Model save

README.md

@@ -1,14 +1,28 @@
 ---
-license: apache-2.0
-base_model: google/vit-base-patch16-224-in21k
+license: other
+base_model: apple/mobilevit-xx-small
 tags:
-- image-classification
 - generated_from_trainer
 datasets:
 - imagefolder
+metrics:
+- accuracy
 model-index:
 - name: vit-base-plankton
-  results: []
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8050847457627118
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -16,7 +30,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # vit-base-plankton
 
-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 plankotn dataset.
+This model is a fine-tuned version of [apple/mobilevit-xx-small](https://huggingface.co/apple/mobilevit-xx-small) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7642
+- Accuracy: 0.8051
 
 ## Model description
 
@@ -43,6 +60,15 @@ The following hyperparameters were used during training:
 - lr_scheduler_type: linear
 - num_epochs: 2
 
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.5476        | 0.52  | 100  | 1.2745          | 0.7419   |
+| 1.0997        | 1.04  | 200  | 0.8653          | 0.7842   |
+| 0.9498        | 1.56  | 300  | 0.7642          | 0.8051   |
+
+
 ### Framework versions
 
 - Transformers 4.35.2

runs/Nov19_15-47-32_12be7f682407/events.out.tfevents.1700408857.12be7f682407.128.1

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+size 12393