update model card README.md

README.md

@@ -7,18 +7,18 @@ datasets:
 metrics:
 - accuracy
 model-index:
-- name: distilhubert-finetuned-gtzan
+- name: distilhubert-finetuned-gtzan-1
   results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
 
-# distilhubert-finetuned-gtzan
+# distilhubert-finetuned-gtzan-1
 
 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: 0.5248
+- Loss: 0.5778
 - Accuracy: 0.82
 
 ## Model description
@@ -38,29 +38,35 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 5e-05
-- train_batch_size: 8
-- eval_batch_size: 8
+- learning_rate: 3e-05
+- train_batch_size: 2
+- eval_batch_size: 2
 - seed: 42
+- gradient_accumulation_steps: 4
+- 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: 10
+- num_epochs: 14
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.7671        | 1.0   | 113  | 1.8112          | 0.51     |
-| 1.2122        | 2.0   | 226  | 1.2912          | 0.59     |
-| 1.09          | 3.0   | 339  | 1.0168          | 0.68     |
-| 0.6682        | 4.0   | 452  | 0.7556          | 0.79     |
-| 0.4922        | 5.0   | 565  | 0.6811          | 0.8      |
-| 0.3392        | 6.0   | 678  | 0.5371          | 0.81     |
-| 0.2529        | 7.0   | 791  | 0.5618          | 0.82     |
-| 0.3071        | 8.0   | 904  | 0.5402          | 0.84     |
-| 0.1416        | 9.0   | 1017 | 0.5492          | 0.81     |
-| 0.2921        | 10.0  | 1130 | 0.5248          | 0.82     |
+| 2.103         | 1.0   | 112  | 2.1288          | 0.42     |
+| 1.5948        | 2.0   | 225  | 1.6203          | 0.55     |
+| 1.3883        | 3.0   | 337  | 1.2437          | 0.69     |
+| 1.1032        | 4.0   | 450  | 1.0490          | 0.73     |
+| 0.7595        | 5.0   | 562  | 0.8857          | 0.79     |
+| 0.812         | 6.0   | 675  | 0.7776          | 0.8      |
+| 0.4903        | 7.0   | 787  | 0.7682          | 0.78     |
+| 0.5568        | 8.0   | 900  | 0.7100          | 0.79     |
+| 0.405         | 9.0   | 1012 | 0.6279          | 0.84     |
+| 0.5888        | 10.0  | 1125 | 0.6944          | 0.8      |
+| 0.2576        | 11.0  | 1237 | 0.6027          | 0.83     |
+| 0.2123        | 12.0  | 1350 | 0.5891          | 0.83     |
+| 0.2008        | 13.0  | 1462 | 0.5659          | 0.83     |
+| 0.1343        | 13.94 | 1568 | 0.5778          | 0.82     |
 
 
 ### Framework versions