End of training

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.7
+      value: 0.7252427184466019
 ---
 
 <!-- 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 [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.0025
-- Accuracy: 0.7
+- Loss: 1.0414
+- Accuracy: 0.7252
 
 ## Model description
 
@@ -58,25 +58,35 @@ The following hyperparameters were used during training:
 - seed: 42
 - gradient_accumulation_steps: 2
 - total_train_batch_size: 16
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-05
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=0.0003
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 10
+- num_epochs: 20
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.9827        | 1.0   | 442  | 1.8651          | 0.4065   |
-| 1.7182        | 2.0   | 884  | 1.6669          | 0.4501   |
-| 1.505         | 3.0   | 1326 | 1.4498          | 0.5246   |
-| 1.1271        | 4.0   | 1768 | 1.3259          | 0.5846   |
-| 1.1128        | 5.0   | 2210 | 1.2216          | 0.6045   |
-| 1.1869        | 6.0   | 2652 | 1.1650          | 0.6372   |
-| 1.0578        | 7.0   | 3094 | 1.1305          | 0.6447   |
-| 0.7803        | 8.0   | 3536 | 1.0496          | 0.6739   |
-| 0.7118        | 9.0   | 3978 | 1.0651          | 0.6958   |
-| 0.4558        | 10.0  | 4420 | 1.0164          | 0.6998   |
+| 1.7073        | 1.0   | 442  | 1.7346          | 0.4571   |
+| 1.737         | 2.0   | 884  | 1.6044          | 0.4873   |
+| 1.4039        | 3.0   | 1326 | 1.4456          | 0.5454   |
+| 1.222         | 4.0   | 1768 | 1.3590          | 0.5886   |
+| 1.2037        | 5.0   | 2210 | 1.2178          | 0.6119   |
+| 1.2368        | 6.0   | 2652 | 1.2507          | 0.6189   |
+| 1.118         | 7.0   | 3094 | 1.1823          | 0.6337   |
+| 0.9895        | 8.0   | 3536 | 1.1384          | 0.6392   |
+| 0.8918        | 9.0   | 3978 | 1.1026          | 0.6586   |
+| 0.6114        | 10.0  | 4420 | 1.1647          | 0.6447   |
+| 0.9911        | 11.0  | 4862 | 1.0066          | 0.6749   |
+| 0.6572        | 12.0  | 5304 | 1.0767          | 0.6854   |
+| 0.6302        | 13.0  | 5746 | 1.0383          | 0.6908   |
+| 0.638         | 14.0  | 6188 | 1.0830          | 0.6963   |
+| 0.4971        | 15.0  | 6630 | 1.0871          | 0.6913   |
+| 0.4579        | 16.0  | 7072 | 1.1098          | 0.6978   |
+| 0.5697        | 17.0  | 7514 | 1.1443          | 0.7012   |
+| 0.3527        | 18.0  | 7956 | 1.1090          | 0.7047   |
+| 0.3721        | 19.0  | 8398 | 1.1116          | 0.7141   |
+| 0.2936        | 20.0  | 8840 | 1.1248          | 0.7181   |
 
 
 ### Framework versions