End of training

README.md

@@ -23,7 +23,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.48552821997105644
+      value: 0.7597684515195369
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -33,8 +33,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [CGCTG/orientation_resnet-50](https://huggingface.co/CGCTG/orientation_resnet-50) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.8638
-- Accuracy: 0.4855
+- Loss: 0.5106
+- Accuracy: 0.7598
 
 ## Model description
 
@@ -62,14 +62,16 @@ The following hyperparameters were used during training:
 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 1
+- num_epochs: 3
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch  | Step | Validation Loss | Accuracy |
 |:-------------:|:------:|:----:|:---------------:|:--------:|
-| 0.8151        | 0.9942 | 86   | 0.8638          | 0.4855   |
+| 0.7836        | 1.0    | 87   | 1.2301          | 0.4986   |
+| 0.6808        | 2.0    | 174  | 0.6659          | 0.6382   |
+| 0.5641        | 2.9711 | 258  | 0.5106          | 0.7598   |
 
 
 ### Framework versions