font-identifier

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.38979591836734695
+      value: 0.9040816326530612
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [microsoft/resnet-18](https://huggingface.co/microsoft/resnet-18) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 2.5735
-- Accuracy: 0.3898
+- Loss: 0.3626
+- Accuracy: 0.9041
 
 ## Model description
 
@@ -61,15 +61,32 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 3
+- num_epochs: 20
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 3.5314        | 0.98  | 30   | 3.2829          | 0.2082   |
-| 2.9107        | 1.98  | 61   | 2.6947          | 0.3633   |
-| 2.6604        | 2.93  | 90   | 2.5735          | 0.3898   |
+| 3.929         | 0.98  | 30   | 3.8215          | 0.0429   |
+| 3.2162        | 1.98  | 61   | 2.9144          | 0.2816   |
+| 2.4387        | 2.99  | 92   | 2.1019          | 0.4776   |
+| 1.9404        | 4.0   | 123  | 1.5607          | 0.6041   |
+| 1.5756        | 4.98  | 153  | 1.3012          | 0.6449   |
+| 1.3374        | 5.98  | 184  | 1.0699          | 0.7102   |
+| 1.1912        | 6.99  | 215  | 0.9145          | 0.7633   |
+| 1.0716        | 8.0   | 246  | 0.7864          | 0.7898   |
+| 0.9751        | 8.98  | 276  | 0.6894          | 0.8204   |
+| 0.8211        | 9.98  | 307  | 0.6256          | 0.8510   |
+| 0.8254        | 10.99 | 338  | 0.5563          | 0.8633   |
+| 0.742         | 12.0  | 369  | 0.5149          | 0.8694   |
+| 0.6949        | 12.98 | 399  | 0.4625          | 0.8878   |
+| 0.6401        | 13.98 | 430  | 0.4799          | 0.8857   |
+| 0.6304        | 14.99 | 461  | 0.3970          | 0.8980   |
+| 0.6239        | 16.0  | 492  | 0.4016          | 0.9      |
+| 0.5911        | 16.98 | 522  | 0.4271          | 0.8755   |
+| 0.5764        | 17.98 | 553  | 0.3922          | 0.9      |
+| 0.5461        | 18.99 | 584  | 0.3750          | 0.9      |
+| 0.6236        | 19.51 | 600  | 0.3626          | 0.9041   |
 
 
 ### Framework versions