End of training

README.md

@@ -21,7 +21,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9899328859060402
+      value: 0.9941275167785235
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,8 +31,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [microsoft/dit-base-finetuned-rvlcdip](https://huggingface.co/microsoft/dit-base-finetuned-rvlcdip) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0346
-- Accuracy: 0.9899
+- Loss: 0.0113
+- Accuracy: 0.9941
 
 ## Model description
 
@@ -60,13 +60,17 @@ 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: 1
+- num_epochs: 5
 
 ### Training results
 
 | Training Loss | Epoch  | Step | Validation Loss | Accuracy |
 |:-------------:|:------:|:----:|:---------------:|:--------:|
-| 0.0362        | 0.9954 | 162  | 0.0346          | 0.9899   |
+| 0.0374        | 0.9954 | 162  | 0.0350          | 0.9866   |
+| 0.0233        | 1.9969 | 325  | 0.0258          | 0.9891   |
+| 0.0253        | 2.9985 | 488  | 0.0188          | 0.9916   |
+| 0.0103        | 4.0    | 651  | 0.0283          | 0.9908   |
+| 0.0065        | 4.9770 | 810  | 0.0113          | 0.9941   |
 
 
 ### Framework versions