update model card README.md

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.82
+      value: 0.85
 ---
 
 <!-- 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 [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.6713
-- Accuracy: 0.82
+- Loss: 0.6094
+- Accuracy: 0.85
 
 ## Model description
 
@@ -56,25 +56,33 @@ The following hyperparameters were used during training:
 - train_batch_size: 8
 - eval_batch_size: 8
 - seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 10
+- num_epochs: 16
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.953         | 1.0   | 113  | 1.7624          | 0.5      |
-| 1.2656        | 2.0   | 226  | 1.2034          | 0.6      |
-| 0.9781        | 3.0   | 339  | 0.9160          | 0.76     |
-| 0.7901        | 4.0   | 452  | 0.7705          | 0.79     |
-| 0.648         | 5.0   | 565  | 0.6881          | 0.82     |
-| 0.2913        | 6.0   | 678  | 0.6096          | 0.8      |
-| 0.3783        | 7.0   | 791  | 0.5663          | 0.86     |
-| 0.1145        | 8.0   | 904  | 0.6054          | 0.82     |
-| 0.1967        | 9.0   | 1017 | 0.5824          | 0.83     |
-| 0.1393        | 10.0  | 1130 | 0.6713          | 0.82     |
+| 2.1935        | 0.99  | 56   | 2.1282          | 0.42     |
+| 1.6089        | 2.0   | 113  | 1.5367          | 0.57     |
+| 1.2446        | 2.99  | 169  | 1.1485          | 0.74     |
+| 0.98          | 4.0   | 226  | 0.9621          | 0.76     |
+| 0.7296        | 4.99  | 282  | 0.7948          | 0.82     |
+| 0.5111        | 6.0   | 339  | 0.7578          | 0.79     |
+| 0.583         | 6.99  | 395  | 0.6152          | 0.86     |
+| 0.4002        | 8.0   | 452  | 0.5863          | 0.85     |
+| 0.2924        | 8.99  | 508  | 0.5834          | 0.84     |
+| 0.1789        | 10.0  | 565  | 0.6087          | 0.85     |
+| 0.1181        | 10.99 | 621  | 0.5911          | 0.84     |
+| 0.0673        | 12.0  | 678  | 0.5887          | 0.85     |
+| 0.0633        | 12.99 | 734  | 0.6294          | 0.84     |
+| 0.0393        | 14.0  | 791  | 0.6205          | 0.84     |
+| 0.0362        | 14.99 | 847  | 0.6382          | 0.85     |
+| 0.0328        | 15.86 | 896  | 0.6094          | 0.85     |
 
 
 ### Framework versions