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: 1.2425
-- Accuracy: 0.84
+- Loss: 0.7186
+- Accuracy: 0.86
 
 ## Model description
 
@@ -38,34 +38,32 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 0.0005
+- learning_rate: 0.0001
 - train_batch_size: 8
-- eval_batch_size: 12
+- eval_batch_size: 16
 - seed: 42
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-05
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 15
+- num_epochs: 12
+- label_smoothing_factor: 0.05
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.2069        | 1.0   | 113  | 1.3361          | 0.5      |
-| 1.5776        | 2.0   | 226  | 1.4992          | 0.43     |
-| 1.2343        | 3.0   | 339  | 1.2779          | 0.48     |
-| 0.8813        | 4.0   | 452  | 1.2418          | 0.62     |
-| 0.8836        | 5.0   | 565  | 0.9679          | 0.71     |
-| 0.7827        | 6.0   | 678  | 0.9275          | 0.7      |
-| 0.4979        | 7.0   | 791  | 1.2511          | 0.69     |
-| 0.466         | 8.0   | 904  | 1.0917          | 0.73     |
-| 0.6358        | 9.0   | 1017 | 0.7578          | 0.81     |
-| 0.5371        | 10.0  | 1130 | 1.2664          | 0.72     |
-| 0.0353        | 11.0  | 1243 | 1.2281          | 0.77     |
-| 0.0159        | 12.0  | 1356 | 1.5949          | 0.73     |
-| 0.0011        | 13.0  | 1469 | 1.0783          | 0.85     |
-| 0.0007        | 14.0  | 1582 | 1.3324          | 0.82     |
-| 0.0007        | 15.0  | 1695 | 1.2425          | 0.84     |
+| 1.7045        | 1.0   | 113  | 1.7952          | 0.44     |
+| 1.1808        | 2.0   | 226  | 1.1510          | 0.66     |
+| 1.0978        | 3.0   | 339  | 0.9947          | 0.74     |
+| 0.837         | 4.0   | 452  | 0.8767          | 0.81     |
+| 0.5078        | 5.0   | 565  | 0.7830          | 0.86     |
+| 0.3832        | 6.0   | 678  | 0.7838          | 0.84     |
+| 0.3902        | 7.0   | 791  | 0.8064          | 0.83     |
+| 0.3322        | 8.0   | 904  | 0.7964          | 0.82     |
+| 0.3455        | 9.0   | 1017 | 0.7507          | 0.87     |
+| 0.2924        | 10.0  | 1130 | 0.8073          | 0.86     |
+| 0.2925        | 11.0  | 1243 | 0.7269          | 0.86     |
+| 0.2853        | 12.0  | 1356 | 0.7186          | 0.86     |
 
 
 ### Framework versions