update model card README.md

README.md

@@ -18,8 +18,8 @@ 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: 0.8078
-- Accuracy: 0.81
+- Loss: 2.2122
+- Accuracy: 0.46
 
 ## Model description
 
@@ -38,34 +38,26 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 5e-05
-- train_batch_size: 12
-- eval_batch_size: 12
+- learning_rate: 1.9710604668225084e-06
+- train_batch_size: 4
+- eval_batch_size: 4
 - seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 8
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 15
+- num_epochs: 5
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 2.1001        | 1.0   | 75   | 2.0810          | 0.45     |
-| 1.563         | 2.0   | 150  | 1.5605          | 0.59     |
-| 1.1348        | 3.0   | 225  | 1.1216          | 0.73     |
-| 0.8687        | 4.0   | 300  | 0.9611          | 0.75     |
-| 0.6107        | 5.0   | 375  | 0.9266          | 0.71     |
-| 0.55          | 6.0   | 450  | 0.7138          | 0.81     |
-| 0.3267        | 7.0   | 525  | 0.7121          | 0.84     |
-| 0.3366        | 8.0   | 600  | 0.7213          | 0.81     |
-| 0.2463        | 9.0   | 675  | 0.7768          | 0.79     |
-| 0.1388        | 10.0  | 750  | 0.8165          | 0.79     |
-| 0.1413        | 11.0  | 825  | 0.7713          | 0.82     |
-| 0.0578        | 12.0  | 900  | 0.7860          | 0.8      |
-| 0.0329        | 13.0  | 975  | 0.7821          | 0.82     |
-| 0.0287        | 14.0  | 1050 | 0.8172          | 0.82     |
-| 0.0277        | 15.0  | 1125 | 0.8078          | 0.81     |
+| 2.2805        | 1.0   | 112  | 2.2812          | 0.25     |
+| 2.2618        | 2.0   | 225  | 2.2510          | 0.32     |
+| 2.24          | 3.0   | 337  | 2.2299          | 0.42     |
+| 2.2191        | 4.0   | 450  | 2.2166          | 0.44     |
+| 2.2425        | 4.98  | 560  | 2.2122          | 0.46     |
 
 
 ### Framework versions