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: 1.1326
-- Accuracy: 0.86
+- Loss: 0.7824
+- Accuracy: 0.8
 
 ## Model description
 
@@ -39,40 +39,25 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 5e-05
-- train_batch_size: 4
-- eval_batch_size: 4
+- train_batch_size: 8
+- eval_batch_size: 8
 - seed: 42
 - distributed_type: multi-GPU
 - 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
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 2.0942        | 1.0   | 225  | 1.9649          | 0.33     |
-| 1.1113        | 2.0   | 450  | 1.2162          | 0.74     |
-| 0.7961        | 3.0   | 675  | 0.9466          | 0.7      |
-| 0.9005        | 4.0   | 900  | 0.6644          | 0.83     |
-| 0.3228        | 5.0   | 1125 | 0.5374          | 0.85     |
-| 0.4422        | 6.0   | 1350 | 0.7370          | 0.76     |
-| 0.1283        | 7.0   | 1575 | 0.7234          | 0.84     |
-| 0.0076        | 8.0   | 1800 | 0.8727          | 0.85     |
-| 0.0037        | 9.0   | 2025 | 0.9373          | 0.84     |
-| 0.1723        | 10.0  | 2250 | 0.9524          | 0.86     |
-| 0.0016        | 11.0  | 2475 | 1.0349          | 0.84     |
-| 0.0016        | 12.0  | 2700 | 1.0471          | 0.85     |
-| 0.0011        | 13.0  | 2925 | 1.0802          | 0.85     |
-| 0.0009        | 14.0  | 3150 | 1.0722          | 0.85     |
-| 0.0007        | 15.0  | 3375 | 1.0931          | 0.85     |
-| 0.0007        | 16.0  | 3600 | 1.1442          | 0.85     |
-| 0.0007        | 17.0  | 3825 | 1.1239          | 0.85     |
-| 0.0005        | 18.0  | 4050 | 1.1810          | 0.85     |
-| 0.0006        | 19.0  | 4275 | 1.1560          | 0.85     |
-| 0.0005        | 20.0  | 4500 | 1.1326          | 0.86     |
+| 1.6129        | 1.0   | 113  | 1.7019          | 0.52     |
+| 1.1591        | 2.0   | 226  | 1.1881          | 0.73     |
+| 1.0244        | 3.0   | 339  | 0.9023          | 0.8      |
+| 0.7501        | 4.0   | 452  | 0.8744          | 0.72     |
+| 0.6153        | 5.0   | 565  | 0.7824          | 0.8      |
 
 
 ### Framework versions