   |
-| 0.1761        | 14.0  | 560  | 1.8079          | 0.525    |
-| 0.1761        | 15.0  | 600  | 1.7950          | 0.5188   |
+| No log        | 1.0   | 10   | 2.0629          | 0.1437   |
+| No log        | 2.0   | 20   | 2.0123          | 0.275    |
+| No log        | 3.0   | 30   | 1.9333          | 0.3312   |
+| No log        | 4.0   | 40   | 1.8060          | 0.3812   |
+| No log        | 5.0   | 50   | 1.7009          | 0.3563   |
+| No log        | 6.0   | 60   | 1.6149          | 0.4188   |
+| No log        | 7.0   | 70   | 1.5948          | 0.4437   |
+| No log        | 8.0   | 80   | 1.5391          | 0.5      |
+| No log        | 9.0   | 90   | 1.4770          | 0.4688   |
+| No log        | 10.0  | 100  | 1.5026          | 0.5      |
+| No log        | 11.0  | 110  | 1.4644          | 0.4437   |
+| No log        | 12.0  | 120  | 1.4115          | 0.5125   |
+| No log        | 13.0  | 130  | 1.4216          | 0.4813   |
+| No log        | 14.0  | 140  | 1.4086          | 0.5      |
+| No log        | 15.0  | 150  | 1.4093          | 0.5      |
+| No log        | 16.0  | 160  | 1.3891          | 0.4875   |
+| No log        | 17.0  | 170  | 1.3754          | 0.4938   |
+| No log        | 18.0  | 180  | 1.3779          | 0.5188   |
 
 
 ### Framework versions
 
 - Transformers 4.41.1
-- Pytorch 2.3.0+cu121
+- Pytorch 2.1.2
 - Datasets 2.19.1
 - Tokenizers 0.19.1

runs/Jun04_14-42-56_7ce828253425/events.out.tfevents.1717512604.7ce828253425.34.1

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+size 1057