update model card README.md

README.md

@@ -1,10 +1,9 @@
 ---
 license: apache-2.0
 tags:
-- image-classification
 - generated_from_trainer
 datasets:
-- alkzar90/croupier-mtg-dataset
+- imagefolder
 metrics:
 - accuracy
 model-index:
@@ -14,7 +13,7 @@ model-index:
       name: Image Classification
       type: image-classification
     dataset:
-      name: croupier-mtg-dataset
+      name: imagefolder
       type: imagefolder
       config: alkzar90--croupier-mtg-dataset
       split: train
@@ -22,16 +21,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.8058823529411765
-widget:
-- src: https://huggingface.co/alkzar90/croupier-creature-classifier/resolve/main/examples/crusader_peco_peco.png
-  example_title: Crusader-Rangarok-Online
-- src: https://huggingface.co/alkzar90/croupier-creature-classifier/resolve/main/examples/goblin_wow.png
-  example_title: Goblin-WoW
-- src: https://huggingface.co/alkzar90/croupier-creature-classifier/resolve/main/examples/dobby_harry_potter.jpg
-  example_title: Dobby-Harry-Potter
-- src: https://huggingface.co/alkzar90/croupier-creature-classifier/resolve/main/examples/resident_evil_nemesis.jpeg
-  example_title: Nemesis-Resident-Evil
+      value: 0.7058823529411765
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -39,10 +29,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # croupier-creature-classifier
 
-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 croupier-mtg-dataset 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 the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.6480
-- Accuracy: 0.8059
+- Loss: 0.7184
+- Accuracy: 0.7059
 
 ## Model description
 
@@ -67,31 +57,23 @@ 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: 15
+- num_epochs: 6
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.1967        | 1.1   | 100  | 0.6480          | 0.8059   |
-| 0.1047        | 2.2   | 200  | 0.8703          | 0.7529   |
-| 0.2249        | 3.3   | 300  | 0.9539          | 0.7588   |
-| 0.0984        | 4.4   | 400  | 0.9319          | 0.7529   |
-| 0.086         | 5.49  | 500  | 0.9061          | 0.7706   |
-| 0.1164        | 6.59  | 600  | 0.7493          | 0.8176   |
-| 0.0518        | 7.69  | 700  | 0.8781          | 0.7765   |
-| 0.0458        | 8.79  | 800  | 0.8851          | 0.7824   |
-| 0.0521        | 9.89  | 900  | 0.9448          | 0.7882   |
-| 0.0576        | 10.99 | 1000 | 0.8884          | 0.7824   |
-| 0.0442        | 12.09 | 1100 | 0.8965          | 0.7882   |
-| 0.0254        | 13.19 | 1200 | 0.9140          | 0.7882   |
-| 0.0426        | 14.29 | 1300 | 0.9274          | 0.7882   |
+| 0.8932        | 1.1   | 100  | 0.9914          | 0.6059   |
+| 0.6608        | 2.2   | 200  | 0.8645          | 0.6588   |
+| 0.6084        | 3.3   | 300  | 0.7326          | 0.7294   |
+| 0.5261        | 4.4   | 400  | 0.7684          | 0.6941   |
+| 0.2511        | 5.49  | 500  | 0.7184          | 0.7059   |
 
 
 ### Framework versions
 
-- Transformers 4.21.0
+- Transformers 4.21.1
 - Pytorch 1.12.0+cu113
 - Datasets 2.4.0
 - Tokenizers 0.12.1