update model card README.md

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.35
+      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: 2.1821
-- Accuracy: 0.35
+- Loss: 0.5868
+- Accuracy: 0.85
 
 ## Model description
 
@@ -52,7 +52,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 1e-06
+- learning_rate: 5e-05
 - train_batch_size: 8
 - eval_batch_size: 8
 - seed: 42
@@ -65,17 +65,17 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 2.2909        | 1.0   | 113  | 2.2939          | 0.16     |
-| 2.2793        | 2.0   | 226  | 2.2789          | 0.2      |
-| 2.2729        | 3.0   | 339  | 2.2617          | 0.19     |
-| 2.2645        | 4.0   | 452  | 2.2446          | 0.28     |
-| 2.2211        | 5.0   | 565  | 2.2290          | 0.29     |
-| 2.2382        | 6.0   | 678  | 2.2162          | 0.31     |
-| 2.2631        | 7.0   | 791  | 2.2039          | 0.31     |
-| 2.247         | 8.0   | 904  | 2.1946          | 0.32     |
-| 2.2255        | 9.0   | 1017 | 2.1877          | 0.33     |
-| 2.1932        | 10.0  | 1130 | 2.1834          | 0.35     |
-| 2.2213        | 11.0  | 1243 | 2.1821          | 0.35     |
+| 1.8862        | 1.0   | 113  | 1.6953          | 0.43     |
+| 1.244         | 2.0   | 226  | 1.1139          | 0.64     |
+| 0.9373        | 3.0   | 339  | 0.9080          | 0.74     |
+| 0.7731        | 4.0   | 452  | 0.7958          | 0.74     |
+| 0.5718        | 5.0   | 565  | 0.6637          | 0.81     |
+| 0.3095        | 6.0   | 678  | 0.6204          | 0.84     |
+| 0.391         | 7.0   | 791  | 0.6014          | 0.82     |
+| 0.1033        | 8.0   | 904  | 0.5147          | 0.87     |
+| 0.1199        | 9.0   | 1017 | 0.5189          | 0.86     |
+| 0.1336        | 10.0  | 1130 | 0.5594          | 0.87     |
+| 0.0549        | 11.0  | 1243 | 0.5868          | 0.85     |
 
 
 ### Framework versions