Model save

README.md

@@ -2,29 +2,12 @@
 license: apache-2.0
 base_model: google/vit-base-patch16-224-in21k
 tags:
-- image-classification
-- vision
 - generated_from_trainer
-datasets:
-- beans
 metrics:
 - accuracy
 model-index:
 - name: vit-base-beans
-  results:
-  - task:
-      name: Image Classification
-      type: image-classification
-    dataset:
-      name: beans
-      type: beans
-      config: default
-      split: validation
-      args: default
-    metrics:
-    - name: Accuracy
-      type: accuracy
-      value: 0.9774436090225563
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,10 +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: 0.0845
-- Accuracy: 0.9774
+- Loss: 0.1031
+- Accuracy: 0.9699
 
 ## Model description
 
@@ -57,7 +40,7 @@ The following hyperparameters were used during training:
 - learning_rate: 2e-05
 - train_batch_size: 8
 - eval_batch_size: 8
-- seed: 1337
+- seed: 2024
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - num_epochs: 5.0
@@ -66,16 +49,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.2975        | 1.0   | 130  | 0.2141          | 0.9699   |
-| 0.2145        | 2.0   | 260  | 0.1453          | 0.9699   |
-| 0.202         | 3.0   | 390  | 0.1253          | 0.9699   |
-| 0.0878        | 4.0   | 520  | 0.0966          | 0.9774   |
-| 0.106         | 5.0   | 650  | 0.0845          | 0.9774   |
+| 0.2939        | 1.0   | 130  | 0.2577          | 0.9699   |
+| 0.1955        | 2.0   | 260  | 0.1212          | 0.9774   |
+| 0.2097        | 3.0   | 390  | 0.1058          | 0.9699   |
+| 0.1102        | 4.0   | 520  | 0.1146          | 0.9699   |
+| 0.1813        | 5.0   | 650  | 0.1031          | 0.9699   |
 
 
 ### Framework versions
 
-- Transformers 4.36.0
-- Pytorch 2.1.0+cu121
-- Datasets 2.14.6
+- Transformers 4.38.0.dev0
+- Pytorch 1.13.1+cu117
+- Datasets 2.15.0
 - Tokenizers 0.15.0