update model card README.md

README.md

@@ -21,7 +21,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.785
+      value: 0.81
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,8 +31,8 @@ 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: 1.0228
-- Accuracy: 0.785
+- Loss: 1.2001
+- Accuracy: 0.81
 
 ## Model description
 
@@ -58,32 +58,17 @@ 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: 20
+- num_epochs: 5
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 2.1613        | 1.0   | 100  | 2.1437          | 0.36     |
-| 1.6412        | 2.0   | 200  | 1.4637          | 0.615    |
-| 1.1977        | 3.0   | 300  | 1.1439          | 0.64     |
-| 0.9222        | 4.0   | 400  | 0.9581          | 0.73     |
-| 0.7547        | 5.0   | 500  | 0.8533          | 0.705    |
-| 0.4407        | 6.0   | 600  | 0.7473          | 0.785    |
-| 0.2775        | 7.0   | 700  | 0.8627          | 0.745    |
-| 0.2278        | 8.0   | 800  | 0.7299          | 0.78     |
-| 0.0881        | 9.0   | 900  | 0.7966          | 0.77     |
-| 0.0358        | 10.0  | 1000 | 0.8457          | 0.79     |
-| 0.0192        | 11.0  | 1100 | 0.9054          | 0.775    |
-| 0.0197        | 12.0  | 1200 | 0.9318          | 0.775    |
-| 0.0075        | 13.0  | 1300 | 0.9652          | 0.775    |
-| 0.0058        | 14.0  | 1400 | 0.9544          | 0.785    |
-| 0.0744        | 15.0  | 1500 | 0.9989          | 0.775    |
-| 0.0043        | 16.0  | 1600 | 0.9860          | 0.785    |
-| 0.0039        | 17.0  | 1700 | 1.0023          | 0.79     |
-| 0.0037        | 18.0  | 1800 | 0.9807          | 0.79     |
-| 0.0036        | 19.0  | 1900 | 1.0155          | 0.785    |
-| 0.0034        | 20.0  | 2000 | 1.0228          | 0.785    |
+| 0.0132        | 1.0   | 113  | 1.0964          | 0.84     |
+| 0.0003        | 2.0   | 226  | 1.2606          | 0.8      |
+| 0.1967        | 3.0   | 339  | 1.2266          | 0.8      |
+| 0.0002        | 4.0   | 452  | 1.2578          | 0.81     |
+| 0.0001        | 5.0   | 565  | 1.2001          | 0.81     |
 
 
 ### Framework versions