update model card README.md

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.88
+      value: 0.81
 ---
 
 <!-- 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: 1.3004
-- Accuracy: 0.73
+- Loss: 0.7392
+- Accuracy: 0.81
 
 ## Model description
 
@@ -52,7 +52,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 0.0001
+- learning_rate: 5e-05
 - train_batch_size: 32
 - eval_batch_size: 32
 - seed: 42
@@ -61,22 +61,32 @@ 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: 10
+- num_epochs: 20
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 2.3007        | 0.97  | 7    | 2.2260          | 0.34     |
-| 2.2424        | 1.93  | 14   | 2.0328          | 0.39     |
-| 1.9803        | 2.9   | 21   | 1.8298          | 0.41     |
-| 1.8344        | 4.0   | 29   | 1.6637          | 0.52     |
-| 1.608         | 4.97  | 36   | 1.5523          | 0.58     |
-| 1.5644        | 5.93  | 43   | 1.4443          | 0.67     |
-| 1.4354        | 6.9   | 50   | 1.3870          | 0.7      |
-| 1.38          | 8.0   | 58   | 1.3434          | 0.69     |
-| 1.3521        | 8.97  | 65   | 1.3051          | 0.76     |
-| 1.3542        | 9.66  | 70   | 1.3004          | 0.73     |
+| 1.3055        | 0.97  | 7    | 1.2863          | 0.73     |
+| 1.2903        | 1.93  | 14   | 1.2504          | 0.7      |
+| 1.2118        | 2.9   | 21   | 1.1450          | 0.77     |
+| 1.1443        | 4.0   | 29   | 1.1224          | 0.74     |
+| 1.006         | 4.97  | 36   | 1.0376          | 0.79     |
+| 1.0174        | 5.93  | 43   | 0.9681          | 0.8      |
+| 0.9155        | 6.9   | 50   | 0.9322          | 0.81     |
+| 0.8781        | 8.0   | 58   | 0.9266          | 0.78     |
+| 0.819         | 8.97  | 65   | 0.8473          | 0.79     |
+| 0.7984        | 9.93  | 72   | 0.8225          | 0.77     |
+| 0.7254        | 10.9  | 79   | 0.8096          | 0.81     |
+| 0.6752        | 12.0  | 87   | 0.7801          | 0.81     |
+| 0.6132        | 12.97 | 94   | 0.7687          | 0.8      |
+| 0.615         | 13.93 | 101  | 0.7603          | 0.79     |
+| 0.6162        | 14.9  | 108  | 0.7599          | 0.82     |
+| 0.5678        | 16.0  | 116  | 0.7414          | 0.81     |
+| 0.548         | 16.97 | 123  | 0.7423          | 0.81     |
+| 0.5495        | 17.93 | 130  | 0.7378          | 0.81     |
+| 0.5185        | 18.9  | 137  | 0.7396          | 0.81     |
+| 0.5544        | 19.31 | 140  | 0.7392          | 0.81     |
 
 
 ### Framework versions