update model card README.md

README.md

@@ -1,7 +1,6 @@
 ---
 license: apache-2.0
 tags:
-- image-classification
 - generated_from_trainer
 datasets:
 - imagefolder
@@ -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
@@ -22,7 +21,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.7411764705882353
+      value: 0.7705882352941177
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -30,10 +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: 0.6702
-- Accuracy: 0.7412
+- Loss: 0.7446
+- Accuracy: 0.7706
 
 ## Model description
 
@@ -58,18 +57,35 @@ 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: 6
+- num_epochs: 25
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 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   |
+| 1.1638        | 1.1   | 100  | 1.0564          | 0.5471   |
+| 0.8524        | 2.2   | 200  | 0.9403          | 0.6118   |
+| 0.8231        | 3.3   | 300  | 0.8282          | 0.7176   |
+| 0.7398        | 4.4   | 400  | 0.9056          | 0.6294   |
+| 0.41          | 5.49  | 500  | 0.8815          | 0.6235   |
+| 0.4849        | 6.59  | 600  | 0.9505          | 0.6294   |
+| 0.3894        | 7.69  | 700  | 0.8052          | 0.6882   |
+| 0.4678        | 8.79  | 800  | 0.8424          | 0.7059   |
+| 0.4279        | 9.89  | 900  | 0.9639          | 0.6706   |
+| 0.3461        | 10.99 | 1000 | 0.8497          | 0.7059   |
+| 0.2741        | 12.09 | 1100 | 0.9090          | 0.7      |
+| 0.1771        | 13.19 | 1200 | 0.8292          | 0.7118   |
+| 0.1779        | 14.29 | 1300 | 1.1314          | 0.6294   |
+| 0.2044        | 15.38 | 1400 | 0.8349          | 0.7294   |
+| 0.1543        | 16.48 | 1500 | 0.8952          | 0.6941   |
+| 0.1283        | 17.58 | 1600 | 0.8054          | 0.7353   |
+| 0.1721        | 18.68 | 1700 | 0.9094          | 0.7235   |
+| 0.1509        | 19.78 | 1800 | 0.9168          | 0.7412   |
+| 0.1257        | 20.88 | 1900 | 0.9395          | 0.7412   |
+| 0.1747        | 21.98 | 2000 | 0.8746          | 0.7471   |
+| 0.1506        | 23.08 | 2100 | 0.7992          | 0.7353   |
+| 0.1021        | 24.18 | 2200 | 0.7446          | 0.7706   |
 
 
 ### Framework versions