Model save

README.md

@@ -2,15 +2,12 @@
 license: apache-2.0
 base_model: google/vit-base-patch16-224-in21k
 tags:
-- image-classification
-- vision
 - generated_from_trainer
 metrics:
 - accuracy
 model-index:
 - name: vit-base-beans
   results: []
-pipeline_tag: image-classification
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -18,10 +15,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # vit-base-beans
 
-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 beans dataset.
+This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1028
-- Accuracy: 0.9699
+- Loss: 0.0797
+- Accuracy: 0.9774
 
 ## Model description
 
@@ -41,24 +38,27 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 2e-05
-- train_batch_size: 2
-- eval_batch_size: 2
+- train_batch_size: 8
+- eval_batch_size: 8
 - seed: 1337
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 2.0
+- num_epochs: 5.0
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.056         | 1.0   | 517  | 0.1028          | 0.9699   |
-| 0.0627        | 2.0   | 1034 | 0.1100          | 0.9699   |
+| 0.281         | 1.0   | 130  | 0.2194          | 0.9624   |
+| 0.1268        | 2.0   | 260  | 0.1289          | 0.9699   |
+| 0.1385        | 3.0   | 390  | 0.0968          | 0.9699   |
+| 0.0749        | 4.0   | 520  | 0.0627          | 0.9925   |
+| 0.1089        | 5.0   | 650  | 0.0797          | 0.9774   |
 
 
 ### Framework versions
 
-- Transformers 4.41.0.dev0
-- Pytorch 2.2.2+cu121
-- Datasets 2.19.0
-- Tokenizers 0.19.1
+- Transformers 4.41.1
+- Pytorch 2.3.0
+- Datasets 2.19.1
+- Tokenizers 0.19.1

model.safetensors

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runs/May23_21-28-08_Edus-MacBook-Pro.local/events.out.tfevents.1716496163.Edus-MacBook-Pro.local

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