End of training

README.md

@@ -1,4 +1,5 @@
 ---
+library_name: transformers
 license: apache-2.0
 base_model: google/vit-base-patch16-224
 tags:
@@ -22,7 +23,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.48125
+      value: 0.575
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +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](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.3523
-- Accuracy: 0.4813
+- Loss: 1.3098
+- Accuracy: 0.575
 
 ## Model description
 
@@ -58,27 +59,37 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 10
+- num_epochs: 20
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 2.093         | 1.0   | 10   | 1.8451          | 0.3312   |
-| 1.4651        | 2.0   | 20   | 1.6375          | 0.3812   |
-| 1.033         | 3.0   | 30   | 1.5209          | 0.3875   |
-| 0.7164        | 4.0   | 40   | 1.4455          | 0.4375   |
-| 0.4719        | 5.0   | 50   | 1.3971          | 0.425    |
-| 0.3109        | 6.0   | 60   | 1.3746          | 0.475    |
-| 0.2034        | 7.0   | 70   | 1.3600          | 0.45     |
-| 0.1403        | 8.0   | 80   | 1.3523          | 0.4813   |
-| 0.1074        | 9.0   | 90   | 1.3493          | 0.4813   |
-| 0.0931        | 10.0  | 100  | 1.3471          | 0.475    |
+| No log        | 1.0   | 10   | 1.8622          | 0.2875   |
+| 1.7517        | 2.0   | 20   | 1.6548          | 0.45     |
+| 1.7517        | 3.0   | 30   | 1.4987          | 0.4688   |
+| 0.8128        | 4.0   | 40   | 1.3997          | 0.5125   |
+| 0.8128        | 5.0   | 50   | 1.3707          | 0.5125   |
+| 0.2863        | 6.0   | 60   | 1.3209          | 0.525    |
+| 0.2863        | 7.0   | 70   | 1.3131          | 0.55     |
+| 0.0776        | 8.0   | 80   | 1.2887          | 0.5563   |
+| 0.0776        | 9.0   | 90   | 1.2996          | 0.5687   |
+| 0.0267        | 10.0  | 100  | 1.3032          | 0.5563   |
+| 0.0267        | 11.0  | 110  | 1.3003          | 0.5625   |
+| 0.0156        | 12.0  | 120  | 1.3069          | 0.5625   |
+| 0.0156        | 13.0  | 130  | 1.3039          | 0.5687   |
+| 0.0117        | 14.0  | 140  | 1.3037          | 0.5687   |
+| 0.0117        | 15.0  | 150  | 1.3059          | 0.5687   |
+| 0.0098        | 16.0  | 160  | 1.3098          | 0.575    |
+| 0.0098        | 17.0  | 170  | 1.3095          | 0.5625   |
+| 0.0088        | 18.0  | 180  | 1.3107          | 0.5625   |
+| 0.0088        | 19.0  | 190  | 1.3112          | 0.5687   |
+| 0.0083        | 20.0  | 200  | 1.3112          | 0.5687   |
 
 
 ### Framework versions
 
-- Transformers 4.42.4
+- Transformers 4.44.2
 - Pytorch 2.4.0+cu121
 - Datasets 2.21.0
 - Tokenizers 0.19.1

config.json

@@ -40,5 +40,5 @@
   "problem_type": "single_label_classification",
   "qkv_bias": true,
   "torch_dtype": "float32",
-  "transformers_version": "4.42.4"
+  "transformers_version": "4.44.2"
 }

model.safetensors

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 size 343242432

training_args.bin

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+size 5176